Classification in Medical Image Analysis Using Adaptive Metric KNN
DEFF Research Database (Denmark)
Chen, Chen; Chernoff, Konstantin; Karemore, Gopal Raghunath;
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 with r......, where we use k-NN for breast cancer risk assessment. The results show that appropriate choice of metric can improve classification....... 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...
Adaptative initialisation of a EvKNN classification algorithm
Chan Wai Tim, Stefen; Rombaut, Michele; Pellerin, Denis
2012-01-01
International audience; The establishment of the learning data base is a long and tedious task that must be carried out before starting the classification process. An Evidential KNN (EvKNN) has been developed in order to help the user, which proposes the "best" samples to label according to a strategy. However, at the beginning of this task, the classes are not clearly defined and are represented by a number of labeled samples smaller than the k required samples for EvKNN. In this paper, we p...
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...
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 the...
Multiclass Boosting with Adaptive Group-Based kNN and Its Application in Text Categorization
Directory of Open Access Journals (Sweden)
Lei La
2012-01-01
Full Text Available AdaBoost is an excellent committee-based tool for classification. However, its effectiveness and efficiency in multiclass categorization face the challenges from methods based on support vector machine (SVM, neural networks (NN, naïve Bayes, and k-nearest neighbor (kNN. This paper uses a novel multi-class AdaBoost algorithm to avoid reducing the multi-class classification problem to multiple two-class classification problems. This novel method is more effective. In addition, it keeps the accuracy advantage of existing AdaBoost. An adaptive group-based kNN method is proposed in this paper to build more accurate weak classifiers and in this way control the number of basis classifiers in an acceptable range. To further enhance the performance, weak classifiers are combined into a strong classifier through a double iterative weighted way and construct an adaptive group-based kNN boosting algorithm (AGkNN-AdaBoost. We implement AGkNN-AdaBoost in a Chinese text categorization system. Experimental results showed that the classification algorithm proposed in this paper has better performance both in precision and recall than many other text categorization methods including traditional AdaBoost. In addition, the processing speed is significantly enhanced than original AdaBoost and many other classic categorization algorithms.
Fuzzy Optimized Metric for Adaptive Network Routing
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Ahmad Khader Haboush
2012-04-01
Full Text Available Network routing algorithms used today calculate least cost (shortest paths between nodes. The cost of a path is the sum of the cost of all links on that path. The use of a single metric for adaptive routing is insufficient to reflect the actual state of the link. In general, there is a limitation on the accuracy of the link state information obtained by the routing protocol. Hence it becomes useful if two or more metrics can be associated to produce a single metric that can describe the state of the link more accurately. In this paper, a fuzzy inference rule base is implemented to generate the fuzzy cost of each candidate path to be used in routing the incoming calls. This fuzzy cost is based on the crisp values of the different metrics; a fuzzy membership function is defined. The parameters of these membership functions reflect dynamically the requirement of the incoming traffic service as well as the current state of the links in the path. And this paper investigates how three metrics, the mean link bandwidth, queue utilization and the mean link delay, can be related using a simple fuzzy logic algorithm to produce a optimized cost of the link for a certain interval that is more „precise‟ than either of the single metric, to solve routing problem .
An Adaptable Metric Shapes Perceptual Space.
Hisakata, Rumi; Nishida, Shin'ya; Johnston, Alan
2016-07-25
How do we derive a sense of the separation of points in the world within a space-variant visual system? Visual directions are thought to be coded directly by a process referred to as local sign, in which a neuron acts as a labeled line for the perceived direction associated with its activation [1, 2]. The separations of visual directions, however, are not given, nor are they directly related to the separations of signals on the receptive surface or in the brain, which are modified by retinal and cortical magnification, respectively [3]. To represent the separation of directions veridically, the corresponding neural signals need to be scaled in some way. We considered this scaling process may be influenced by adaptation. Here, we describe a novel adaptation paradigm, which can alter both apparent spatial separation and size. We measured the perceived separation of two dots and the size of geometric figures after adaptation to random dot patterns. We show that adapting to high-density texture not only increases the apparent sparseness (average element separation) of a lower-density pattern, as expected [4], but paradoxically, it reduces the apparent separation of dot pairs and induces apparent shrinkage of geometric form. This demonstrates for the first time a contrary linkage between perceived density and perceived extent. Separation and size appear to be expressed relative to a variable spatial metric whose properties, while not directly observable, are revealed by reductions in both apparent size and texture density. PMID:27426520
Directory of Open Access Journals (Sweden)
J. Sofia Priya Dharshini
2014-09-01
Full Text Available In MIMO Technology, a cross layer design enhances the spectral efficiency, reliability and throughput of the network. In this paper, a cross-layer approach using k-NN based Adaptive Modulation Coding (AMC and Incremental Redundancy Hybrid Automatic Repeat Request (IR-HARQ is proposed for MIMO Systems. The proposed cross layer approach connects physical layer and data link layer to enhance the performance of MIMO network. By means of MIMO fading channels, the coded symbols are forwarded in the physical layer on a frame by frame fashion subsequently using Space Time Block Coding (STBC. The receiver computes the signal to noise ratio (SNR and forwards back to the AMC controller. The controller selects a suitable MCS for the next transmission through k-NN classifier supervised learning algorithm. IR-HARQ is utilized at the data link layer to regulate packet retransmissions. The obtained results prove that the proposed technique has better performance in terms of throughput, BER and spectral efficiency
A Unified View of Adaptive Variable-Metric Projection Algorithms
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Masahiro Yukawa
2009-01-01
Full Text Available We present a unified analytic tool named variable-metric adaptive projected subgradient method (V-APSM that encompasses the important family of adaptive variable-metric projection algorithms. The family includes the transform-domain adaptive filter, the Newton-method-based adaptive filters such as quasi-Newton, the proportionate adaptive filter, and the Krylov-proportionate adaptive filter. We provide a rigorous analysis of V-APSM regarding several invaluable properties including monotone approximation, which indicates stable tracking capability, and convergence to an asymptotically optimal point. Small metric-fluctuations are the key assumption for the analysis. Numerical examples show (i the robustness of V-APSM against violation of the assumption and (ii the remarkable advantages over its constant-metric counterpart for colored and nonstationary inputs under noisy situations.
Applicability of Existing Objective Metrics of Perceptual Quality for Adaptive Video Streaming
DEFF Research Database (Denmark)
Søgaard, Jacob; Krasula, Lukás; Shahid, Muhammad;
2016-01-01
Objective video quality metrics are designed to estimate the quality of experience of the end user. However, these objective metrics are usually validated with video streams degraded under common distortion types. In the presented work, we analyze the performance of published and known full......-reference and noreference quality metrics in estimating the perceived quality of adaptive bit-rate video streams knowingly out of scope. Experimental results indicate not surprisingly that state of the art objective quality metrics overlook the perceived degradations in the adaptive video streams and perform poorly...
Large-Margin kNN Classification Using a Deep Encoder Network
Min, Martin Renqiang; Stanley, David A.; Yuan, Zineng; Bonner, Anthony; Zhang, Zhaolei
2009-01-01
KNN is one of the most popular classification methods, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. Linear feature transformation methods have been widely applied to extract class-relevant information to improve kNN classification, which is very limited in many applications. Kernels have been used to learn powerful non-linear feature transformations, but these methods fail to scale to large datasets....
Adapting Binary Information Retrieval Evaluation Metrics for Segment-based Retrieval Tasks
Aly, Robin; Eskevich, Maria; Ordelman, Roeland; Jones, Gareth J.F.
2013-01-01
This report describes metrics for the evaluation of the effectiveness of segment-based retrieval based on existing binary information retrieval metrics. This metrics are described in the context of a task for the hyperlinking of video segments. This evaluation approach re-uses existing evaluation measures from the standard Cranfield evaluation paradigm. Our adaptation approach can in principle be used with any kind of effectiveness measure that uses binary relevance, and for other segment-bae...
Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning
DEFF Research Database (Denmark)
Søgaard, Jacob; Forchhammer, Søren; Brunnström, Kjell
2015-01-01
Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method...
Large-Margin kNN Classification Using a Deep Encoder Network
Min, Martin Renqiang; Yuan, Zineng; Bonner, Anthony; Zhang, Zhaolei
2009-01-01
KNN is one of the most popular classification methods, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. Linear feature transformation methods have been widely applied to extract class-relevant information to improve kNN classification, which is very limited in many applications. Kernels have been used to learn powerful non-linear feature transformations, but these methods fail to scale to large datasets. In this paper, we present a scalable non-linear feature mapping method based on a deep neural network pretrained with restricted boltzmann machines for improving kNN classification in a large-margin framework, which we call DNet-kNN. DNet-kNN can be used for both classification and for supervised dimensionality reduction. The experimental results on two benchmark handwritten digit datasets show that DNet-kNN has much better performance than large-margin kNN using a linear mapping and kNN based on a deep autoencoder pretr...
QRS detection using K-Nearest Neighbor algorithm (KNN and evaluation on standard ECG databases
Directory of Open Access Journals (Sweden)
Indu Saini
2013-07-01
Full Text Available The performance of computer aided ECG analysis depends on the precise and accurate delineation of QRS-complexes. This paper presents an application of K-Nearest Neighbor (KNN algorithm as a classifier for detection of QRS-complex in ECG. The proposed algorithm is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhythmia database. In this work, a digital band-pass filter is used to reduce false detection caused by interference present in ECG signal and further gradient of the signal is used as a feature for QRS-detection. In addition the accuracy of KNN based classifier is largely dependent on the value of K and type of distance metric. The value of K = 3 and Euclidean distance metric has been proposed for the KNN classifier, using fivefold cross-validation. The detection rates of 99.89% and 99.81% are achieved for CSE and MIT-BIH databases respectively. The QRS detector obtained a sensitivity Se = 99.86% and specificity Sp = 99.86% for CSE database, and Se = 99.81% and Sp = 99.86% for MIT-BIH Arrhythmia database. A comparison is also made between proposed algorithm and other published work using CSE and MIT-BIH Arrhythmia databases. These results clearly establishes KNN algorithm for reliable and accurate QRS-detection.
QRS detection using K-Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases.
Saini, Indu; Singh, Dilbag; Khosla, Arun
2013-07-01
The performance of computer aided ECG analysis depends on the precise and accurate delineation of QRS-complexes. This paper presents an application of K-Nearest Neighbor (KNN) algorithm as a classifier for detection of QRS-complex in ECG. The proposed algorithm is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhythmia database. In this work, a digital band-pass filter is used to reduce false detection caused by interference present in ECG signal and further gradient of the signal is used as a feature for QRS-detection. In addition the accuracy of KNN based classifier is largely dependent on the value of K and type of distance metric. The value of K = 3 and Euclidean distance metric has been proposed for the KNN classifier, using fivefold cross-validation. The detection rates of 99.89% and 99.81% are achieved for CSE and MIT-BIH databases respectively. The QRS detector obtained a sensitivity Se = 99.86% and specificity Sp = 99.86% for CSE database, and Se = 99.81% and Sp = 99.86% for MIT-BIH Arrhythmia database. A comparison is also made between proposed algorithm and other published work using CSE and MIT-BIH Arrhythmia databases. These results clearly establishes KNN algorithm for reliable and accurate QRS-detection.
An Adaptive Steganographic Method in Frequency Domain Based on Statistical Metrics of Image
Directory of Open Access Journals (Sweden)
Seyyed Amin Seyyedi
2015-05-01
Full Text Available Steganography is a branch of information hiding. A tradeoff between the hiding payload and quality of digital image steganographic schemes is major challenge of the steganographic methods. An adaptive steganographic method for embedding secret message into gray scale images is proposed. Before embedding the secret message, the cover image is transformed into frequency domain by integer wavelet. The middle frequency band of cover image is partitioned into 4×4 non overlapping blocks. The blocks by deviation and entropy metrics are classified into three categories: smooth, edge, and texture regions. Number of bits which can be embedded in a block is defined by block features. Moreover, RC4 encryption method is used to increase secrecy protection. Experimental results denote the feasibility of the proposed method. Statistical tests were conducted to collect related data to verify the security of method.
Optimal stellar photometry for multi-conjugate adaptive optics systems using science-based metrics
Turri, P; Stetson, P B; Fiorentino, G; Andersen, D R; Bono, G; Massari, D; Veran, J -P
2016-01-01
We present a detailed discussion of how to obtain precise stellar photometry in crowded fields using images obtained with multi-conjugate adaptive optics (MCAO), with the intent of informing the scientific development of this key technology for the Extremely Large Telescopes. We use deep J and K$_\\mathrm{s}$ exposures of NGC 1851 obtained using the Gemini Multi-Conjugate Adaptive Optics System (GeMS) on Gemini South to quantify the performance of the system and to develop an optimal strategy for extracting precise stellar photometry from the images using well-known PSF-fitting techniques. We judge the success of the various techniques we employ by using science-based metrics, particularly the width of the main sequence turn-off region. We also compare the GeMS photometry with the exquisite HST data of the same target in the visible. We show that the PSF produced by GeMS possesses significant spatial and temporal variability that must be accounted for during the photometric analysis by allowing the PSF model a...
Directory of Open Access Journals (Sweden)
Karsten Schulz
2009-11-01
Full Text Available Nearest neighbor techniques are commonly used in remote sensing, pattern recognition and statistics to classify objects into a predefined number of categories based on a given set of predictors. These techniques are especially useful for highly nonlinear relationship between the variables. In most studies the distance measure is adopted a priori. In contrast we propose a general procedure to find an adaptive metric that combines a local variance reducing technique and a linear embedding of the observation space into an appropriate Euclidean space. To illustrate the application of this technique, two agricultural land cover classifications using mono-temporal and multi-temporal Landsat scenes are presented. The results of the study, compared with standard approaches used in remote sensing such as maximum likelihood (ML or k-Nearest Neighbor (k-NN indicate substantial improvement with regard to the overall accuracy and the cardinality of the calibration data set. Also, using MNN in a soft/fuzzy classification framework demonstrated to be a very useful tool in order to derive critical areas that need some further attention and investment concerning additional calibration data.
Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus
2014-01-01
Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.
Spatial Queries with Two kNN Predicates
Aly, Ahmed M; Aref, Walid G.; Ouzzani, Mourad
2012-01-01
The widespread use of location-aware devices has led to countless location-based services in which a user query can be arbitrarily complex, i.e., one that embeds multiple spatial selection and join predicates. Amongst these predicates, the k-Nearest-Neighbor (kNN) predicate stands as one of the most important and widely used predicates. Unlike related research, this paper goes beyond the optimization of queries with single kNN predicates, and shows how queries with two kNN predicates can be o...
Self-organized manifold learning and heuristic charting via adaptive metrics
Horvath, Denis; Brutovsky, Branislav
2014-01-01
Classical metric and non-metric multidimensional scaling (MDS) variants are widely known manifold learning (ML) methods which enable construction of low dimensional representation (projections) of high dimensional data inputs. However, their use is crucially limited to the cases when data are inherently reducible to low dimensionality. In general, drawbacks and limitations of these, as well as pure, MDS variants become more apparent when the exploration (learning) is exposed to the structured data of high intrinsic dimension. As we demonstrate on artificial and real-world datasets, the over-determination problem can be solved by means of the hybrid and multi-component discrete-continuous multi-modal optimization heuristics. Its remarkable feature is, that projections onto 2D are constructed simultaneously with the data categorization (classification) compensating in part for the loss of original input information. We observed, that the optimization module integrated with ML modeling, metric learning and categ...
metricDTW: local distance metric learning in Dynamic Time Warping
Zhao, Jiaping; Xi, Zerong; Itti, Laurent
2016-01-01
We propose to learn multiple local Mahalanobis distance metrics to perform k-nearest neighbor (kNN) classification of temporal sequences. Temporal sequences are first aligned by dynamic time warping (DTW); given the alignment path, similarity between two sequences is measured by the DTW distance, which is computed as the accumulated distance between matched temporal point pairs along the alignment path. Traditionally, Euclidean metric is used for distance computation between matched pairs, wh...
Cogntive Consistency Analysis in Adaptive Bio-Metric Authentication System Design
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Gahangir Hossain
2015-07-01
Full Text Available Cognitive consistency analysis aims to continuously monitor one's perception equilibrium towards successful accomplishment of cognitive task. Opposite to cognitive flexibility analysis – cognitive consistency analysis identifies monotone of perception towards successful interaction process (e.g., biometric authentication and useful in generation of decision support to assist one in need. This study consider fingertip dynamics (e.g., keystroke, tapping, clicking etc. to have insights on instantaneous cognitive states and its effects in monotonic advancement towards successful authentication process. Keystroke dynamics and tapping dynamics are analyzed based on response time data. Finally, cognitive consistency and confusion (inconsistency are computed with Maximal Information Coefficient (MIC and Maximal Asymmetry Score (MAS, respectively. Our preliminary study indicates that a balance between cognitive consistency and flexibility are needed in successful authentication process. Moreover, adaptive and cognitive interaction system requires in depth analysis of user’s cognitive consistency to provide a robust and useful assistance.
Adaptive ant-based routing in wireless sensor networks using Energy Delay metrics
Institute of Scientific and Technical Information of China (English)
Yao-feng WEN; Yu-quan CHEN; Min PAN
2008-01-01
To find the optimal routing is always an important topic in wireless sensor networks (WSNs). Considering a WSN where the nodes have limited energy, we propose a novel Energy*Delay model based on ant algorithms ("E&D ANTS" for short)to minimize the time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the tradeoff of energy and delay in wireless network systems, the reinforcement learning (RL) algorithm is introduced to train the model. In this survey, the paradigm of E&D ANTS is explicated and compared to other ant-based routing algorithms like AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy cost and delay per round.
A Novel Approach for the Diagnosis of Diabetes and Liver Cancer using ANFIS and Improved KNN
Directory of Open Access Journals (Sweden)
C. Kalaiselvi
2014-07-01
Full Text Available The multi-factorial, chronicle, severe diseases are cancer and diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure and cancer. Many studies have been proved that several types of cancer are possible in diabetes patients having a high blood sugar. Many approaches are proposed in the past to diagnose both cancer and diabetes. Even though the existing approaches are efficient one, the classification accuracy is poor. An Enhanced approach is proposed to achieve a higher efficiency and lower complexity. Adaptive neuro fuzzy inference system is used to classify the dataset with the help of adaptive group based KNN. The Pima Indian diabetes dataset are used as input dataset and classified based on the attribute information. The experimental result shows the classification accuracy is better than the existing approaches such FLANN, ANN with FUZZYKNN.
Prediksi Inflasi di Indonesia Menggunakan Algoritma K- Nearest Neighbor (KNN)
Harahap, Nency Lestari
2015-01-01
Developed country is a country that has a strong economy and stability. One of the main indicators used to see the development of the economy of a country is the level of inflation. Therefore, a prediction of inflation important in order to assist the government in making policy to maintain economic stability. In this research, KNearest Neighbor algorithm (KNN) predict inflation based on the exchange rate, the BI Rate, money supply and Gross Domestic Product and inflation rate ...
A hybrid KNN-MLP algorithm to diagnose bipolar disorder
Mozhgan Mohammad Ghasemi; Mehdi Khalili
2014-01-01
In this paper an attempt has been made to the other corner of the power of neural networks. According to the neural network in the diagnosis of diseases, we use neural network models for diagnosing bipolar disorder; bipolar disorder is the common disorder of depression mood. We have used two neural network models: MLP & KNN. With different percentages of the implementation of neural network models is discussed. And the error was calculated for each model. We can by using the MLP model achieve...
A hybrid KNN-MLP algorithm to diagnose bipolar disorder
Directory of Open Access Journals (Sweden)
Mozhgan Mohammad Ghasemi
2014-12-01
Full Text Available In this paper an attempt has been made to the other corner of the power of neural networks. According to the neural network in the diagnosis of diseases, we use neural network models for diagnosing bipolar disorder; bipolar disorder is the common disorder of depression mood. We have used two neural network models: MLP & KNN. With different percentages of the implementation of neural network models is discussed. And the error was calculated for each model. We can by using the MLP model achieve an error of 16% for the diagnosis of bipolar disorder.
International Nuclear Information System (INIS)
To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land–atmosphere interactions in response to LCLUC. (letter)
Metric Education Evaluation Package.
Kansky, Bob; And Others
This document was developed out of a need for a complete, carefully designed set of evaluation instruments and procedures that might be applied in metric inservice programs across the nation. Components of this package were prepared in such a way as to permit local adaptation to the evaluation of a broad spectrum of metric education activities.…
AN EFFICIENT TEXT CLASSIFICATION USING KNN AND NAIVE BAYESIAN
Directory of Open Access Journals (Sweden)
J.Sreemathy
2012-03-01
Full Text Available The main objective is to propose a text classification based on the features selection and preprocessing thereby reducing the dimensionality of the Feature vector and increase the classificationaccuracy. Text classification is the process of assigning a document to one or more target categories, based on its contents. In the proposed method, machine learning methods for text classification is used to apply some text preprocessing methods in different dataset, and then to extract feature vectors for each new document by using various feature weighting methods for enhancing the text classification accuracy. Further training the classifier by Naive Bayesian (NB and K-nearest neighbor (KNN algorithms, the predication can be made according to the category distribution among this k nearest neighbors.Experimental results show that the methods are favorable in terms of their effectiveness and efficiencywhen compared with other classifier such as SVM.
Synthesis and characterizations of BNT-BT-KNN ceramics for energy storage applications
Chandrasekhar, M.; Kumar, P.
2016-09-01
Dielectric, ferroelectric and piezoelectric properties of the (0.94-x) Bi0.5Na0.5TiO3-0.06BaTiO3-xK0.5Na0.5NbO3/BNT-BT-KNN ceramics with x = 0.02 and 0.05 (2KNN and 5KNN) were studied in detail. Dielectric study and temperature-dependent polarization hysteresis loops indicated a ferroelectric-to-antiferroelectric transition at depolarization temperature (Td). The low Td in both the ceramic samples suggested the dominant antiferroelectric ordering at room temperature (RT), which was also confirmed by RT polarization and strain hysteresis loops studies. Antiferroelectric-to-paraelectric phase transition temperature (Tm) was nearly same for both systems. The 5KNN ceramic samples showed the relaxor behaviour. The values of the dielectric constant, Td, and maximum strain percentage increased, whereas the coercive field and remnant polarization decreased with the increase of the KNN percentage in the BNT-BT-KNN system. High-energy storage density ∼0.5 J/cm3 at RT hinted about the suitability of the 5KNN system for energy storage applications.
Scalable Large-Margin Mahalanobis Distance Metric Learning
Shen, Chunhua; Wang, Lei
2010-01-01
For many machine learning algorithms such as $k$-Nearest Neighbor ($k$-NN) classifiers and $ k $-means clustering, often their success heavily depends on the metric used to calculate distances between different data points. An effective solution for defining such a metric is to learn it from a set of labeled training samples. In this work, we propose a fast and scalable algorithm to learn a Mahalanobis distance metric. By employing the principle of margin maximization to achieve better generalization performances, this algorithm formulates the metric learning as a convex optimization problem and a positive semidefinite (psd) matrix is the unknown variable. a specialized gradient descent method is proposed. our algorithm is much more efficient and has a better performance in scalability compared with existing methods. Experiments on benchmark data sets suggest that, compared with state-of-the-art metric learning algorithms, our algorithm can achieve a comparable classification accuracy with reduced computation...
公路网移动终端的KNN查询技术%KNN Query Technology of Mobile Terminals in Highway Networks
Institute of Scientific and Technical Information of China (English)
梁茹冰; 刘琼
2012-01-01
The dynamic POIs (Points of Interest) in highway networks are difficult to query. Most current researches focus only on the static POIs with the help of the Euclidean distance metrics, which are inefficient for the weak connection and frequent movement of mobile terminals in mobile computing environments. In order to solve this problem, a structure to store cell data objects is designed to describe the highway network graph model, and a continuous KNN (K-Nearest Neighbor) query (CQ-KNN) algorithm for mobile terminals is presented. For the purpose of improving the existing MKNN algorithm proposed by Wang et al, CQ-KNN algorithm combines the progressive probe and the edge information list retrieval, thus saving the cost of range query execution in MKNN algorithm when fixed layers are insufficient. Moreover, CQ-KNN algorithm employs the local cache strategy to support the continuous query of mobile terminals and adopts the cache consistency maintenance strategy based on the invalid broadcast location report. Simulated results show that CQ-KNN algorithm is superior to MKNN algorithm in terms of CPU processing speed and network response delay, and that it effectively supports the off-line approximate KNN query of mobile terminals.%公路网中移动兴趣点(POIs)的查询处理是一个难点,目前的研究多基于欧氏距离对静态POIs进行处理,不能很好地适应移动环境下终端弱连接和频繁移动的需要.文中在公路网移动计算场景下,设计了一种存储分区数据对象的结构来表示公路网图形模型,提出适用于移动终端的连续KNN查询(CQ-KNN)算法.该算法改进了Wang等提出的MKNN算法,将逐层渐近探测和检索边列表结合起来进行近邻查询,避免了MKNN算法在限定层数不够却不得不执行范围查询时所带来的开销；同时使用缓存策略来支持移动终端提交的连续查询请求,并给出基于广播位置失效报告的缓存一致性维
López-Hoffman, Laura; Breshears, David D.; Allen, Craig D.; Miller, Marc L.
2013-01-01
Under a changing climate, devising strategies to help stakeholders adapt to alterations to ecosystems and their services is of utmost importance. In western North America, diminished snowpack and river flows are causing relatively gradual, homogeneous (system-wide) changes in ecosystems and services. In addition, increased climate variability is also accelerating the incidence of abrupt and patchy disturbances such as fires, floods and droughts. This paper posits that two key variables often considered in landscape ecology—the rate of change and the degree of patchiness of change—can aid in developing climate change adaptation strategies. We use two examples from the “borderland” region of the southwestern United States and northwestern Mexico. In piñon-juniper woodland die-offs that occurred in the southwestern United States during the 2000s, ecosystem services suddenly crashed in some parts of the system while remaining unaffected in other locations. The precise timing and location of die-offs was uncertain. On the other hand, slower, homogeneous change, such as the expected declines in water supply to the Colorado River delta, will likely impact the entire ecosystem, with ecosystem services everywhere in the delta subject to alteration, and all users likely exposed. The rapidity and spatial heterogeneity of faster, patchy climate change exemplified by tree die-off suggests that decision-makers and local stakeholders would be wise to operate under a Rawlsian “veil of ignorance,” and implement adaptation strategies that allow ecosystem service users to equitably share the risk of sudden loss of ecosystem services before actual ecosystem changes occur. On the other hand, in the case of slower, homogeneous, system-wide impacts to ecosystem services as exemplified by the Colorado River delta, adaptation strategies can be implemented after the changes begin, but will require a fundamental rethinking of how ecosystems and services are used and valued. In
Klauder, J R
1998-01-01
Canonical quantization may be approached from several different starting points. The usual approaches involve promotion of c-numbers to q-numbers, or path integral constructs, each of which generally succeeds only in Cartesian coordinates. All quantization schemes that lead to Hilbert space vectors and Weyl operators---even those that eschew Cartesian coordinates---implicitly contain a metric on a flat phase space. This feature is demonstrated by studying the classical and quantum ``aggregations'', namely, the set of all facts and properties resident in all classical and quantum theories, respectively. Metrical quantization is an approach that elevates the flat phase space metric inherent in any canonical quantization to the level of a postulate. Far from being an unwanted structure, the flat phase space metric carries essential physical information. It is shown how the metric, when employed within a continuous-time regularization scheme, gives rise to an unambiguous quantization procedure that automatically ...
GPU-FS-kNN: a software tool for fast and scalable kNN computation using GPUs.
Directory of Open Access Journals (Sweden)
Ahmed Shamsul Arefin
Full Text Available BACKGROUND: The analysis of biological networks has become a major challenge due to the recent development of high-throughput techniques that are rapidly producing very large data sets. The exploding volumes of biological data are craving for extreme computational power and special computing facilities (i.e. super-computers. An inexpensive solution, such as General Purpose computation based on Graphics Processing Units (GPGPU, can be adapted to tackle this challenge, but the limitation of the device internal memory can pose a new problem of scalability. An efficient data and computational parallelism with partitioning is required to provide a fast and scalable solution to this problem. RESULTS: We propose an efficient parallel formulation of the k-Nearest Neighbour (kNN search problem, which is a popular method for classifying objects in several fields of research, such as pattern recognition, machine learning and bioinformatics. Being very simple and straightforward, the performance of the kNN search degrades dramatically for large data sets, since the task is computationally intensive. The proposed approach is not only fast but also scalable to large-scale instances. Based on our approach, we implemented a software tool GPU-FS-kNN (GPU-based Fast and Scalable k-Nearest Neighbour for CUDA enabled GPUs. The basic approach is simple and adaptable to other available GPU architectures. We observed speed-ups of 50-60 times compared with CPU implementation on a well-known breast microarray study and its associated data sets. CONCLUSION: Our GPU-based Fast and Scalable k-Nearest Neighbour search technique (GPU-FS-kNN provides a significant performance improvement for nearest neighbour computation in large-scale networks. Source code and the software tool is available under GNU Public License (GPL at https://sourceforge.net/p/gpufsknn/.
Accelerating k-NN Algorithm with Hybrid MPI and OpenSHMEM
Energy Technology Data Exchange (ETDEWEB)
Lin, Jian; Hamidouche, Khaled; Zheng, Jie; Lu, Xiaoyi; Vishnu, Abhinav; Panda, Dhabaleswar
2015-08-05
Machine Learning algorithms are benefiting from the continuous improvement of programming models, including MPI, MapReduce and PGAS. k-Nearest Neighbors (k-NN) algorithm is a widely used machine learning algorithm, applied to supervised learning tasks such as classification. Several parallel implementations of k-NN have been proposed in the literature and practice. However, on high-performance computing systems with high-speed interconnects, it is important to further accelerate existing designs of the k-NN algorithm through taking advantage of scalable programming models. To improve the performance of k-NN on large-scale environment with InfiniBand network, this paper proposes several alternative hybrid MPI+OpenSHMEM designs and performs a systemic evaluation and analysis on typical workloads. The hybrid designs leverage the one-sided memory access to better overlap communication with computation than the existing pure MPI design, and propose better schemes for efficient buffer management. The implementation based on k-NN program from MaTEx with MVAPICH2-X (Unified MPI+PGAS Communication Runtime over InfiniBand) shows up to 9.0% time reduction for training KDD Cup 2010 workload over 512 cores, and 27.6% time reduction for small workload with balanced communication and computation. Experiments of running with varied number of cores show that our design can maintain good scalability.
Indexing the bit-code and distance for fast KNN search in high-dimensional spaces
Institute of Scientific and Technical Information of China (English)
LIANG Jun-jie; FENG Yu-cai
2007-01-01
Various index structures have recently been proposed to facilitate high-dimensional KNN queries, among which the techniques of approximate vector presentation and one-dimensional (iD) transformation can break the curse of dimensionality.Based on the two techniques above, a novel high-dimensional index is proposed, called Bit-code and Distance based index (BD).BD is based on a special partitioning strategy which is optimized for high-dimensional data. By the definitions of bit code and transformation function, a high-dimensional vector can be first approximately represented and then transformed into a 1D vector,the key managed by a B+-tree. A new KNN search algorithm is also proposed that exploits the bit code and distance to prune the search space more effectively. Results of extensive experiments using both synthetic and real data demonstrated that BD outperforms the existing index structures for KNN search in high-dimensional spaces.
Photometric redshift estimation for quasars by integration of KNN and SVM
Han, Bo; Ding, Hong-Peng; Zhang, Yan-Xia; Zhao, Yong-Heng
2016-05-01
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts. However, catastrophic failure is an unsolved problem with a long history and it still exists in the current photometric redshift estimation approaches (such as the k-nearest neighbor (KNN) algorithm). In this paper, we propose a novel two-stage approach by integration of KNN and support vector machine (SVM) methods together. In the first stage, we apply the KNN algorithm to photometric data and estimate their corresponding z phot. Our analysis has found two dense regions with catastrophic failure, one in the range of z phot ɛ [0.3, 1.2] and the other in the range of zphot ɛ [1.2, 2.1]. In the second stage, we map the photometric input pattern of points falling into the two ranges from their original attribute space into a high dimensional feature space by using a Gaussian kernel function from an SVM. In the high dimensional feature space, many outliers resulting from catastrophic failure by simple Euclidean distance computation in KNN can be identified by a classification hyperplane of SVM and can be further corrected. Experimental results based on the Sloan Digital Sky Survey (SDSS) quasar data show that the two-stage fusion approach can significantly mitigate catastrophic failure and improve the estimation accuracy of photometric redshifts of quasars. The percents in different |δz| ranges and root mean square (rms) error by the integrated method are 83.47%, 89.83%, 90.90% and 0.192, respectively, compared to the results by KNN (71.96%, 83.78%, 89.73% and 0.204).
基于相似度衡量的决策树自适应迁移%Self-adaptive Transfer for Decision Trees Based on Similarity Metric
Institute of Scientific and Technical Information of China (English)
王雪松; 潘杰; 程玉虎; 曹戈
2013-01-01
如何解决迁移学习中的负迁移问题并合理把握迁移的时机与方法,是影响迁移学习广泛应用的关键点.针对这个问题,提出一种基于相似度衡量机制的决策树自适应迁移方法(Self-adaptive transfer for decision trees based on a similarity metric,STDT).首先,根据源任务数据集是否允许访问,自适应地采用成分预测概率或路径预测概率对决策树间的相似性进行判定,其亲和系数作为量化衡量关联任务相似程度的依据.然后,根据多源判定条件确定是否采用多源集成迁移,并将相似度归一化后依次分配给待迁移源决策树作为迁移权值.最后,对源决策树进行集成迁移以辅助目标任务实现决策.基于UCI机器学习库的仿真结果说明,与多源迁移加权求和算法(Weighted sum rule,WSR)和MS-TrAdaBoost相比,STDT能够在保证决策精度的前提下实现更为快速的迁移.
Schiaffino, L.; Rosado Muñoz, A.; Guerrero Martínez, J.; Francés Villora, J.; Gutiérrez, A.; Martínez Torres, I.; Kohan, y. D. R.
2016-04-01
Deep Brain Stimulation (DBS) applies electric pulses into the subthalamic nucleus (STN) improving tremor and other symptoms associated to Parkinson’s disease. Accurate STN detection for proper location and implant of the stimulating electrodes is a complex task and surgeons are not always certain about final location. Signals from the STN acquired during DBS surgery are obtained with microelectrodes, having specific characteristics differing from other brain areas. Using supervised learning, a trained model based on previous microelectrode recordings (MER) can be obtained, being able to successfully classify the STN area for new MER signals. The K Nearest Neighbours (K-NN) algorithm has been successfully applied to STN detection. However, the use of the fuzzy form of the K-NN algorithm (KNN-F) has not been reported. This work compares the STN detection algorithm of K-NN and KNN-F. Real MER recordings from eight patients where previously classified by neurophysiologists, defining 15 features. Sensitivity and specificity for the classifiers are obtained, Wilcoxon signed rank non-parametric test is used as statistical hypothesis validation. We conclude that the performance of KNN-F classifier is higher than K-NN with p<0.01 in STN specificity.
Energy Technology Data Exchange (ETDEWEB)
Nawrocki, J; Chino, J; Light, K; Vergalasova, I; Craciunescu, O [Duke University Medical Center, Durham, NC (United States)
2014-06-01
Purpose: To compare PET extracted metrics and investigate the role of a gradient-based PET segmentation tool, PET Edge (MIM Software Inc., Cleveland, OH), in the context of an adaptive PET protocol for node positive gynecologic cancer patients. Methods: An IRB approved protocol enrolled women with gynecological, PET visible malignancies. A PET-CT was obtained for treatment planning prescribed to 45–50.4Gy with a 55– 70Gy boost to the PET positive nodes. An intra-treatment PET-CT was obtained between 30–36Gy, and all volumes re-contoured. Standard uptake values (SUVmax, SUVmean, SUVmedian) and GTV volumes were extracted from the clinician contoured GTVs on the pre- and intra-treament PET-CT for primaries and nodes and compared with a two tailed Wilcoxon signed-rank test. The differences between primary and node GTV volumes contoured in the treatment planning system and those volumes generated using PET Edge were also investigated. Bland-Altman plots were used to describe significant differences between the two contouring methods. Results: Thirteen women were enrolled in this study. The median baseline/intra-treatment primary (SUVmax, mean, median) were (30.5, 9.09, 7.83)/( 16.6, 4.35, 3.74), and nodes were (20.1, 4.64, 3.93)/( 6.78, 3.13, 3.26). The p values were all < 0.001. The clinical contours were all larger than the PET Edge generated ones, with mean difference of +20.6 ml for primary, and +23.5 ml for nodes. The Bland-Altman revealed changes between clinician/PET Edge contours to be mostly within the margins of the coefficient of variability. However, there was a proportional trend, i.e. the larger the GTV, the larger the clinical contours as compared to PET Edge contours. Conclusion: Primary and node SUV values taken from the intratreament PET-CT can be used to assess the disease response and to design an adaptive plan. The PET Edge tool can streamline the contouring process and lead to smaller, less user-dependent contours.
Quevedo, Hernando
2016-01-01
We review the problem of describing the gravitational field of compact stars in general relativity. We focus on the deviations from spherical symmetry which are expected to be due to rotation and to the natural deformations of mass distributions. We assume that the relativistic quadrupole moment takes into account these deviations, and consider the class of axisymmetric static and stationary quadrupolar metrics which satisfy Einstein's equations in empty space and in the presence of matter represented by a perfect fluid. We formulate the physical conditions that must be satisfied for a particular spacetime metric to describe the gravitational field of compact stars. We present a brief review of the main static and axisymmetric exact solutions of Einstein's vacuum equations, satisfying all the physical conditions. We discuss how to derive particular stationary and axisymmetric solutions with quadrupolar properties by using the solution generating techniques which correspond either to Lie symmetries and B\\"acku...
Pijpers, F P
2006-01-01
Scientific output varies between research fields and between disciplines within a field such as astrophysics. Even in fields where publication is the primary output, there is considerable variation in publication and hence in citation rates. Data from the Smithsonian/NASA Astrophysics Data System is used to illustrate this problem and argue against a "one size fits all" approach to performance metrics, especially over the short time-span covered by the Research Assessment Exercise (soon underway in the UK).
International Nuclear Information System (INIS)
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
Klauder, John R.
1998-01-01
Canonical quantization may be approached from several different starting points. The usual approaches involve promotion of c-numbers to q-numbers, or path integral constructs, each of which generally succeeds only in Cartesian coordinates. All quantization schemes that lead to Hilbert space vectors and Weyl operators---even those that eschew Cartesian coordinates---implicitly contain a metric on a flat phase space. This feature is demonstrated by studying the classical and quantum ``aggregati...
Siparov, S V
2015-01-01
The suggested approach makes it possible to produce a consistent description of motions of a physical system. It is shown that the concept of force fields defining the systems dynamics is equivalent to the choice of the corresponding metric of an anisotropic space, which is used for the modeling of physical reality and the processes that take place. The examples from hydrodynamics, electrodynamics, quantum mechanics and theory of gravitation are discussed. This approach makes it possible to get rid of some known paradoxes. It can be also used for the further development of the theory.
Directory of Open Access Journals (Sweden)
Akmal Mat Harttat Maziati
2015-06-01
Full Text Available Alkaline niobate mainly potassium sodium niobate, (KxNa1-x NbO3 (abreviated as KNN has long attracted attention as piezoelectric materials as its high Curie temperature (Tc and piezoelectric properties. The volatility of alkaline element (K, Na is, however detrimental to the stoichiometry of KNN, contributing to the failure to achieve high-density structure and lead to the formation of intrinsic defects. By partially doping of several rare-earth elements, the inherent defects could be improved significantly. Therefore, considerable attempts have been made to develop doped-KNN based ceramic materials with high electrical properties. In this paper, these research activities are reviewed, including dopants type and doping role in KNN perovskite structure.
KNN/BNT composite lead-free films for high-frequency ultrasonic transducer applications.
Lau, Sien Ting; Ji, Hong Fen; Li, Xiang; Ren, Wei; Zhou, Qifa; Shung, K Kirk
2011-01-01
Lead-free K(0.5)Na(0.5)NbO(3)/Bi(0.5)Na(0.5)TiO(3) (KNN/ BNT) films have been fabricated by a composite sol-gel technique. Crystalline KNN fine powder was dispersed in the BNT precursor solution to form a composite slurry which was then spin-coated onto a platinum-buffered Si substrate. Repeated layering and vacuum infiltration were applied to produce 5-μm-thick dense composite film. By optimizing the sintering temperature, the films exhibited good dielectric and ferroelectric properties comparable to PZT films. A 193-MHz high-frequency ultrasonic transducer fabricated from this composite film showed a -6-dB bandwidth of approximately 34%. A tungsten wire phantom was imaged to demonstrate the capability of the transducer. PMID:21244994
Processing and characterizations of BNT-KNN ceramics for actuator applications
Directory of Open Access Journals (Sweden)
Mallam Chandrasekhar
2016-06-01
Full Text Available BNT-KNN powder (with composition 0.93Bi0.5Na0.5TiO3–0.07K0.5Na0.5NbO3 was synthesized as a single perovskite phase by conventional solid state reaction route and dense ceramics were obtained by sintering of powder compacts at 1100 °C for 4 h. Dielectric study confirmed relaxor behaviour, whereas the microstructure study showed sharp cornered cubic like grains with an average grain size ∼1.15 µm. The saturated polarization vs. electric field (P-E hysteresis loops confirmed the ferroelectric (FE nature while the butterfly shaped strain vs. electric field (S-E loops suggested the piezoelectric nature of the BNT-KNN ceramic samples. Maximum electric field induced strain of ∼0.62% suggested the usefulness of this system for actuator applications.
Blog Classification: Adding Linguistic Knowledge to Improve the K-NN Algorithm
Bayoudh, Ines; Bechet, Nicolas; Roche, Mathieu
Blogs are interactive and regularly updated websites which can be seen as diaries. These websites are composed by articles based on distinct topics. Thus, it is necessary to develop Information Retrieval approaches for this new web knowledge. The first important step of this process is the categorization of the articles. The paper above compares several methods using linguistic knowledge with k-NN algorithm for automatic categorization of weblogs articles.
A multiple-point spatially weighted k-NN method for object-based classification
Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.
2016-10-01
Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.
Lead-free piezoelectric KNN-BZ-BNT films with a vertical morphotropic phase boundary
Directory of Open Access Journals (Sweden)
Wen Chen
2015-07-01
Full Text Available The lead-free piezoelectric 0.915K0.5Na0.5NbO3-0.075BaZrO3-0.01Bi0.5Na0.5TiO3 (0.915KNN-0.075BZ-0.01BNT films were prepared by a chemical solution deposition method. The films possess a pure rhomobohedral perovskite phase and a dense surface without crack. The temperature-dependent dielectric properties of the specimens manifest that only phase transition from ferroelectric to paraelectric phase occurred and the Curie temperature is 217 oC. The temperature stability of ferroelectric phase was also supported by the stable piezoelectric properties of the films. These results suggest that the slope of the morphotropic phase boundary (MPB for the solid solution formed with the KNN and BZ in the films should be vertical. The voltage-induced polarization switching, and a distinct piezo-response suggested that the 0.915 KNN-0.075BZ-0.01BNT films show good piezoelectric properties.
Improving Estimation Accuracy of Quasars’ Photometric Redshifts by Integration of KNN and SVM
Han, Bo; Ding, Hongpeng; Zhang, Yanxia; Zhao, Yongheng
2015-08-01
The massive photometric data collected from multiple large-scale sky surveys offers significant opportunities for measuring distances of many celestial objects by photometric redshifts zphot in a wide coverage of the sky. However, catastrophic failure, an unsolved problem for a long time, exists in the current photometric redshift estimation approaches (such as k-nearest-neighbor). In this paper, we propose a novel two-stage approach by integration of k-nearest-neighbor (KNN) and support vector machine (SVM) methods together. In the first stage, we apply KNN algorithm on photometric data and estimate their corresponding zphot. By analysis, we observe two dense regions with catastrophic failure, one in the range of zphot [0.1,1.1], the other in the range of zphot [1.5,2.5]. In the second stage, we map the photometric multiband input pattern of points falling into the two ranges from original attribute space into high dimensional feature space by Gaussian kernel function in SVM. In the high dimensional feature space, many bad estimation points resulted from catastrophic failure by using simple Euclidean distance computation in KNN can be identified by classification hyperplane SVM and further be applied correction. Experimental results based on SDSS data for quasars showed that the two-stage fusion approach can significantly mitigate catastrophic failure and improve the estimation accuracy of photometric redshift.
Sharp metric obstructions for quasi-Einstein metrics
Case, Jeffrey S
2011-01-01
Using the tractor calculus to study conformally warped manifolds, 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 curvature tractor, itself the tractor analogue of the curvature of the Fefferman-Graham ambient metric. We then use these obstructions to produce a tensorial invariant which is polynomial in the Riemann curvature and its divergence, and which gives the desired obstruction. In particular, this leads to a generalization to arbitrary dimensions of an algorithm due to Bartnik and Tod for finding static metrics. We also explore the consequences of this work for gradient Ricci solitons, finding an obstruction to their existence on suitably generic manifolds, and observing an interesting similarity between the nonnegativity of the curvature tractor and Hamilton's matrix Harnack inequality.
QRS detection using K-Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases
Indu Saini; Dilbag Singh; Arun Khosla
2013-01-01
The performance of computer aided ECG analysis depends on the precise and accurate delineation of QRS-complexes. This paper presents an application of K-Nearest Neighbor (KNN) algorithm as a classifier for detection of QRS-complex in ECG. The proposed algorithm is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhythmia database. In this work, a digital band-pass filter is used to reduce false detection caused by interference present in ECG signal and further ...
Directory of Open Access Journals (Sweden)
Akbar Tayebi
2010-01-01
Full Text Available In this paper, we study a class of Finsler metrics which contains the class of Berwald metrics as a special case. We prove that every Finsler metric in this class is a generalized Douglas-Weyl metric. Then we study isotropic flag curvature Finsler metrics in this class. Finally we show that on this class of Finsler metrics, the notion of Landsberg and weakly Landsberg curvature are equivalent.
COMBINING DECISION TREES AND K-NN FOR CASE-BASED PLANNING
Directory of Open Access Journals (Sweden)
Sofia Benbelkacem
2014-11-01
Full Text Available In everyday life, we are often faced with similar problems which we resolve with our experience. Case-based reasoning is a paradigm of problem solving based on past experience. Thus, case-based reasoning is considered as a valuable technique for the implementation of various tasks involving solving planning problem. Planning is considered as a decision support process designed to provide resources and required services to achieve specific objectives, allowing the selection of a better solution among several alternatives. However, we propose to exploit decision trees and k-NN combination to choose the most appropriate solutions. In a previous work [1], we have proposed a new planning approach guided by case-based reasoning and decision tree, called DTR, for case retrieval. In this paper, we use a classifier combination for similarity calculation in order to select the best solution to the target case. Thus, the use of the decision trees and k-NN combination allows improving the relevance of results and finding the most relevant cases.
Photometric Redshift Estimation for Quasars by Integration of KNN and SVM
Han, Bo; Zhang, Yanxia; Zhao, Yongheng
2016-01-01
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts. However, catastrophic failure is still an unsolved problem for a long time and exists in the current photometric redshift estimation approaches (such as $k$-nearest-neighbor). In this paper, we propose a novel two-stage approach by integration of $k$-nearest-neighbor (KNN) and support vector machine (SVM) methods together. In the first stage, we apply KNN algorithm on photometric data and estimate their corresponding z$_{\\rm phot}$. By analysis, we find two dense regions with catastrophic failure, one in the range of z$_{\\rm phot}\\in[0.3,1.2]$, the other in the range of z$_{\\rm phot}\\in [1.2,2.1]$. In the second stage, we map the photometric input pattern of points falling into the two ranges from original attribute space into a high dimensional feature space by Gaussian kernel function in SVM. In the high dimensional feature space,...
Complexity Metrics for Spreadsheet Models
Bregar, Andrej
2008-01-01
Several complexity metrics are described which are related to logic structure, data structure and size of spreadsheet models. They primarily concentrate on the dispersion of cell references and cell paths. Most metrics are newly defined, while some are adapted from traditional software engineering. Their purpose is the identification of cells which are liable to errors. In addition, they can be used to estimate the values of dependent process metrics, such as the development duration and effort, and especially to adjust the cell error rate in accordance with the contents of each individual cell, in order to accurately asses the reliability of a model. Finally, two conceptual constructs - the reference branching condition cell and the condition block - are discussed, aiming at improving the reliability, modifiability, auditability and comprehensibility of logical tests.
Evaluation of normalization methods for cDNA microarray data by k-NN classification
Energy Technology Data Exchange (ETDEWEB)
Wu, Wei; Xing, Eric P; Myers, Connie; Mian, Saira; Bissell, Mina J
2004-12-17
Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double
Evaluation of normalization methods for cDNA microarray data by k-NN classification
Directory of Open Access Journals (Sweden)
Myers Connie
2005-07-01
Full Text Available Abstract Background Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Results Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN, was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect or intensity-dependent dye bias (referred later as intensity effect moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Conclusion Using LOOCV error of k-NNs as the
Tang, Y.; Jing, L.; Li, H.; Liu, Q.; Ding, H.
2016-04-01
In this paper, the potential of multiple-point statistics (MPS) for object-based classification is explored using a modified k-nearest neighbour (k-NN) classification method (MPk-NN). The method first utilises a training image derived from a classified map to characterise the spatial correlation between multiple points of land cover classes, overcoming the limitations of two-point geostatistical methods, and then the spatial information in the form of multiple-point probability is incorporated into the k-NN classifier. The remotely sensed image of an IKONOS subscene of the Beijing urban area was selected to evaluate the method. The image was object-based classified using the MPk-NN method and several alternatives, including the traditional k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the MPk-NN approach can achieve greater classification accuracy relative to the alternatives, which are 82.05% and 89.12% based on pixel and object testing data, respectively. Thus, the proposed method is appropriate for object-based classification.
Random Forests for Metric Learning with Implicit Pairwise Position Dependence
Xiong, Caiming; Xu, Ran; Corso, Jason J
2012-01-01
Metric learning makes it plausible to learn distances for complex distributions of data from labeled data. However, to date, most metric learning methods are based on a single Mahalanobis metric, which cannot handle heterogeneous data well. Those that learn multiple metrics throughout the space have demonstrated superior accuracy, but at the cost of computational efficiency. Here, we take a new angle to the metric learning problem and learn a single metric that is able to implicitly adapt its distance function throughout the feature space. This metric adaptation is accomplished by using a random forest-based classifier to underpin the distance function and incorporate both absolute pairwise position and standard relative position into the representation. We have implemented and tested our method against state of the art global and multi-metric methods on a variety of data sets. Overall, the proposed method outperforms both types of methods in terms of accuracy (consistently ranked first) and is an order of ma...
A ROBUST GA/KNN BASED HYPOTHESIS VERIFICATION SYSTEM FOR VEHICLE DETECTION
Directory of Open Access Journals (Sweden)
Nima Khairdoost
2015-03-01
Full Text Available Vehicle detection is an important issue in driver assistance systems and self-guided vehicles that includes two stages of hypothesis generation and verification. In the first stage, potential vehicles are hypothesized and in the second stage, all hypothesis are verified. The focus of this work is on the second stage. We extract Pyramid Histograms of Oriented Gradients (PHOG features from a traffic image as candidates of feature vectors to detect vehicles. Principle Component Analysis (PCA and Linear Discriminant Analysis (LDA are applied to these PHOG feature vectors as dimension reduction and feature selection tools parallelly. After feature fusion, we use Genetic Algorithm (GA and cosine similarity-based K Nearest Neighbor (KNN classification to improve the performance and generalization of the features. Our tests show good classification accuracy of more than 97% correct classification on realistic on-road vehicle images.
Estimation of the activation energy of sintering in KNN ceramics using master sintering theory
Singh, Rajan; Patro, P. K.; Kulkarni, Ajit R.; Harendranath, C. S.
2014-04-01
The master sintering curve (MSC) of K0.5Na0.5NbO3 (KNN) ceramics was constructed using constant heating rate dilatometry data based on the combined stage sintering model. The linear shrinkage was recorded using three heating rates 5 °C, 7 °C and 11 °C/ min. The obtained results suggest that in MSC, the sintered density is a unique function of the integral of a temperature function over time and it is independent of the sintering history. The MSC theory can be applied to predict shrinkage and final density. Also, it can be used to design a reproducible process to fabricate ceramics with required density.
Zhu, Benpeng; Zhang, Zhiqiang; Ma, Teng; Yang, Xiaofei; Li, Yongxiang; Shung, K. Kirk; Zhou, Qifa
2015-04-01
Using tape-casting technology, 35 μm free-standing (100)-textured Li doped KNN (KNLN) thick film was prepared by employing NaNbO3 (NN) as template. It exhibited similar piezoelectric behavior to lead containing materials: a longitudinal piezoelectric coefficient (d33) of ˜150 pm/V and an electromechanical coupling coefficient (kt) of 0.44. Based on this thick film, a 52 MHz side-looking miniature transducer with a bandwidth of 61.5% at -6 dB was built for Intravascular ultrasound (IVUS) imaging. In comparison with 40 MHz PMN-PT single crystal transducer, the rabbit aorta image had better resolution and higher noise-to-signal ratio, indicating that lead-free (100)-textured KNLN thick film may be suitable for IVUS (>50 MHz) imaging.
The First-Principle Calculation of La-doping Effect on Piezoelectricity in Tetragonal KNN Crystal
Institute of Scientific and Technical Information of China (English)
张乔丽; 朱基亮; 袁大庆; 朱波; 王明松; 朱小红; 范平; 左翼; 郑永男; 朱升云
2012-01-01
The La-dopping effect on the piezoelectricity in the K0.5Na0.5NbO3 （KNN） crystal with a tetragonal phase is investigated for the first time using the first-principle calculation based on density functional theory. The full potentiallinearized augumented plane wave plus local orbitals （APW-LO） method and the supercell method are used in the calculation for the KNN crystal with and without the La doping. The results show that the piezoelectricity originates from the strong hybridization between the Nb atom and the O atom, and the substitution of the K or Na atom by the La impurity atom introduces the anisotropic relaxation and enhances the piezoelectricity at first and then restrains the hybridization of the Nb-O atoms when the La doping content further increases.
The high density phase of the k-NN hard core lattice gas model
Nath, Trisha; Rajesh, R.
2016-07-01
The k-NN hard core lattice gas model on a square lattice, in which the first k next nearest neighbor sites of a particle are excluded from being occupied by another particle, is the lattice version of the hard disc model in two dimensional continuum. It has been conjectured that the lattice model, like its continuum counterpart, will show multiple entropy-driven transitions with increasing density if the high density phase has columnar or striped order. Here, we determine the nature of the phase at full packing for k up to 820 302 . We show that there are only eighteen values of k, all less than k = 4134, that show columnar order, while the others show solid-like sublattice order.
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Using quality metrics with laser range scanners
MacKinnon, David K.; Aitken, Victor; Blais, Francois
2008-02-01
We have developed a series of new quality metrics that are generalizable to a variety of laser range scanning systems, including those acquiring measurements in the mid-field. Moreover, these metrics can be integrated into either an automated scanning system, or a system that guides a minimally trained operator through the scanning process. In particular, we represent the quality of measurements with regard to aliasing and sampling density for mid-field measurements, two issues that have not been well addressed in contemporary literature. We also present a quality metric that addresses the issue of laser spot motion during sample acquisition. Finally, we take into account the interaction between measurement resolution and measurement uncertainty where necessary. These metrics are presented within the context of an adaptive scanning system in which quality metrics are used to minimize the number of measurements obtained during the acquisition of a single range image.
Zhang, Xiaoling; Shen, Yi-Bing
2012-01-01
In this paper, a characteristic condition of Einstein Kropina metrics is given. By the characteristic condition, we prove that a non-Riemannian Kropina metric $F=\\frac{\\alpha^2}{\\beta}$ with constant Killing form $\\beta$ on an n-dimensional manifold $M$, $n\\geq 2$, is an Einstein metric if and only if $\\alpha$ is also an Einstein metric. By using the navigation data $(h,W)$, it is proved that an n-dimensional ($n\\geq2$) Kropina metric $F=\\frac{\\alpha^2}{\\beta}$ is Einstein if and only if the ...
Fernández, V. V.; Moya, A. M.; Rodrigues Jr., W. A.
2002-01-01
In this paper we introduce the concept of metric Clifford algebra $\\mathcal{C\\ell}(V,g)$ for a $n$-dimensional real vector space $V$ endowed with a metric extensor $g$ whose signature is $(p,q)$, with $p+q=n$. The metric Clifford product on $\\mathcal{C\\ell}(V,g)$ appears as a well-defined \\emph{deformation}(induced by $g$) of an euclidean Clifford product on $\\mathcal{C\\ell}(V)$. Associated with the metric extensor $g,$ there is a gauge metric extensor $h$ which codifies all the geometric inf...
Institute of Scientific and Technical Information of China (English)
李华兵; 杨昆
2016-01-01
针对现有差异甲基化区域 DMRs 识别方法中过度删除显著性弱的甲基化位点、DMRs 长度受限以及不能直接处理多类的问题，提出了一种利用滑动窗口和 KNN 算法识别不同类别间DMRs 的算法.算法先通过滑动窗口结合 KNN 分类器筛选候选区域，再根据误差率合并候选区域得到 DMRs.真实数据上的实验表明，算法的分类性能、聚类指数明显优于对照算法，扩展了对照的 Ong 算法识别的 DMRs 长度，并能发现 Ong 算法未发现的 DMRs.%In view of the shortcomings of the existing methods for identifying differentially methylated regions(DMRs),such as over deletion of sites that significance are weaker,region length limitation and can’t be directly processed by the multi-class.An algorithm of identifying DMRs based on sliding window and k-nearest neighbor(KNN)is proposed.In this method,candidate regions are obtained using sliding windows and KNN,and it merges candidate regions to get DMRs.Through real data simulation results demonstrate the method is superior to control method, such as classification performance,cluster index,the DMRs length of the control methods of Ong is extended and find some DMRs that can’t be found in control algorithm of Ong.
Prentice, Julia C; Frakt, Austin B; Pizer, Steven D
2016-04-01
Increasingly, performance metrics are seen as key components for accurately measuring and improving health care value. Disappointment in the ability of chosen metrics to meet these goals is exemplified in a recent Institute of Medicine report that argues for a consensus-building process to determine a simplified set of reliable metrics. Overall health care goals should be defined and then metrics to measure these goals should be considered. If appropriate data for the identified goals are not available, they should be developed. We use examples from our work in the Veterans Health Administration (VHA) on validating waiting time and mental health metrics to highlight other key issues for metric selection and implementation. First, we focus on the need for specification and predictive validation of metrics. Second, we discuss strategies to maintain the fidelity of the data used in performance metrics over time. These strategies include using appropriate incentives and data sources, using composite metrics, and ongoing monitoring. Finally, we discuss the VA's leadership in developing performance metrics through a planned upgrade in its electronic medical record system to collect more comprehensive VHA and non-VHA data, increasing the ability to comprehensively measure outcomes. PMID:26951272
Optical and Piezoelectric Study of KNN Solid Solutions Co-Doped with La-Mn and Eu-Fe
Directory of Open Access Journals (Sweden)
Jesús-Alejandro Peña-Jiménez
2016-09-01
Full Text Available The solid-state method was used to synthesize single phase potassium-sodium niobate (KNN co-doped with the La3+–Mn4+ and Eu3+–Fe3+ ion pairs. Structural determination of all studied solid solutions was accomplished by XRD and Rietveld refinement method. Electron paramagnetic resonance (EPR studies were performed to determine the oxidation state of paramagnetic centers. Optical spectroscopy measurements, excitation, emission and decay lifetime were carried out for each solid solution. The present study reveals that doping KNN with La3+–Mn4+ and Eu3+–Fe3+ at concentrations of 0.5 mol % and 1 mol %, respectively, improves the ferroelectric and piezoelectric behavior and induce the generation of optical properties in the material for potential applications.
V. Myroniuk
2015-01-01
This paper deals with modern experience of statistical inventory of forests using ground-based inventory and remote sensing data (RSD). A detailed analysis of the k-NN method of classification of satellite images is given and features of its applying for thematic mapping of forest fund under the statistical forest inventory defined. The algorithm for calculating the stock of plantings for the statistical software with R open source is shown on the example of local research material.
Mattioli W; Quatrini V; Di Paolo S; Di Santo D; Giuliarelli D; Angelini A.; Portoghesi L; Corona P
2012-01-01
Estimation and mapping of forest attributes are a fundamental support for forest management planning. This study describes a practical experimentation concerning the use of design-based k-Nearest Neighbors (k-NN) approach to estimate and map selected attributes in the framework of inventories at forest management level. The study area was the Chiarino forest within the Gran Sasso and Monti della Laga National Park (central Italy). Aboveground biomass and current annual increment of tree volum...
Directory of Open Access Journals (Sweden)
Mattioli W
2012-02-01
Full Text Available Estimation and mapping of forest attributes are a fundamental support for forest management planning. This study describes a practical experimentation concerning the use of design-based k-Nearest Neighbors (k-NN approach to estimate and map selected attributes in the framework of inventories at forest management level. The study area was the Chiarino forest within the Gran Sasso and Monti della Laga National Park (central Italy. Aboveground biomass and current annual increment of tree volume were selected as the attributes of interest for the test. Field data were acquired within 28 sample plots selected by stratified random sampling. Satellite data were acquired by a Landsat 5 TM multispectral image. Attributes from field surveys and Landsat image processing were coupled by k-NN to predict the attributes of interest for each pixel of the Landsat image. Achieved results demonstrate the effectiveness of the k-NN approach for statistical estimation, that is compatible with the produced forest attribute raster maps and also proves to be characterized, in the considered study case, by a precision double than that obtained by conventional inventory based on field sample plots only.
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...
Cuturi, Marco
2011-01-01
Transportation distances have been used for more than a decade now in machine learning to compare histograms of features. They have one parameter: the ground metric, which can be any metric between the features themselves. As is the case for all parameterized distances, transportation distances can only prove useful in practice when this parameter is carefully chosen. To date, the only option available to practitioners to set the ground metric parameter was to rely on a priori knowledge of the features, which limited considerably the scope of application of transportation distances. We propose to lift this limitation and consider instead algorithms that can learn the ground metric using only a training set of labeled histograms. We call this approach ground metric learning. We formulate the problem of learning the ground metric as the minimization of the difference of two polyhedral convex functions over a convex set of distance matrices. We follow the presentation of our algorithms with promising experimenta...
Metrics for Sustainable Manufacturing
Reich-Weiser, Corinne; Vijayaraghavan, Athulan; Dornfeld, David
2008-01-01
A sustainable manufacturing strategy requires metrics for decision making at all levels of the enterprise. In this paper, a methodology is developed for designing sustainable manufacturing metrics given the speciﬁc concerns to be addressed. A top-down approach is suggested that follows the framework of goal and scope deﬁnition: (1) goal- what are the concerns addressed and what is the appropriate metric type to achieve the goal (2) scope what is the appropriate geographic and manufacturing ex...
-Metric Space: A Generalization
Directory of Open Access Journals (Sweden)
Farshid Khojasteh
2013-01-01
Full Text Available We introduce the notion of -metric as a generalization of a metric by replacing the triangle inequality with a more generalized inequality. We investigate the topology of the spaces induced by a -metric and present some essential properties of it. Further, we give characterization of well-known fixed point theorems, such as the Banach and Caristi types in the context of such spaces.
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.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of cosmetology students, this instructional package on cosmetology is part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational terminology, measurement terms, and tools currently in use. Each of the…
Privacy Metrics and Boundaries
L-F. Pau (Louis-François)
2005-01-01
textabstractThis paper aims at defining a set of privacy metrics (quantitative and qualitative) in the case of the relation between a privacy protector ,and an information gatherer .The aims with such metrics are: -to allow to assess and compare different user scenarios and their differences; for ex
Computational visual distinctness metric
Martínez-Baena, J.; Toet, A.; Fdez-Vidal, X.R.; Garrido, A.; Rodríguez-Sánchez, R.
1998-01-01
A new computational visual distinctness metric based on principles of the early human visual system is presented. The metric is applied to quantify (1) the visual distinctness of targets in complex natural scenes and (2) the perceptual differences between compressed and uncompressed images. The new
Institute of Scientific and Technical Information of China (English)
ZHAOZhen-gang
2005-01-01
We have constructed the positive definite metric matrixes for the bounded domains of Rn and proved an inequality which is about the Jacobi matrix of a harmonic mapping on a bounded domain of Rn and the metric matrix of the same bounded domain.
Knowledge discovery in medical systems using differential diagnosis, LAMSTAR & k-NN.
Isola, Rahul; Carvalho, Rebeck; Tripathy, Amiya Kumar
2012-11-01
Medical data is an ever-growing source of information generated from the hospitals in the form of patient records. When mined properly the information hidden in these records is a huge resource bank for medical research. As of now, this data is mostly used only for clinical work. This data often contains hidden patterns and relationships, that can lead to better diagnosis, better medicines, better treatment and overall, a platform to better understand the mechanisms governing almost all aspects of the medical domain. Unfortunately, discovery of these hidden patterns and relationships often goes unexploited. However there is on-going research in medical diagnosis which can predict the diseases of the heart, lungs and various tumours based on the past data collected from the patients.They are mostly limited to domain specific systems that predict diseases restricted to their area of operation like heart, brain and various other domains. These are not applicable to the whole medical dataset. The system proposed in this paper uses this vast storage of information so that diagnosis based on this historical data can be made. It focuses on computing the probability of occurrence of a particular ailment from the medical data by mining it using a unique algorithm which increases accuracy of such diagnosis by combining the key points of Neural Networks, Large Memory Storage and Retrieval (LAMSTAR), k-NN and Differential Diagnosis all integrated into one single algorithm. The system uses a Service-Oriented Architecture wherein the system components of diagnosis, information portal and other miscellaneous services are provided.This algorithm can be used in solving a few common problems that are encountered in automated diagnosis these days, which include: diagnosis of multiple diseases showing similar symptoms, diagnosis of a person suffering from multiple diseases, receiving faster and more accurate second opinion and faster identification of trends present in the medical
Prevention of Spammers and Promoters in Video Social Networks using SVM-KNN
Directory of Open Access Journals (Sweden)
Indira K
2014-10-01
Full Text Available As online social networks acquire larger user bases, they also become more interesting targets for spammers and promoters. Spam can take very different forms on social websites, especially in the form of videos and cannot always be detected by analyzing textual content. There are online video sharing systems that allow the users to post videos s response to any type of discussion topic. This feature encourages some of the users to post polluted content illegally as responses and there may be content promoters who try to promote them in the top listed search. Content pollution like spread advertise to generate sales, disseminate pornography, and compromise system reputation may threaten the trust of users on the system, thus weaken its success in promoting social interactions. As a solution for this problem, we classify the users as spammers, content promoters and legitimate users by building a test collection of real YouTube users using which we can provide a classification we use of content, individual and social attributes that help in characterizing each user class. For effective classification we use SVMKNN which is an active learning approach. Our proposed approach poses a promising alternative to simply considering all users as legitimate or to randomly selecting users for manual inspection. In simple SVM training is very slow on whole dataset and not works very well on multiple classes. To overcome this problem and to provide efficient classification in fast manner we proposed new approach is SVM-KNN. Train a Support Vector Machine on K no of collections of nearest neighbours.
Blecher, David P
2012-01-01
The present paper is a sequel to our paper "Metric characterization of isometries and of unital operator spaces and systems". We characterize certain common objects in the theory of operator spaces (unitaries, unital operator spaces, operator systems, operator algebras, and so on), in terms which are purely linear-metric, by which we mean that they only use the vector space structure of the space and its matrix norms. In the last part we give some characterizations of operator algebras (which are not linear-metric in our strict sense described in the paper).
A note on static metrics: the degenerate case
Ferrando, Joan Josep
2013-01-01
We give the necessary and sufficient conditions for a 3-metric to be the adapted spatial metric of a static vacuum solution. This work accomplishes for the degenerate cases the already known study for the regular ones (Bartnik and Tod 2006 {\\it Class. Quantum Grav.} {\\bf 23} 569-571).
Carver, Gary P.
1994-05-01
The federal agencies are working with industry to ease adoption of the metric system. The goal is to help U.S. industry compete more successfully in the global marketplace, increase exports, and create new jobs. The strategy is to use federal procurement, financial assistance, and other business-related activities to encourage voluntary conversion. Based upon the positive experiences of firms and industries that have converted, federal agencies have concluded that metric use will yield long-term benefits that are beyond any one-time costs or inconveniences. It may be time for additional steps to move the Nation out of its dual-system comfort zone and continue to progress toward metrication. This report includes 'Metric Highlights in U.S. History'.
Dominici, Diego
2011-01-01
This work introduces a distance between natural numbers not based on their position on the real line but on their arithmetic properties. We prove some metric properties of this distance and consider a possible extension.
结合SVM和KNN的Web日志挖掘技术研究方法%Research method of Web log mining technology with combination of SVM and KNN
Institute of Scientific and Technical Information of China (English)
曾俊
2012-01-01
将SVM和KNN算法结合在一起,组成一种新的Web文本分类算法-SVM-KNN算法.当Web文本和SVM最优超平面的距离大于预选设定的阈值,则采用SVM进行分类,反之采用SVM作为代表点的KNN算法对样本分类.实证结果表明,SVM-KNN分类算法的分类精度比单纯SVM或KNN分类算法有不同程度的提高,为Web数据挖掘提供了一种有效的分类方法.%This paper used SVM and KNN algorithm together to form a new classification algorithm for Web text-SVM-KNN algorithm. When optimal super plane distance of Web text and SVM was greater than the preselected threshold, used SVM to classify, otherwise it adopted KNN algorithm to classify the samples of SVM as the representative point. The experimental results show that the accuracy of SVM-KNN classification algorithm are better than pure SVM or KNN classification algorithm, and the Web text classification provides an effective classification method.
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.
Sýkorová, Veronika
2008-01-01
The aim of the thesis is to prove measurability of the Data Quality which is a relatively subjective measure and thus is difficult to measure. In doing this various aspects of measuring the quality of data are analyzed and a Complex Data Quality Monitoring System is introduced with the aim to provide a concept for measuring/monitoring the overall Data Quality in an organization. The system is built on a metrics hierarchy decomposed into particular detailed metrics, dimensions enabling multidi...
Paul POCATILU
2007-01-01
Many software and IT projects fail in completing theirs objectives because different causes of which the management of the projects has a high weight. In order to have successfully projects, lessons learned have to be used, historical data to be collected and metrics and indicators have to be computed and used to compare them with past projects and avoid failure to happen. This paper presents some metrics that can be used for the IT project management.
Mass Customization Measurements Metrics
DEFF Research Database (Denmark)
Nielsen, Kjeld; Brunø, Thomas Ditlev; Jørgensen, Kaj Asbjørn;
2014-01-01
A recent survey has indicated that 17 % of companies have ceased mass customizing less than 1 year after initiating the effort. This paper presents measurement for a company’s mass customization performance, utilizing metrics within the three fundamental capabilities: robust process design, choice...... navigation, and solution space development. A mass customizer when assessing performance with these metrics can identify within which areas improvement would increase competitiveness the most and enable more efficient transition to mass customization....
Indian Academy of Sciences (India)
S Wiegand; S Flege; O Baake; W Ensinger
2012-10-01
Thin films of (Na0.5K0.5)NbO3 (KNN) were synthesized on Pt/Ti/SiO2/Si substrates with repeated spin-coating after fabrication of the precursor solution by a sol–gel process. The KNN precursor solution was prepared from K- and Na-acetate, Nb-pentaethoxide and 1,3-propanediol. Based on three characteristic temperatures derived from thermal analysis (TG–DTA) experiments, five heat treatment programs were developed. All programs lead to single phase perovskite KNN films with random crystal orientation, but only the programs that included a treatment after each single spin-coating step provided pore free surfaces with grains of about 100 nm size. The lowest leakage current at 150 kV cm-1 was obtained for the temperature program that included pyrolysis and calcination steps after each deposited layer.
Study on Topic Tracking Based on KNN%基于KNN的话题跟踪研究
Institute of Scientific and Technical Information of China (English)
李树平; 夏春艳; 李胜东; 亓智斌; 赵杰
2012-01-01
The key technology of topic tracking task is text classification algorithm, its difficulty is topic / reports representation mod- el. According to the definition of topic tracking, contrast to commonly used text classification algorithms and text representation meth- ods, this paper selects KNN text classification algorithm as key technology of topic tracking, uses Topic vector space model to design topic / reports representation model, combines topic detection and tracking evaluation method to achieve the topic tracking system. Experimental results prove that the system has stable topic tracking performance when key technology of topic tracking is KNN.%话题跟踪任务的关键技术是文本分类算法，难点在于话题服道表示模型。根据话题跟踪的定义，对比常用的文本分类算法和文本表示方法，选择KNN文本分类算法作为话题跟踪关键技术，利用向量空间模型设计话题/报道表示模型，结合话题检测与跟踪评测方法实现了话题跟踪系统，试验结果证明KNN作为话题跟踪关键技术，系统具有较稳定的话题跟踪性能。
Huang, Jian; Liu, Gui-xiong
2016-09-01
The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm ( k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z ' if T z ' was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.
面向轨迹数据流的KNN近似查询%KNN Approximate Query for Trajectory Data Stream
Institute of Scientific and Technical Information of China (English)
王考杰; 郑雪峰; 宋一丁; 曲阜平
2011-01-01
This paper proposes a novel approach for continuous approximate query over trajectory stream based on sliding window. Through local clustering, the sliding window is divide into various sized basic windows and sampling the data elements of a basic window using biased sampling rate, forms trajectory stream synopses. Toward such synopses, it can implement distributed K-Nearest Neighbor(KNN) queries utilizing the plane sweep algorithm of computational geometry. The extensive experiments verify the effectiveness of proposed algorithm and it has better expansibility.%提出一种基于滑动窗口的K-最近邻(KNN)近似查询算法.将滑动窗口内数据通过聚类划分成若干大小不一的基本窗口,针对每个基本窗口给定一个采样率,对窗口内数据进行偏倚采样,形成数据流摘要,并基于该摘要,采用计算几何平面扫描算法执行分布式最近邻查询.仿真实验结果表明该算法有效,且具有较好的可扩展性.
Huang, Jian; Liu, Gui-xiong
2016-04-01
The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm (k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z if T z was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.
结合FSVM和KNN的人脸表情识别%Facial Expression Recognition Based on FSVM and KNN
Institute of Scientific and Technical Information of China (English)
王小虎; 黄银珍; 张石清
2013-01-01
为了提高人脸表情的正确识别率，提出了一种组合模糊支持向量机（FSVM ）和K-近邻（KNN）的人脸表情识别的新方法。该方法通过主成分分析（PCA ）提取人脸表情特征，对于待分类的不同区域，根据区分程度自适应划分为不同区域类型；并结合FSVM和KNN算法的特点，对不同区域类型切换分类算法。实验表明，此方法既能保证分类的精确度，又能简化计算复杂度。%To improve the recognition accuracy ,a new approach for facial expression recognition based on Fuzzy Support Vector Machine (FSVM ) and K-Nearest Neighbor (KNN) is presented in this paper .At first ,the feature of the static facial expression image is extracted by the Principle Component Analysis (PCA ) ,then ,the algorithm divide the region into different types ,and combine with the characteristic of the FSVM and KNN ,switch the classification methods to the different types .The result of the experiment show that proposed algorithm can achieve good recognition accuracy ,and can simplify the computation complexity .
Dissertation: Geodesics of Random Riemannian Metrics
LaGatta, Tom
2011-01-01
We introduce Riemannian First-Passage Percolation (Riemannian FPP) as a new model of random differential geometry, by considering a random, smooth Riemannian metric on $\\mathbb R^d$. We are motivated in our study by the random geometry of first-passage percolation (FPP), a lattice model which was developed to model fluid flow through porous media. By adapting techniques from standard FPP, we prove a shape theorem for our model, which says that large balls under this metric converge to a deterministic shape under rescaling. As a consequence, we show that smooth random Riemannian metrics are geodesically complete with probability one. In differential geometry, geodesics are curves which locally minimize length. They need not do so globally: consider great circles on a sphere. For lattice models of FPP, there are many open questions related to minimizing geodesics; similarly, it is interesting from a geometric perspective when geodesics are globally minimizing. In the present study, we show that for any fixed st...
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.
Directory of Open Access Journals (Sweden)
Kyril Tintarev
2007-05-01
Full Text Available The paper studies energy functionals on quasimetric spaces, defined by quadratic measure-valued Lagrangeans. This general model of medium, known as metric fractals, includes nested fractals and sub-Riemannian manifolds. In particular, the quadratic form of the Lagrangean satisfies Sobolev inequalities with the critical exponent determined by the (quasimetric homogeneous dimension, which is also involved in the asymptotic distribution of the form's eigenvalues. This paper verifies that the axioms of the metric fractal are preserved by space products, leading thus to examples of non-differentiable media of arbitrary intrinsic dimension.
Moya, A. M.; Fernadez, V. V.; Rodrigues Jr., W. A.
2005-01-01
In this paper, the second in a series of eight we continue our development of the basic tools of the multivector and extensor calculus which are used in our formulation of the differential geometry of smooth manifolds of arbitrary topology . We introduce metric and gauge extensors, pseudo-orthogonal metric extensors, gauge bases, tetrad bases and prove the remarkable golden formula, which permit us to view any Clifford algebra Cl(V,G) as a deformation of the euclidean Clifford algebra Cl(V,G_...
Institute of Scientific and Technical Information of China (English)
MA Zhi-Hao
2008-01-01
Metric of quantum states plays an important role in quantum information theory. In this letter, we find the deep connection between quantum logic theory and quantum information theory. Using the method of quantum logic, we can get a famous inequality in quantum information theory, and we answer a question raised by S. Gudder.
Engineering performance metrics
Delozier, R.; Snyder, N.
1993-03-01
Implementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including, conceptual design, detailed design, implementation, and integration. The lessons teamed from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system accomplishing project objectives and in achieving improved customer satisfaction. To facilitate this effort, a team was chartered to assist in the development of the metrics system. This team, consisting of customers and Engineering staff members, was utilized to ensure that the needs and views of the customers were considered in the development of performance measurements. The development of a system of metrics is no different than the development of any type of system. It includes the steps of defining performance measurement requirements, measurement process conceptual design, performance measurement and reporting system detailed design, and system implementation and integration.
International Nuclear Information System (INIS)
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
Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm
Directory of Open Access Journals (Sweden)
Joon Heo
2009-06-01
Full Text Available Positioning technology to track a moving object is an important and essential component of ubiquitous computing environments and applications. An RFID-based positioning system using the k-nearest neighbor (k-NN algorithm can determine the position of a moving reader from observed reference data. In this study, the optimal detection range of an RFID-based positioning system was determined on the principle that tag spacing can be derived from the detection range. It was assumed that reference tags without signal strength information are regularly distributed in 1-, 2- and 3-dimensional spaces. The optimal detection range was determined, through analytical and numerical approaches, to be 125% of the tag-spacing distance in 1-dimensional space. Through numerical approaches, the range was 134% in 2-dimensional space, 143% in 3-dimensional space.
Directory of Open Access Journals (Sweden)
Trunev A. P.
2013-11-01
Full Text Available We investigate the hypothesis of a plurality of parallel and virtual worlds. It is assumed that sentient beings in each virtual world reach a stage of development that can create a virtual world to simulate the history of their own development. In this case, the virtual worlds are nested within each other, which put a severe restriction on the possible geometry of space-time. Discussed the draft geometry virtual worlds consistently displayed from one world to another. It is shown that in this case, the metric should be universal, depending only on the fundamental constants. There are examples of universal metrics obtained in Einstein's theory of gravitation and Yang-Mills theory
Social media evaluation metrics
Ronalds Skulme; Valerijs Praude
2015-01-01
Background. There are many methods how specialists can evaluate return of online marketing activities. Most of the methods out there are designed for versatile use. But each online marketing tool has its own unique specific metrics that should be taken into account when measuring the return of marketing activities. Authors believe that the methods that are designed to evaluate online marketing activities should also be more specific. Hence authors believe that more specific online marketing r...
Learning Sequence Neighbourhood Metrics
Bayer, Justin; van der Smagt, Patrick
2011-01-01
Recurrent neural networks (RNNs) in combination with a pooling operator and the neighbourhood components analysis (NCA) objective function are able to detect the characterizing dynamics of sequences and embed them into a fixed-length vector space of arbitrary dimensionality. Subsequently, the resulting features are meaningful and can be used for visualization or nearest neighbour classification in linear time. This kind of metric learning for sequential data enables the use of algorithms tailored towards fixed length vector spaces such as R^n.
Applications of Metric Coinduction
Kozen, Dexter; Ruozzi, Nicholas
2009-01-01
Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step showing that some property is preserved by one step of the approximation process, then automatically infer by the coinduction principle that the property holds of the limit object. This can often be used to avoid complicated analytic arguments involving limits and convergence, replacing them with simpler algebraic arg...
NPScape Metric GIS Data - Housing
National Park Service, Department of the Interior — NPScape housing metrics are calculated using outputs from the Spatially Explicit Regional Growth Model. Metric GIS datasets are produced seamlessly for the United...
Geometry of manifolds with area metric: Multi-metric backgrounds
Energy Technology Data Exchange (ETDEWEB)
Schuller, Frederic P. [Perimeter Institute for Theoretical Physics, 31 Caroline Street N, Waterloo N2L 2Y5 (Canada) and Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, A. Postal 70-543, Mexico D.F. 04510 (Mexico)]. E-mail: fschuller@perimeterinstitute.ca; Wohlfarth, Mattias N.R. [II. Institut fuer Theoretische Physik, Universitaet Hamburg, Luruper Chaussee 149, 22761 Hamburg (Germany)]. E-mail: mattias.wohlfarth@desy.de
2006-07-24
We construct the differential geometry of smooth manifolds equipped with an algebraic curvature map acting as an area measure. Area metric geometry provides a spacetime structure suitable for the discussion of gauge theories and strings, and is considerably more general than Lorentzian geometry. Our construction of geometrically relevant objects, such as an area metric compatible connection and derived tensors, makes essential use of a decomposition theorem due to Gilkey, whereby we generate the area metric from a finite collection of metrics. Employing curvature invariants for multi-metric backgrounds we devise a class of gravity theories with inherently stringy character, and discuss gauge matter actions.
Perturbation of the Kerr Metric
Frutos-Alfaro, Francisco
2014-01-01
A new Kerr-like metric with quadrupole moment is obtained by means of perturbing the Kerr spacetime. By comparison with the exterior Hartle-Thorne metric, it is showed that it could be matched to an interior solution. This metric may represent the spacetime of an astrophysical object.
Some References on Metric Information.
National Bureau of Standards (DOC), Washington, DC.
This resource work lists metric information published by the U.S. Government and the American National Standards Institute. Also organizations marketing metric materials for education are given. A short table of conversions is included as is a listing of basic metric facts for everyday living. (LS)
Sustainable chemistry metrics.
Calvo-Flores, Francisco García
2009-01-01
Green chemistry has developed mathematical parameters to describe the sustainability of chemical reactions and processes, in order to quantify their environmental impact. These parameters are related to mass and energy magnitudes, and enable analyses and numerical diagnoses of chemical reactions. The environmental impact factor (E factor), atom economy, and reaction mass efficiency have been the most influential metrics, and they are interconnected by mathematical equations. The ecodesign concept must also be considered for complex industrial syntheses, as a part of the sustainability of manufacturing processes. The aim of this Concept article is to identify the main parameters for evaluating undesirable environmental consequences. PMID:19780101
Ross, T Sean
2013-01-01
This book is geared toward engineers and laser physicists involved in the development of laser-based systems, especially laser systems for directed energy applications. It begins with a review of basic laser properties and moves to definitions and implications of the various standard beam quality metrics such as [i]M[/i][sup]2[/sup], power in the bucket, brightness, beam parameter product, and Strehl ratio. The practical aspects of beam metrology, which have not been sufficiently addressed in the literature, are amply covered here.
Institute of Scientific and Technical Information of China (English)
傅德胜; 经正俊
2015-01-01
在计算机取证领域，数据碎片的取证分析已成为获取数字证据的一种重要手段。本文针对取证中数据碎片的取证问题提出了一种新的基于内容特征的数据碎片类型识别算法，该方法首先对数据碎片进行分块主成分分析PCA 后，对 PCA 特征向量进行线性鉴别分析 LDA 获取组合特征向量，然后利用 K 最邻近 KNN 算法和序列最小优化SMO 算法组成融合分类器，运用获取的组合特征向量对数据碎片进行分类识别。实验表明，该算法与其他相关算法相比，具有较高的识别准确率和识别速率，取得了良好的识别效果。%In the computer forensics field, the forensic analysis of data fragment has become an important means to obtain digital evidence. Aiming at the problem of data fragment forensics, this paper proposes a novel algorithm of data classification identification based on the content feature. Firstly, it makes principal component analysis (PCA) of each blocks in the data fragment; secondly, it makes linear discriminant analysis (LDA) of each PCA feature vector so as to get the combinational feature vector; finally, the author identifies the type of data fragment with the combinational fea-ture vector by using the fusion classifier of k nearest neighbor (KNN) algorithm and sequential minimal optimization algorithm (SMO). Experimental results have shown that compared with the related algorithms the proposed algorithm has better identification accuracy and identification rate which achieves better identification results.
A generalization of contact metric manifolds
Kim, J H; Park, J.H.; Sekigawa, K.
2013-01-01
We give a characterization of a contact metric manifold as a special almost contact metric manifold and discuss an almost contact metric manifold which is {a} natural generalization of the contact metric manifolds introduced by Y. Tashiro.
Camanho, Xián O; Molina, Alfred
2015-01-01
We study pure Lovelock vacuum and perfect fluid equations for Kasner-type metrics. These equations correspond to a single $N$th order Lovelock term in the action in $d=2N+1,\\,2N+2$ dimensions, and they capture the relevant gravitational dynamics when aproaching the big-bang singularity within the Lovelock family of theories. Pure Lovelock gravity also bears out the general feature that vacuum in the critical odd dimension, $d=2N+1$, is kinematic; i.e. we may define an analogue Lovelock-Riemann tensor that vanishes in vacuum for $d=2N+1$, yet the Riemann curvature is non-zero. We completely classify isotropic and vacuum Kasner metrics for this class of theories in several isotropy types. The different families can be characterized by means of certain higher order 4th rank tensors. We also analyze in detail the space of vacuum solutions for five and six dimensional pure Gauss-Bonnet theory. It possesses an interesting and illuminating geometric structure and symmetries that carry over to the general case. We al...
3D Face Recognition based on Radon Transform, PCA, LDA using KNN and SVM
Directory of Open Access Journals (Sweden)
P. S. Hiremath
2014-06-01
Full Text Available Biometrics (or biometric authentication refers to the identification of humans by their characteristics or traits. Bio-metrics is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Three dimensional (3D human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to the availability of improved 3D acquisition devices and processing algorithms. Three dimensional face recognition also helps to resolve some of the issues associated with two dimensional (2D face recognition. In the previous research works, there are several methods for face recognition using range images that are limited to the data acquisition and pre-processing stage only. In the present paper, we have proposed a 3D face recognition algorithm which is based on Radon transform, Principal Component Analysis (PCA and Linear Discriminant Analysis (LDA. The Radon transform (RT is a fundamental tool to normalize 3D range data. The PCA is used to reduce the dimensionality of feature space, and the LDA is used to optimize the features, which are finally used to recognize the faces. The experimentation has been done using three publicly available databases, namely, Bhosphorus, Texas and CASIA 3D face databases. The experimental results are shown that the proposed algorithm is efficient in terms of accuracy and detection time, in comparison with other methods based on PCA only and RT+PCA. It is observed that 40 Eigen faces of PCA and 5 LDA components lead to an average recognition rate of 99.20% using SVM classifier.
Institute of Scientific and Technical Information of China (English)
张俊丽; 张帆
2007-01-01
目前,大多数搜索引擎都是用相关度或page-rank或HITS(Hyperlink-Induced Topic Search)算法对匹配的结果进行排序,然后以列表的方式呈现给用户.事实表明:其索引质量不高,对所收集的信息缺乏有效的分类处理,用户面对成千上万的搜索结果无法--查看,而真正符合需要的搜索结果常常因为排在后面而被漏检,返回的结果只有极少部分得到了用户的有效利用.文章提出运用基于K近邻的模糊C均值算法(以下简称KNN-FCM)对搜索引擎的初始结果进行自动聚类,系统再针对用户作出的适时反馈进行相应的输出调整,从而方便用户查找信息.
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.
A New Complete Class Complexity Metric
Singh, Vinay; Bhattacherjee, Vandana
2014-01-01
Software complexity metrics is essential for minimizing the cost of software maintenance. Package level and System level complexity cannot be measured without class level complexity. This research addresses the class complexity metrics. This paper studies the existing class complexity metrics and proposes a new class complexity metric CCC (Complete class complexity metric). The CCC metric is then analytically evaluated by Weyuker's property.
Quantum correlations for the metric
Wetterich, C
2016-01-01
We discuss the correlation function for the metric for homogeneous and isotropic cosmologies. The exact propagator equation determines the correlation function as the inverse of the second functional derivative of the quantum effective action, for which we take the Einstein-Hilbert approximation. This formulation relates the metric correlation function employed in quantum gravity computations to cosmological observables as the graviton power spectrum. While the graviton correlation function can be obtained equivalently as a solution of the linearized Einstein equations, this does not hold for the vector and scalar components of the metric. We project the metric fluctuations on the subspace of "physical fluctuations", which couple to a conserved energy momentum tensor. On the subspace of physical metric fluctuations the relation to physical sources becomes invertible, such that the effective action and its relation to correlation functions does not need gauge fixing. The physical metric fluctuations have a sim...
Metric adjusted skew information
DEFF Research Database (Denmark)
Hansen, Frank
2008-01-01
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......) 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...
Applications of Metric Coinduction
Kozen, Dexter
2009-01-01
Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step showing that some property is preserved by one step of the approximation process, then automatically infer by the coinduction principle that the property holds of the limit object. This can often be used to avoid complicated analytic arguments involving limits and convergence, replacing them with simpler algebraic arguments. This paper examines the application of this principle in a variety of areas, including infinite streams, Markov chains, Markov decision processes, and non-well-founded sets. These results point to the usefulness of coinduction as a general proof technique.
Feedback-based gameplay metrics
Marczak, Raphael; Schott, Gareth; Hanna, Pierre; Rouas, Jean-Luc
2013-01-01
International audience The application of gameplay metrics to empirically express a player's engagement with the game system has become more appealing to a broader range of researchers beyond the computer sciences. Within game studies, the appropriation and use of gameplay metrics not only further shifts these methods beyond formalized user testing (e.g. with the aim of product improvement) but creates a demand for a more universal approach to game metric extraction that can be applied to ...
Metric-adjusted skew information
DEFF Research Database (Denmark)
Liang, Cai; Hansen, Frank
2010-01-01
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...... 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 information is a special case...... of (unbounded) metric-adjusted skew information....
Canonical metrics on complex manifold
Institute of Scientific and Technical Information of China (English)
YAU Shing-Tung
2008-01-01
@@ Complex manifolds are topological spaces that are covered by coordinate charts where the Coordinate changes are given by holomorphic transformations. For example, Riemann surfaces are one dimensional complex manifolds. In order to understand complex manifolds, it is useful to introduce metrics that are compatible with the complex structure. In general, we should have a pair (M, ds2M) where ds2M is the metric. The metric is said to be canonical if any biholomorphisms of the complex manifolds are automatically isometries. Such metrics can naturally be used to describe invariants of the complex structures of the manifold.
Canonical metrics on complex manifold
Institute of Scientific and Technical Information of China (English)
YAU; Shing-Tung(Yau; S.-T.)
2008-01-01
Complex manifolds are topological spaces that are covered by coordinate charts where the coordinate changes are given by holomorphic transformations.For example,Riemann surfaces are one dimensional complex manifolds.In order to understand complex manifolds,it is useful to introduce metrics that are compatible with the complex structure.In general,we should have a pair(M,ds~2_M)where ds~2_M is the metric.The metric is said to be canonical if any biholomorphisms of the complex manifolds are automatically isometries.Such metrics can naturally be used to describe invariants of the complex structures of the manifold.
Metrics for IT service management
Brooks, Peter
2006-01-01
This book considers the design and implementation of metrics in service organizations using industry standard frameworks. It uses the ITIL process structure and many principles from the ITIL and ISO20000 (BS15000) as a basis. It is a general guide to the use of metrics as a mechanism to control and steer IT service organizations.A major reason for covering this topic is that many organizations have found it very difficult to use metrics properly. This book will deal with the causes of the difficulties to implementing metrics and will present workable solutions.It provides a general gui
Directory of Open Access Journals (Sweden)
M. Umemura
2016-06-01
Full Text Available We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS using K-Nearest Neighbor (KNN of feature obtained by Convolutional Neural Network (CNN. Image labeling assigns labels (e.g., road, cross-walk and road shoulder to semantic regions in an image. Since CNN is effective for various image recognition tasks, we try to use the feature of CNN (Caffenet pre-trained by ImageNet. We use 4,096-dimensional feature at fc7 layer in the Caffenet as the descriptor of a region because the feature at fc7 layer has effective information for object classification. We extract the feature by the Caffenet from regions cropped from images. Since the similarity between features reflects the similarity of contents of regions, we can select top K similar regions cropped from training samples with a test region. Since regions in training images have manually-annotated ground truth labels, we vote the labels attached to top K similar regions to the test region. The class label with the maximum vote is assigned to each pixel in the test image. In experiments, we use 36 LIDAR intensity images with ground truth labels. We divide 36 images into training (28 images and test sets (8 images. We use class average accuracy and pixel-wise accuracy as evaluation measures. Our method was able to assign the same label as human beings in 97.8% of the pixels in test LIDAR intensity images.
Umemura, Masaki; Hotta, Kazuhiro; Nonaka, Hideki; Oda, Kazuo
2016-06-01
We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS) using K-Nearest Neighbor (KNN) of feature obtained by Convolutional Neural Network (CNN). Image labeling assigns labels (e.g., road, cross-walk and road shoulder) to semantic regions in an image. Since CNN is effective for various image recognition tasks, we try to use the feature of CNN (Caffenet) pre-trained by ImageNet. We use 4,096-dimensional feature at fc7 layer in the Caffenet as the descriptor of a region because the feature at fc7 layer has effective information for object classification. We extract the feature by the Caffenet from regions cropped from images. Since the similarity between features reflects the similarity of contents of regions, we can select top K similar regions cropped from training samples with a test region. Since regions in training images have manually-annotated ground truth labels, we vote the labels attached to top K similar regions to the test region. The class label with the maximum vote is assigned to each pixel in the test image. In experiments, we use 36 LIDAR intensity images with ground truth labels. We divide 36 images into training (28 images) and test sets (8 images). We use class average accuracy and pixel-wise accuracy as evaluation measures. Our method was able to assign the same label as human beings in 97.8% of the pixels in test LIDAR intensity images.
Remarks on Vertex-Distinguishing IE-Total Coloring of Complete Bipartite Graphs K4,n and Kn,n
Institute of Scientific and Technical Information of China (English)
Xiang'en CHEN; Xiaoqing XIN; Wenyu HE
2012-01-01
Let G be a simple graph.An IE-total coloring f of G refers to a coloring of the vertices and edges of G so that no two adjacent vertices receive the same color.Let C(u) be the set of colors of vertex u and edges incident to u under f.For an IE-total coloring f of G using k colors,if C(u) ≠ C(v) for any two different vertices u and v of V(G),then f is called a k-vertex-distinguishing IE-total-coloring of G,or a k-VDIET coloring of G for short.The minimum number of colors required for a VDIET coloring of G is denoted by xievt(G),and it is called the VDIET chromatic number of G.We will give VDIET chromatic numbers for complete bipartite graph K4,n (n ≥ 4),Kn,n (5 ≤ n ≤ 21) in this article.
Directory of Open Access Journals (Sweden)
Muhammad Bilal
2016-07-01
Full Text Available Sentiment mining is a field of text mining to determine the attitude of people about a particular product, topic, politician in newsgroup posts, review sites, comments on facebook posts twitter, etc. There are many issues involved in opinion mining. One important issue is that opinions could be in different languages (English, Urdu, Arabic, etc.. To tackle each language according to its orientation is a challenging task. Most of the research work in sentiment mining has been done in English language. Currently, limited research is being carried out on sentiment classification of other languages like Arabic, Italian, Urdu and Hindi. In this paper, three classification models are used for text classification using Waikato Environment for Knowledge Analysis (WEKA. Opinions written in Roman-Urdu and English are extracted from a blog. These extracted opinions are documented in text files to prepare a training dataset containing 150 positive and 150 negative opinions, as labeled examples. Testing data set is supplied to three different models and the results in each case are analyzed. The results show that Naïve Bayesian outperformed Decision Tree and KNN in terms of more accuracy, precision, recall and F-measure.
An Improved KNN Algorithm Based on Multi-attribute Classification%基于多属性分类的KNN改进算法
Institute of Scientific and Technical Information of China (English)
张炯辉; 许尧舜
2013-01-01
To improve the classification accuracy of the conventional Euclidean KNN algorithm and the im-proved KNN algorithm based on information entropy,this paper proposes an improved KNN algorithm based on multi-attribute classification. The procedures of the new algorithm comprise:i) classify the attributes according to the percentage of their attribute values in an entire attribute of sample set into those discrete attributes suit-able for entropy-based KNN algorithm and those continuous attributes suitable for conventional Euclidean KNN similarity-based algorithm;ii) process the two types of attributes separately and then sum up the two series of results with weighing and put the sum as the distance between samples;iii) select k samples those are closest to the test sample to determine the decision attribute type of the test sample.%提出了一种基于多属性分类的KNN改进算法，可有效提高传统的欧几里德KNN算法和基于信息熵的KNN改进算法的分类准确度。首先，按照单个属性不同属性值的个数占整个属性包含样本的比例进行属性的分类，分为基于信息熵的KNN算法处理的离散属性和基于传统欧几里德KNN相似度处理的连续属性两类，然后分别对不同属性进行区别处理；其次，将两类不同处理后得到的结果按比例求和作为样本之间的距离；最后，选取与待测样本的距离最小的k个样本判断测试样本的决策属性类别。
Generalized metric spaces and mappings
Lin, Shou
2016-01-01
The idea of mutual classification of spaces and mappings is one of the main research directions of point set topology. In a systematical way, this book discusses the basic theory of generalized metric spaces by using the mapping method, and summarizes the most important research achievements, particularly those from Chinese scholars, in the theory of spaces and mappings since the 1960s. This book has three chapters, two appendices and a list of more than 400 references. The chapters are "The origin of generalized metric spaces", "Mappings on metric spaces" and "Classes of generalized metric spaces". Graduates or senior undergraduates in mathematics major can use this book as their text to study the theory of generalized metric spaces. Researchers in this field can also use this book as a valuable reference.
2008-01-01
As Global Positioning Satellite (GPS) applications become more prevalent for land- and air-based vehicles, GPS applications for space vehicles will also increase. The Applied Technology Directorate of Kennedy Space Center (KSC) has developed a lightweight, low-cost GPS Metric Tracking Unit (GMTU), the first of two steps in developing a lightweight, low-cost Space-Based Tracking and Command Subsystem (STACS) designed to meet Range Safety's link margin and latency requirements for vehicle command and telemetry data. The goals of STACS are to improve Range Safety operations and expand tracking capabilities for space vehicles. STACS will track the vehicle, receive commands, and send telemetry data through the space-based asset, which will dramatically reduce dependence on ground-based assets. The other step was the Low-Cost Tracking and Data Relay Satellite System (TDRSS) Transceiver (LCT2), developed by the Wallops Flight Facility (WFF), which allows the vehicle to communicate with a geosynchronous relay satellite. Although the GMTU and LCT2 were independently implemented and tested, the design collaboration of KSC and WFF engineers allowed GMTU and LCT2 to be integrated into one enclosure, leading to the final STACS. In operation, GMTU needs only a radio frequency (RF) input from a GPS antenna and outputs position and velocity data to the vehicle through a serial or pulse code modulation (PCM) interface. GMTU includes one commercial GPS receiver board and a custom board, the Command and Telemetry Processor (CTP) developed by KSC. The CTP design is based on a field-programmable gate array (FPGA) with embedded processors to support GPS functions.
Double Metric, Generalized Metric and $\\alpha'$-Geometry
Hohm, Olaf
2015-01-01
We relate the unconstrained `double metric' of the `$\\alpha'$-geometry' formulation of double field theory to the constrained generalized metric encoding the spacetime metric and b-field. This is achieved by integrating out auxiliary field components of the double metric in an iterative procedure that induces an infinite number of higher-derivative corrections. As an application we prove that, to first order in $\\alpha'$ and to all orders in fields, the deformed gauge transformations are Green-Schwarz-deformed diffeomorphisms. We also prove that to first order in $\\alpha'$ the spacetime action encodes precisely the Green-Schwarz deformation with Chern-Simons forms based on the torsionless gravitational connection. This seems to be in tension with suggestions in the literature that T-duality requires a torsionful connection, but we explain that these assertions are ambiguous since actions that use different connections are related by field redefinitions.
Improved Adaptive-Reinforcement Learning Control for morphing unmanned air vehicles.
Valasek, John; Doebbler, James; Tandale, Monish D; Meade, Andrew J
2008-08-01
This paper presents an improved Adaptive-Reinforcement Learning Control methodology for the problem of unmanned air vehicle morphing control. The reinforcement learning morphing control function that learns the optimal shape change policy is integrated with an adaptive dynamic inversion control trajectory tracking function. An episodic unsupervised learning simulation using the Q-learning method is developed to replace an earlier and less accurate Actor-Critic algorithm. Sequential Function Approximation, a Galerkin-based scattered data approximation scheme, replaces a K-Nearest Neighbors (KNN) method and is used to generalize the learning from previously experienced quantized states and actions to the continuous state-action space, all of which may not have been experienced before. The improved method showed smaller errors and improved learning of the optimal shape compared to the KNN. PMID:18632393
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.
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.
Conformal Patterson-Walker metrics
Hammerl, Matthias; Šilhan, Josef; Taghavi-Chabert, Arman; Žádník, Vojtěch
2016-01-01
The classical Patterson-Walker construction of a split-signature (pseudo-)Riemannian structure from a given torsion-free affine connection is generalized to a construction of a split-signature conformal structure from a given projective class of connections. A characterization of the induced structures is obtained. We achieve a complete description of Einstein metrics in the conformal class formed by the Patterson-Walker metric. Finally, we describe all symmetries of the conformal Patterson-Walker metric. In both cases we obtain descriptions in terms of geometric data on the original structure.
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)
A unifying process capability metric
Directory of Open Access Journals (Sweden)
John Jay Flaig
2009-07-01
Full Text Available A new economic approach to process capability assessment is presented, which differs from the commonly used engineering metrics. The proposed metric consists of two economic capability measures – the expected profit and the variation in profit of the process. This dual economic metric offers a number of significant advantages over other engineering or economic metrics used in process capability analysis. First, it is easy to understand and communicate. Second, it is based on a measure of total system performance. Third, it unifies the fraction nonconforming approach and the expected loss approach. Fourth, it reflects the underlying interest of management in knowing the expected financial performance of a process and its potential variation.
Rigidity of Quasi-Einstein Metrics
Case, Jeffrey; Shu, Yujen; Wei, Guofang
2008-01-01
We call a metric quasi-Einstein if the $m$-Bakry-Emery Ricci tensor is a constant multiple of the metric tensor. This is a generalization of Einstein metrics, which contains gradient Ricci solitons and is also closely related to the construction of the warped product Einstein metrics. We study properties of quasi-Einstein metrics and prove several rigidity results. We also give a splitting theorem for some K\\"ahler quasi-Einstein metrics.
Busarakam, Kanungnid; Bull, Alan T; Trujillo, Martha E; Riesco, Raul; Sangal, Vartul; van Wezel, Gilles P; Goodfellow, Michael
2016-06-01
A polyphasic study was designed to determine the taxonomic provenance of three Modestobacter strains isolated from an extreme hyper-arid Atacama Desert soil. The strains, isolates KNN 45-1a, KNN 45-2b(T) and KNN 45-3b, were shown to have chemotaxonomic and morphological properties in line with their classification in the genus Modestobacter. The isolates had identical 16S rRNA gene sequences and formed a branch in the Modestobacter gene tree that was most closely related to the type strain of Modestobacter marinus (99.6% similarity). All three isolates were distinguished readily from Modestobacter type strains by a broad range of phenotypic properties, by qualitative and quantitative differences in fatty acid profiles and by BOX fingerprint patterns. The whole genome sequence of isolate KNN 45-2b(T) showed 89.3% average nucleotide identity, 90.1% (SD: 10.97%) average amino acid identity and a digital DNA-DNA hybridization value of 42.4±3.1 against the genome sequence of M. marinus DSM 45201(T), values consistent with its assignment to a separate species. On the basis of all of these data, it is proposed that the isolates be assigned to the genus Modestobacter as Modestobacter caceresii sp. nov. with isolate KNN 45-2b(T) (CECT 9023(T)=DSM 101691(T)) as the type strain. Analysis of the whole-genome sequence of M. caceresii KNN 45-2b(T), with 4683 open reading frames and a genome size of ∽4.96Mb, revealed the presence of genes and gene-clusters that encode for properties relevant to its adaptability to harsh environmental conditions prevalent in extreme hyper arid Atacama Desert soils. PMID:27108251
Metrics Generation Process for Mechatronics
WARNIEZ, Aude; Penas, Olivia; Choley, Jean-Yves; Hehenberger, Peter
2016-01-01
International audience Due to the complexity of designing mechatronic systems, providers of these systems need to precisely evaluate their products, design processes and projects all along the design phase and beyond. We propose a metrics generation process and then define related specifications to develop an evaluation tool to build customized metrics for the mechatronic industry with respect to its specific process and expectations. The proposed process has been experimented on the modul...
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.
Stochastic Contraction in Riemannian Metrics
Pham, Quang-Cuong; Slotine, Jean-Jacques
2013-01-01
Stochastic contraction analysis is a recently developed tool for studying the global stability properties of nonlinear stochastic systems, based on a differential analysis of convergence in an appropriate metric. To date, stochastic contraction results and sharp associated performance bounds have been established only in the specialized context of state-independent metrics, which restricts their applicability. This paper extends stochastic contraction analysis to the case of general time- and...
基于KD-Tree的KNN文本分类算法%KNN Algorithm for Text Classification Based on KD-Tree
Institute of Scientific and Technical Information of China (English)
刘忠; 刘洋; 建晓
2012-01-01
This paper apply KD-Tree to KNN text classification algorithm,firstly put a training text set into a KD-Tree,then search KD-Tree for the all parents nodes of the tested text node,the set including these parents text nodes is the most nearest text set,the type of the tested text is the same as the type of the most nearest text which has the most similarity with the test text,this algorithm decreases the number of the compared texts,and the time complexity is o（log2N）.Experiments show that the improved KNN text classification algorithm is better than the traditional KNN text classification in classification efficiency.%本文将KD-Tree应用到KNN文本分类算法中,先对训练文本集建立一个KD-Tree,然后在KD-Tree中搜索测试文本的所有祖先节点文本,这些祖先节点文本集合就是待测文本的最邻近文本集合,与测试文本有最大相似度的祖先的文本类型就是待测试文本的类型,这种算法大大减少了参与比较的向量文本数目,时间复杂度仅为O（log2N）。实验表明,改进后的KNN文本分类算法具有比传统KNN文本分类法更高的分类效率。
Using principal component analysis for selecting network behavioral anomaly metrics
Gregorio-de Souza, Ian; Berk, Vincent; Barsamian, Alex
2010-04-01
This work addresses new approaches to behavioral analysis of networks and hosts for the purposes of security monitoring and anomaly detection. Most commonly used approaches simply implement anomaly detectors for one, or a few, simple metrics and those metrics can exhibit unacceptable false alarm rates. For instance, the anomaly score of network communication is defined as the reciprocal of the likelihood that a given host uses a particular protocol (or destination);this definition may result in an unrealistically high threshold for alerting to avoid being flooded by false positives. We demonstrate that selecting and adapting the metrics and thresholds, on a host-by-host or protocol-by-protocol basis can be done by established multivariate analyses such as PCA. We will show how to determine one or more metrics, for each network host, that records the highest available amount of information regarding the baseline behavior, and shows relevant deviances reliably. We describe the methodology used to pick from a large selection of available metrics, and illustrate a method for comparing the resulting classifiers. Using our approach we are able to reduce the resources required to properly identify misbehaving hosts, protocols, or networks, by dedicating system resources to only those metrics that actually matter in detecting network deviations.
Shinya Tanaka; Tomoaki Takahashi; Tomohiro Nishizono; Fumiaki Kitahara; Hideki Saito; Toshiro Iehara; Eiji Kodani; Yoshio Awaya
2014-01-01
The main objective of this study was to evaluate the effectiveness of adding feature variables, such as forest type information and topographic- and climatic-environmental factors to satellite image data, on the accuracy of stand volume estimates made with the k-nearest neighbor (k-NN) technique in southwestern Japan. Data from the Forest Resources Monitoring Survey—a national plot sampling survey in Japan—was used as in situ data in this study. The estimates obtained from three Landsat Enha...
Institute of Scientific and Technical Information of China (English)
田鑫鑫; 陈珉; 王会; 裴恩乐; 袁晓; 沈国平; 蔡锋; 徐桂林
2012-01-01
为了掌握獐(Hydropotes inermis)的警戒行为特征并为重引入项目提供管理依据,以人为干扰源观察獐的警戒反应,发现其警戒模式包括听(hear)或扫视(scan)、盯视(stare)、走开(walk away)、跑开(run away)、吼叫(bark)和压脖(stretch).利用逃跑起始距离对上海松江野化圈养(自主采食)獐、上海华夏圈养(人工饲喂)獐和江苏盐城野生獐警戒性进行比较,得出人工饲喂獐警戒性最小,野生獐警戒性最大.野化獐警戒性提高,表明可通过降低人类活动和种群密度、扩大区域面积等途径野化提高獐警戒性.%From September, 2010 to August, 2011 , we tested the vigilance pattern of the semi-captive Chinese Water Deer ( Hydropotes inermis) with human simulated predator in Songjing, Shanghai, and results suggest that Chinese water deer's vigilance pattern includes hearing and scanning, staring and walking away or running away, and sometimes they bark or stretch their necks while staring. Barking in Chinese water deer mainly functions as an anti-predator behavior against predators instead of sending signals to other deer. Stretching may function as a trial to tell the level of threats from a predator or function as a ritualized behavior which indicates the health status of the water deer. We didn't observe aggressive behavior in Chinese water deer. We used flight initiation distance ( FID) as a metric to compare the vigilance level of water deer populations of different captive status, including captive, human supplementary water deer in Huaxia, captive, free grazing water deer in Songjiang, and wild water deer in Yancheng Natural Reserve. The results suggest that the vigilance level differs significantly, which means captive water deer decrease their vigilance level compared to their wild counterparts, however human raised water deer could be trained to increased vigilance level. Experiences with human, size of space, population density and the existence of
A wavelet contrast metric for the targeting task performance metric
Preece, Bradley L.; Flug, Eric A.
2016-05-01
Target acquisition performance depends strongly on the contrast of the target. The Targeting Task Performance (TTP) metric, within the Night Vision Integrated Performance Model (NV-IPM), uses a combination of resolution, signal-to-noise ratio (SNR), and contrast to predict and model system performance. While the dependence on resolution and SNR are well defined and understood, defining a robust and versatile contrast metric for a wide variety of acquisition tasks is more difficult. In this correspondence, a wavelet contrast metric (WCM) is developed under the assumption that the human eye processes spatial differences in a manner similar to a wavelet transform. The amount of perceivable information, or useful wavelet coefficients, is used to predict the total viewable contrast to the human eye. The WCM is intended to better match the measured performance of the human vision system for high-contrast, low-contrast, and low-observable targets. After further validation, the new contrast metric can be incorporated using a modified TTP metric into the latest Army target acquisition software suite, the NV-IPM.
Method Points: towards a metric for method complexity
Directory of Open Access Journals (Sweden)
Graham McLeod
1998-11-01
Full Text Available A metric for method complexity is proposed as an aid to choosing between competing methods, as well as in validating the effects of method integration or the products of method engineering work. It is based upon a generic method representation model previously developed by the author and adaptation of concepts used in the popular Function Point metric for system size. The proposed technique is illustrated by comparing two popular I.E. deliverables with counterparts in the object oriented Unified Modeling Language (UML. The paper recommends ways to improve the practical adoption of new methods.
SYSTEMATIC REVIEW OF METRICS IN SOFTWARE AGILE PROJECTS
Directory of Open Access Journals (Sweden)
Amrita Raj Mukker
2015-11-01
Full Text Available This is a review paper in which things discussed would be about the various software metrics and about agile methodology. Nowadays Agile practices are increasing popularity in software development communities. This paper is a summary of the various metrics, agile and agile methodology used in software industries. Further this papers shows how Extreme Programming practices (XP could enhance the development and implementation of a large -scale and geographically distributed systems .Adaptation of Extreme Programming practices in the project has increased the human factor output and its has helped in bringing up promising idea to enhance the conceptualization and implementation as well as future extensions of large scale projects.
Systematic Review of Metrics in Software Agile Projects
Directory of Open Access Journals (Sweden)
Amrita Raj Mukker
2014-02-01
Full Text Available This is a review paper in which things discussed would be about the various software metrics and about agile methodology. Nowadays Agile practices are increasing popularity in software development communities. This paper is a summary of the various metrics, agile and agile methodology used in software industries. Further this papers shows how Extreme Programming practices (XP could enhance the development and imp lementation of a large -scale and geographically distributed systems .Adaptation of Extreme Programming practices in the project has increased the human factor output and its has helped in bringing up promising idea to enhance the conceptualization and implementation as well as future extensions of large scale projects.
Projectively related metrics, Weyl nullity, and metric projectively invariant equations
Gover, A Rod
2015-01-01
A metric projective structure is a manifold equipped with the unparametrised geodesics of some pseudo-Riemannian metric. We make acomprehensive treatment of such structures in the case that there is a projective Weyl curvature nullity condition. The analysis is simplified by a fundamental and canonical 2-tensor invariant that we discover. It leads to a new canonical tractor connection for these geometries which is defined on a rank $(n+1)$-bundle. We show this connection is linked to the metrisability equations that govern the existence of metrics compatible with the structure. The fundamental 2-tensor also leads to a new class of invariant linear differential operators that are canonically associated to these geometries; included is a third equation studied by Gallot et al. We apply the results to study the metrisability equation, in the nullity setting described. We obtain strong local and global results on the nature of solutions and also on the nature of the geometries admitting such solutions, obtaining ...
Energy Technology Data Exchange (ETDEWEB)
Enqvist, Kari [Physics Department, University of Helsinki, and Helsinki Institute of Physics, FIN-00014 Helsinki (Finland); Koivisto, Tomi [Institute for Theoretical Physics and Spinoza Institute, Leuvenlaan 4, 3584 CE Utrecht (Netherlands); Rigopoulos, Gerasimos, E-mail: kari.enqvist@helsinki.fi, E-mail: T.S.Koivisto@astro.uio.no, E-mail: rigopoulos@physik.rwth-aachen.de [Institut für Theoretische Teilchenphysik und Kosmologie, RWTH Aachen University, D-52056 Aachen (Germany)
2012-05-01
We consider inflation within the context of what is arguably the simplest non-metric extension of Einstein gravity. There non-metricity is described by a single graviscalar field with a non-minimal kinetic coupling to the inflaton field Ψ, parameterized by a single parameter γ. There is a simple equivalent description in terms of a massless field and an inflaton with a modified potential. We discuss the implications of non-metricity for chaotic inflation and find that it significantly alters the inflaton dynamics for field values Ψ∼>M{sub P}/γ, dramatically changing the qualitative behaviour in this regime. In the equivalent single-field description this is described as a cuspy potential that forms of barrier beyond which the inflation becomes a ghost field. This imposes an upper bound on the possible number of e-folds. For the simplest chaotic inflation models, the spectral index and the tensor-to-scalar ratio receive small corrections dependent on the non-metricity parameter. We also argue that significant post-inflationary non-metricity may be generated.
A Cuckoo Search Algorithm Based on Variable Metric Method and Adaptive Step%基于变尺度法和自适应步长的布谷鸟搜索算法
Institute of Scientific and Technical Information of China (English)
江浩; 阮奇
2015-01-01
Cuckoo Search ( CS) is a novel meta-heuristic algorithm. Aiming at the defects of weak local search ability,slow convergence velocity and low convergence accuracy,a modified CS algorithm based on DFP and adaptive step is proposed in this paper. In the im-proved cuckoo search algorithm,the step of Lévy flight nonlinear dynamic changes improve convergence velocity. After evolved from Lévy flights and elimination mechanism,the cuckoo populations rapidly access to global minima by DFP. Sixth representative benchmark functions are used to test the performance of DACS algorithm and CS algorithm respectively. The conclusions indicate that DACS algo-rithm has faster convergence speed,higher convergence accuracy and robustness,compared with CS algorithm. Meanwhile,DACS algo-rithm keeps strong global search capability,which is particularly suitable for the optimization of multimodal function and high dimension function.%布谷鸟搜索算法( Cuckoo Search,CS)是一种新型的元启发式算法。针对CS算法局部搜索能力较弱、后期收敛速度偏慢和收敛精度不高等缺点,提出一种基于变尺度法(DFP)和自适应步长(Adaptive Step)的布谷鸟搜索算法(DACS),使Lévy飞行的步长非线性自适应变化来提高算法的收敛速度,同时使经过Lévy飞行机制和淘汰机制进化后的布谷鸟种群再运用DFP快速获取全局最优解。用6种具有各种代表性的测试函数分别测试DACS算法和CS算法的性能。实验结果表明,DACS算法在保持强大的全局搜索能力的同时,比CS算法具有更快的收敛速度、更高的收敛精度和更好的鲁棒性,尤其适合多峰及高维函数的优化。
Lagrange Spaces with (γ,β-Metric
Directory of Open Access Journals (Sweden)
Suresh K. Shukla
2013-01-01
Full Text Available We study Lagrange spaces with (γ,β-metric, where γ is a cubic metric and β is a 1-form. We obtain fundamental metric tensor, its inverse, Euler-Lagrange equations, semispray coefficients, and canonical nonlinear connection for a Lagrange space endowed with a (γ,β-metric. Several other properties of such space are also discussed.
26KNN approach to denoising f rom ALS point clouds%基于26KNN的机载点云去噪方法
Institute of Scientific and Technical Information of China (English)
李峰海
2013-01-01
Data of point clouds from ALS have huge noises w hich infence the accuracy of process-ing and occupy mounts of computer memory .Therefore denoising is highly enssential before huge point cloud processing .According to the traditional KNN method ,this paper proposed an algo-rithm called 26KNN which provides a reliable preprocessing method of huge point cloud .%机载扫描系统（ALS）点云数据中含有数量巨大的噪声点，影响数据处理精度，同时也占用了大量的内存。因此在处理点云数据前必须对超大点云进行去噪。根据传统的KNN算法，结合分块读取、存贮技术，提出基于26KNN的机载点云去噪方法，成功实现了超大点云的预处理。
基于KNN的Android智能手机微信取证方法%A KNN based forensic method of Android smartphone WeChat
Institute of Scientific and Technical Information of China (English)
吴熙曦; 李炳龙; 张天琪
2014-01-01
To solve the problem that data of WeChat is so much that data related to the case can’t be found quickly,a Android smart phone WeChat forensic method based KNN algorithm was presented.Word similarity was introduced to calculate the distance of conversations.The conversations would be represented as a vector of feature words and catego-rized with KNN algorithm to quickly find the crime-related data.The experiments verify the feasibility and accuracy of the method.%针对微信数据多，无法从中快速找到与案件相关数据的问题，提出了一种基于KNN（k-nearest neighbor）算法的Android智能手机微信取证方法。引入词语相似度计算会话间的距离，将微信会话表示成特征词的向量，用KNN算法对会话进行分类，迅速找到与犯罪有关的聊天内容，并通过实验验证了该方法的可行性与准确性。
Learning Objects Reusability Effectiveness Metric (LOREM
Directory of Open Access Journals (Sweden)
Torky Ibrahim Sultan
2014-03-01
Full Text Available In this research we aim to propose an advanced metric to evaluate the effectiveness of learning objects in order to be reused in new contexts. By the way learning objects reusability is achieving economic benefits from educational technology as it saving time and improving quality, but in case of choosing unsuitable learning object it may be less benefit than creating the learning object from scratch. Actually learning objects reusability can facilitate systems development and adaptation. By surveying the current evaluation metrics, we found that while they cover essential aspects, they enables all reviewers of learning objects to evaluate all criteria without paying attention to their roles in creating the learning object which affect their capability to evaluate specific criteria. Our proposed Approach (LOREM is evaluating learning objects based on a group of Aspects which measure their level of effectiveness in order to be reused in other contexts. LOREM classifies reviewers into 3 categories; 1. Academic Group: (Subject Expert Matter “SME” and Instructor. 2. Technical Group: (Instructional Designer “ID”, LO Developer and LO Designer. 3. Students group. The authorization of reviewers in these several categories are differentiated according to reviewer's type, e.g., (Instructor, LO Developer and their area of expert (their expertise subjects for academic and students reviewers.
Eye Tracking Metrics for Workload Estimation in Flight Deck Operation
Ellis, Kyle; Schnell, Thomas
2010-01-01
Flight decks of the future are being enhanced through improved avionics that adapt to both aircraft and operator state. Eye tracking allows for non-invasive analysis of pilot eye movements, from which a set of metrics can be derived to effectively and reliably characterize workload. This research identifies eye tracking metrics that correlate to aircraft automation conditions, and identifies the correlation of pilot workload to the same automation conditions. Saccade length was used as an indirect index of pilot workload: Pilots in the fully automated condition were observed to have on average, larger saccadic movements in contrast to the guidance and manual flight conditions. The data set itself also provides a general model of human eye movement behavior and so ostensibly visual attention distribution in the cockpit for approach to land tasks with various levels of automation, by means of the same metrics used for workload algorithm development.
Robertson, Stanley L
2016-01-01
Magnetic Eternally Collapsing Objects (MECO) have been proposed as the central engines of galactic black hole candidates (GBHC) and supermassive active galactic nuclei (AGN). Previous work has shown that their luminosities and spectral and timing characteristics are in good agreement with observations. These features and the formation of jets are generated primarily by the interactions of accretion disks with an intrinsically magnetic central MECO. The interaction of accretion disks with the anchored magnetic fields of the central objects permits a unified description of properties for GBHC, AGN, neutron stars in low mass x-ray binaries and dwarf novae systems. The previously published MECO models have been based on a quasistatic Schwarzschild metric of General Relativity; however, the only essential feature of this metric is its ability to produce extreme gravitational redshifts. For reasons discussed in this article, an alternative development based on a quasistatic exponential metric is considered here.
Status report on aerospace metrication
Peterson, A.
1983-10-01
Following passage of PL 94-168, the transition to the use of metric units within the United States has been very slow. The lack of a national plan with no clear understanding or agreement concerning the source of the funds required to effect the transition have been major impediments. There are international pressures from the international standards-making organizations, the ICAO and NATO, to proceed with the unification of standards. Within the commercial aviation field, the United States is resisting the pressure, but is participating in international standardization activities because of a general recognition of the need to support future market requirements and to assist in the resolution of a significant NATO logistics problem. The AIA, with the SAE and other standards-making organizations, is attempting to secure a harmonization of United States and AECMA metric standards. The future transition progress is not expected to accelerate significantly until metric standards are available.
Rainbow metric from quantum gravity
Directory of Open Access Journals (Sweden)
Mehdi Assanioussi
2015-12-01
Full Text Available In this Letter, we describe a general mechanism for emergence of a rainbow metric from a quantum cosmological model. This idea is based on QFT on a quantum spacetime. Under general assumptions, we discover that the quantum spacetime on which the field propagates can be replaced by a classical spacetime, whose metric depends explicitly on the energy of the field: as shown by an analysis of dispersion relations, quanta of different energy propagate on different metrics, similar to photons in a refractive material (hence the name “rainbow” used in the literature. In deriving this result, we do not consider any specific theory of quantum gravity: the qualitative behaviour of high-energy particles on quantum spacetime relies only on the assumption that the quantum spacetime is described by a wave-function Ψo in a Hilbert space HG.
Moduli spaces of riemannian metrics
Tuschmann, Wilderich
2015-01-01
This book studies certain spaces of Riemannian metrics on both compact and non-compact manifolds. These spaces are defined by various sign-based curvature conditions, with special attention paid to positive scalar curvature and non-negative sectional curvature, though we also consider positive Ricci and non-positive sectional curvature. If we form the quotient of such a space of metrics under the action of the diffeomorphism group (or possibly a subgroup) we obtain a moduli space. Understanding the topology of both the original space of metrics and the corresponding moduli space form the central theme of this book. For example, what can be said about the connectedness or the various homotopy groups of such spaces? We explore the major results in the area, but provide sufficient background so that a non-expert with a grounding in Riemannian geometry can access this growing area of research.
Metrics correlation and analysis service (MCAS)
International Nuclear Information System (INIS)
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
Metrics correlation and analysis service (MCAS)
Energy Technology Data Exchange (ETDEWEB)
Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya; /Fermilab
2009-05-01
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
S-curvature of isotropic Berwald metrics
Institute of Scientific and Technical Information of China (English)
Akbar TAYEBI; Mehdi RAFIE-RAD
2008-01-01
Isotropic Berwald metrics are as a generalization of Berwald metrics. Shen proved that every Berwald metric is of vanishing S-curvature. In this paper, we generalize this fact and prove that every isotropic Berwald metric is of isotropic S-curvature. Let F = α + β be a Randers metric of isotropic Berwald curvature. Then it corresponds to a conformal vector field through navigation representation.
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.
Positive Semidefinite Metric Learning with Boosting
Shen, Chunhua; Kim, Junae; Wang, Lei; Hengel, Anton van den
2009-01-01
The learning of appropriate distance metrics is a critical problem in image classification and retrieval. In this work, we propose a boosting-based technique, termed \\BoostMetric, for learning a Mahalanobis distance metric. One of the primary difficulties in learning such a metric is to ensure that the Mahalanobis matrix remains positive semidefinite. Semidefinite programming is sometimes used to enforce this constraint, but does not scale well. \\BoostMetric is instead based on a key observat...
Performance Metrics for Haptic Interfaces
Samur, Evren
2012-01-01
Haptics technology is being used more and more in different applications, such as in computer games for increased immersion, in surgical simulators to create a realistic environment for training of surgeons, in surgical robotics due to safety issues and in mobile phones to provide feedback from user action. The existence of these applications highlights a clear need to understand performance metrics for haptic interfaces and their implications on device design, use and application. Performance Metrics for Haptic Interfaces aims at meeting this need by establishing standard practices for the ev
Thermodynamic Metrics and Optimal Paths
Energy Technology Data Exchange (ETDEWEB)
Sivak, David; Crooks, Gavin
2012-05-08
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.
Einstein metrics in projective geometry
Cap, A; Macbeth, H R
2012-01-01
It is well known that pseudo-Riemannian metrics in the projective class of a given torsion free affine connection can be obtained from (and are equivalent to) the solutions of a certain overdetermined projectively invariant differential equation. This equation is a special case of a so-called first BGG equation. The general theory of such equations singles out a subclass of so-called normal solutions. We prove that non-degerate normal solutions are equivalent to pseudo-Riemannian Einstein metrics in the projective class and observe that this connects to natural projective extensions of the Einstein condition.
Institute of Scientific and Technical Information of China (English)
徐山; 杜卫锋
2013-01-01
The overrunning of the unwanted short messages seriously impacts the social ethos and disrupts the normal life order of people .It has considerable practical value to research and develop the filtering technology of harmful short messages .In this paper, ICTCLAS segmentation system developed by the Institute of Computing Technology of CAS is applied to realise the transition of short message text to the eigenvectors in combination with keywords extraction using TFIDF word right metrics , then the kNN method is adopted to realise the discriminant of short messagescategories, thus the filtration of bad short messages is realised .In addition, according to the unbalanced distribution of training set, we apply the density-based improved method to solve the case of original classification results which are prone to the categories of big sample quite efficiently.Experiments show that the accuracy rate of the improved method reaches about 79.18%, a 1.23% increase compared with the originalmethod.This method is able to more effectively filter the unwanted short messages , and has certain practical value .%不良短信的泛滥，严重影响了社会风气，干扰了人们正常的生活秩序，研发不良短信过滤技术具有相当的实用价值。应用中科院计算所研制开发的ICTCLAS分词系统，结合TFIDF词权度量指标提取关键词，实现短信文本到特征向量的转换，然后采用kNN方法实现短信的类别判断，从而实现不良短信的过滤。另外，针对训练集分布不均衡的情况，应用基于密度的改进方法，较为有效地处理了原来分类结果倾向于大类别样本的情况。实验表明，改进后的方法的准确率约79．18％，比原方法提升了约1．23％。该方法能够比较有效地过滤不良短信，具有一定的实用价值。
Support for a Common Metric for Pediatric Pain Intensity Scales
Directory of Open Access Journals (Sweden)
Carl L von Baeyer
2000-01-01
Full Text Available Institutional adoption of routine measurement of pediatric pain has been impeded partly by the profusion of different metrics (eg, 0 to 5, 0 to 6, 0 to 10, 0 to 100 for reporting pain intensity on various instruments. The present paper discusses the importance of adopting a common metric, that is, a single numbering system on which estimates of pain intensity from various sources can be recorded. To explore both support and reservations concerning the adoption of a common metric, a survey questionnaire was sent in 1999 to an estimated 600 subscribers to the Pediatric Pain Internet Mailing List. Individuals working in pediatric institutions where children's pain is routinely measured, or where adoption of such measures is planned, were requested to respond by e-mail or mail. Responses (n=37 were from nurses (49%, physicians (24%, psychologists (7% and others/unlisted (20% on four continents. Adoption of a common metric was endorsed by 81% of respondents. Among the possible numbering systems, the 0 to 10 system was strongly favoured (70% over other options. Respondents commented that adoption of a common metric would improve communication and consistency in measurement both within and among institutions. Some disadvantages, such as staff resistance to altering existing systems, were also suggested. The majority of respondents thought that it would be desirable to adopt a common metric. Among the possible numbering systems, the 0 to 10 system is by far the most favoured. Adopting a common 0 to 10 standard, and adapting existing tools to that metric, would be positive steps toward identifying and relieving children's pain.
Socio-technical security metrics
Gollmann, D.; Herley, C.; Koenig, V.; Pieters, W.; Sasse, M.A.
2015-01-01
Report from Dagstuhl seminar 14491. This report documents the program and the outcomes of Dagstuhl Seminar 14491 “Socio-Technical Security Metrics”. In the domain of safety, metrics inform many decisions, from the height of new dikes to the design of nuclear plants. We can state, for example, that t
Danila, Bogdan; Lobo, Francisco S N; Mak, M K
2016-01-01
We consider the internal structure and the physical properties of specific classes of neutron, quark and Bose-Einstein Condensate stars in the hybrid metric-Palatini gravity theory, which is a combination of the metric and Palatini $f(R)$ formalisms. 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. We derive the equilibrium equations for a spherically symmetric configuration (mass continuity and Tolman-Oppenheimer-Volkoff) in the framework of 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. Stellar models, described by the stiff fluid, radiation-like, the bag model and the Bose-Einstein Condensate equations of state are explicitly constructed in both General Relativity and hybrid metric-Palatini...
Deser, S.
2006-01-01
We raise, and provide an (unsatisfactory) answer to, the title's question: why, unlike all other fields, does the gravitational "metric" variable not have zero vacuum? After formulating, without begging it, we exhibit additions to the conventional action that express existence of the inverse through a field equation.
Area metric gravity and accelerating cosmology
Punzi, R; Wohlfarth, M N R; Punzi, Raffaele; Schuller, Frederic P.; Wohlfarth, Mattias N.R.
2007-01-01
Area metric manifolds emerge as effective classical backgrounds in quantum string theory and quantum gauge theory, and present a true generalization of metric geometry. Here, we consider area metric manifolds in their own right, and develop in detail the foundations of area metric differential geometry. Based on the construction of an area metric curvature scalar, which reduces in the metric-induced case to the Ricci scalar, we re-interpret the Einstein-Hilbert action as dynamics for an area metric spacetime. In contrast to modifications of general relativity based on metric geometry, no continuous deformation scale needs to be introduced; the extension to area geometry is purely structural and thus rigid. We present an intriguing prediction of area metric gravity: without dark energy or fine-tuning, the late universe exhibits a small acceleration.
Ontology-based metrics computation for business process analysis
Carlos Pedrinaci; John Domingue
2009-01-01
Business Process Management (BPM) aims to support the whole life-cycle necessary to deploy and maintain business processes in organisations. Crucial within the BPM lifecycle is the analysis of deployed processes. Analysing business processes requires computing metrics that can help determining the health of business activities and thus the whole enterprise. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. In thi...
Institute of Scientific and Technical Information of China (English)
孙晓; 潘汀; 任福继
2016-01-01
深度神经网络已经被证明在图像、语音、文本领域具有挖掘数据深层潜在的分布式表达特征的能力。通过在多个面部情感数据集上训练深度卷积神经网络和深度稀疏校正神经网络两种深度学习模型,对深度神经网络在面部情感分类领域的应用作了对比评估。进而,引入了面部结构先验知识,结合感兴趣区域(Region of interest, ROI)和K最近邻算法(K-nearest neighbors, KNN),提出一种快速、简易的针对面部表情分类的深度学习训练改进方案—ROI-KNN,该训练方案降低了由于面部表情训练数据过少而导致深度神经网络模型泛化能力不佳的问题,提高了深度学习在面部表情分类中的鲁棒性,同时,显著地降低了测试错误率。%Deep neural networks have been proved to be able to mine distributed representation of data including image, speech and text. By building two models of deep convolutional neural networks and deep sparse rectifier neural networks on facial expression dataset, we make contrastive evaluations in facial expression recognition system with deep neural networks. Additionally, combining region of interest (ROI) and K-nearest neighbors (KNN), we propose a fast and simple improved method called “ROI-KNN” for facial expression classification, which relieves the poor generalization of deep neural networks due to lacking of data and decreases the testing error rate apparently and generally. The proposed method also improves the robustness of deep learning in facial expression classification.
Charged C-metric in conformal gravity
Lim, Yen-Kheng
2016-01-01
Using a C-metric-type ansatz, we obtain an exact solution to conformal gravity coupled to a Maxwell electromagnetic field. The solution resembles a C-metric spacetime carrying an electromagnetic charge. The metric is cast in a factorised form which allows us to study the domain structure of its static coordinate regions. This metric reduces to the well-known Mannheim-Kazanas metric under an appropriate limiting procedure, and also reduces to the (Anti-)de Sitter C-metric of Einstein gravity f...
Charged C-metric in conformal gravity
Lim, Yen-Kheng
2016-01-01
Using a C-metric-type ansatz, we obtain an exact solution to conformal gravity coupled to a Maxwell electromagnetic field. The solution resembles a C-metric spacetime carrying an electromagnetic charge. The metric is cast in a factorised form which allows us to study the domain structure of its static coordinate regions. This metric reduces to the well-known Mannheim-Kazanas metric under an appropriate limiting procedure, and also reduces to the (Anti-)de Sitter C-metric of Einstein gravity for a particular choice of parameters.
Charged C -metric in conformal gravity
Lim, Yen-Kheng
2016-04-01
Using a C -metric-type ansatz, we obtain an exact solution to conformal gravity coupled to a Maxwell electromagnetic field. The solution resembles a C -metric spacetime carrying an electromagnetic charge. The metric is cast in a factorized form which allows us to study the domain structure of its static coordinate regions. This metric reduces to the well-known Mannheim-Kazanas metric under an appropriate limiting procedure, and also reduces to the (anti)de Sitter C -metric of Einstein gravity for a particular choice of parameters.
Hybrid metric-Palatini gravity
Capozziello, Salvatore; Koivisto, Tomi S; Lobo, Francisco S N; Olmo, Gonzalo J
2015-01-01
Recently, the phenomenology of f(R) gravity has been scrutinized motivated by the possibility to account for the self-accelerated cosmic expansion without invoking dark energy sources. Besides, this kind of modified gravity is capable of addressing the dynamics of several self-gravitating systems alternatively to the presence of dark matter. It has been established that both metric and Palatini versions of these theories have interesting features but also manifest severe and different downsides. A hybrid combination of theories, containing elements from both these two formalisms, turns out to be also very successful accounting for the observed phenomenology and is able to avoid some drawbacks of the original approaches. This article reviews the formulation of this hybrid metric-Palatini approach and its main achievements in passing the local tests and in applications to astrophysical and cosmological scenarios, where it provides a unified approach to the problems of dark energy and dark matter.
Projective Compactifications and Einstein metrics
Cap, Andreas
2013-01-01
For complete affine manifolds we introduce a definition of compactification based on the projective differential geometry (i.e.\\ geodesic path data) of the given connection. The definition of projective compactness involves a real parameter $\\alpha$ called the order of projective compactness. For volume preserving connections, this order is captured by a notion of volume asymptotics that we define. These ideas apply to complete pseudo-Riemannian spaces, via the Levi-Civita connection, and thus provide a notion of compactification alternative to conformal compactification. For each order $\\alpha$, we provide an asymptotic form of a metric which is sufficient for projective compactness of the given order, thus also providing many local examples. Distinguished classes of projectively compactified geometries of orders one and two are associated with Ricci-flat connections and non--Ricci--flat Einstein metrics, respectively. Conversely, these geometric conditions are shown to force the indicated order of projectiv...
Quality Metrics in Inpatient Neurology.
Dhand, Amar
2015-12-01
Quality of care in the context of inpatient neurology is the standard of performance by neurologists and the hospital system as measured against ideal models of care. There are growing regulatory pressures to define health care value through concrete quantifiable metrics linked to reimbursement. Theoretical models of quality acknowledge its multimodal character with quantitative and qualitative dimensions. For example, the Donabedian model distils quality as a phenomenon of three interconnected domains, structure-process-outcome, with each domain mutually influential. The actual measurement of quality may be implicit, as in peer review in morbidity and mortality rounds, or explicit, in which criteria are prespecified and systemized before assessment. As a practical contribution, in this article a set of candidate quality indicators for inpatient neurology based on an updated review of treatment guidelines is proposed. These quality indicators may serve as an initial blueprint for explicit quality metrics long overdue for inpatient neurology.
Marketing metrics for medical practices.
Zahaluk, David; Baum, Neil
2012-01-01
There's a saying by John Wanamaker who pontificated, "Half the money I spend on advertising is wasted; the trouble is, I don't know which half". Today you have opportunities to determine which parts of your marketing efforts are effective and what is wasted. However, you have to measure your marketing results. This article will discuss marketing metrics and how to use them to get the best bang for your marketing buck. PMID:22834190
Metrics for antibody therapeutics development
Reichert, Janice M
2010-01-01
A wide variety of full-size monoclonal antibodies (mAbs) and therapeutics derived from alternative antibody formats can be produced through genetic and biological engineering techniques. These molecules are now filling the preclinical and clinical pipelines of every major pharmaceutical company and many biotechnology firms. Metrics for the development of antibody therapeutics, including averages for the number of candidates entering clinical study and development phase lengths for mAbs approv...
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.
Extremal almost-Kahler metrics
Lejmi, Mehdi
2009-01-01
We generalize the notion of the Futaki invariant and extremal vector field to the general almost-Kahler case and we prove the periodicity of the extremal vector field when the symplectic form represents an integral cohomology class modulo torsion. We give also an explicit formula of the hermitian scalar curvature which allows us to obtain examples of non-integrable extremal almost-Kahler metrics saturating LeBrun's estimates.
Marketing metrics for medical practices.
Zahaluk, David; Baum, Neil
2012-01-01
There's a saying by John Wanamaker who pontificated, "Half the money I spend on advertising is wasted; the trouble is, I don't know which half". Today you have opportunities to determine which parts of your marketing efforts are effective and what is wasted. However, you have to measure your marketing results. This article will discuss marketing metrics and how to use them to get the best bang for your marketing buck.
On Degenerate Metrics and Electromagnetism
Searight, T P
2003-01-01
A theory of degenerate metrics is developed and applied to the problem of unifying gravitation with electromagnetism. The approach is similar to the Kaluza-Klein approach with a fifth dimension, however no ad hoc conditions are needed to explain why the extra dimension is not directly observable under everyday conditions. Maxwell's theory is recovered with differences only at very small length scales, and a new formula is found for the Coulomb potential that is regular everywhere.
基于GA和KNN的SVM决策树分类方法研究%Research of SVM Decision-treen Classification Based on GA and KNN
Institute of Scientific and Technical Information of China (English)
陈东莉
2012-01-01
In this paper, a SVM decision-tree algorithm was presented based on GA and KNN. First,GA is used to create optimal or near-optimal decision-tree, which defines a novel separability measure. Then in the class phase, standard SVM is used to make binary classification for the divisible nodes, and SVM combined with KNN are used to classify the fallible nodes. Finally, the multi-classification is a-chieved by the SVM decision-tree. Experimental results show that the proposed method could effectively improve the classification precision in comparison to traditional classification methods.%文章提出了一种基于遗传算法和K近邻的SVM决策树方法,并将其应用于解决SVM多分类问题.算法以基于类分布的类间分离性测度为准则,利用遗传算法对传统的SVM决策树进行优化,生成最优(较优)决策树.在分类阶段,对容易分的节点利用SVM进行分类,而对可分离性差的节点采用SVM和K近邻相结合的分类方法,最终实现多类别分类.实验结果表明,与传统的分类方法相比,该算法的实验效果较好,是一种有效的分类方法.
The escape velocity and Schwarzschild metric
Murzagalieva, A G; Murzagaliev, G Z
2002-01-01
The escape velocity value in the terms of general relativity by means Schwarzschild metric is provided to make of the motion equation with Friedman cosmological model behavior build in the terms of Robertson-Worker metric. (author)
Security Metrics in Industrial Control Systems
Collier, Zachary A; Ganin, Alexander A; Kott, Alex; Linkov, Igor
2015-01-01
Risk is the best known and perhaps the best studied example within a much broader class of cyber security metrics. However, risk is not the only possible cyber security metric. Other metrics such as resilience can exist and could be potentially very valuable to defenders of ICS systems. Often, metrics are defined as measurable properties of a system that quantify the degree to which objectives of the system are achieved. Metrics can provide cyber defenders of an ICS with critical insights regarding the system. Metrics are generally acquired by analyzing relevant attributes of that system. In terms of cyber security metrics, ICSs tend to have unique features: in many cases, these systems are older technologies that were designed for functionality rather than security. They are also extremely diverse systems that have different requirements and objectives. Therefore, metrics for ICSs must be tailored to a diverse group of systems with many features and perform many different functions. In this chapter, we first...
Almost contact metric 3-submersions
Directory of Open Access Journals (Sweden)
Bill Watson
1984-01-01
Full Text Available An almost contact metric 3-submersion is a Riemannian submersion, π from an almost contact metric manifold (M4m+3,(φi,ξi,ηii=13,g onto an almost quaternionic manifold (N4n,(Jii=13,h which commutes with the structure tensors of type (1,1;i.e., π*φi=Jiπ*, for i=1,2,3. For various restrictions on ∇φi, (e.g., M is 3-Sasakian, we show corresponding limitations on the second fundamental form of the fibres and on the complete integrability of the horizontal distribution. Concommitantly, relations are derived between the Betti numbers of a compact total space and the base space. For instance, if M is 3-quasi-Saskian (dΦ=0, then b1(N≤b1(M. The respective φi-holomorphic sectional and bisectional curvature tensors are studied and several unexpected results are obtained. As an example, if X and Y are orthogonal horizontal vector fields on the 3-contact (a relatively weak structure total space of such a submersion, then the respective holomorphic bisectional curvatures satisfy: Bφi(X,Y=B′J′i(X*,Y*−2. Applications to the real differential geometry of Yarg-Milis field equations are indicated based on the fact that a principal SU(2-bundle over a compactified realized space-time can be given the structure of an almost contact metric 3-submersion.
Centrality Metric for Dynamic Networks
Lerman, Kristina; Kang, Jeon Hyung
2010-01-01
Centrality is an important notion in network analysis and is used to measure the degree to which network structure contributes to the importance of a node in a network. While many different centrality measures exist, most of them apply to static networks. Most networks, on the other hand, are dynamic in nature, evolving over time through the addition or deletion of nodes and edges. A popular approach to analyzing such networks represents them by a static network that aggregates all edges observed over some time period. This approach, however, under or overestimates centrality of some nodes. We address this problem by introducing a novel centrality metric for dynamic network analysis. This metric exploits an intuition that in order for one node in a dynamic network to influence another over some period of time, there must exist a path that connects the source and destination nodes through intermediaries at different times. We demonstrate on an example network that the proposed metric leads to a very different ...
Software Metrics: Calculation and Optimization of Thresholds
Abhishek Kumar Maheswari
2011-01-01
In this article, we present a algorithmic method for the calculation of thresholds (the starting point for a new state) for a software metric set. To this aim, machine learning and data mining techniques are utilized. We define a data-driven methodology that can be used for efficiency optimization of existing metric sets, for the simplification of complex classification models, and for the calculation of thresholds for a metric set in an environment where no metric set yet exists. The methodo...
Formal analysis of security metrics and risk
Krautsevich L.; Martinelli F.; Yautsiukhin A.
2011-01-01
Security metrics are usually defined informally and, therefore, the rigourous analysis of these metrics is a hard task. This analysis is required to identify the existing relations between the security metrics, which try to quantify the same quality: security. Risk, computed as Annualised Loss Expectancy, is often used in order to give the overall assessment of security as a whole. Risk and security metrics are usually defined separately and the relation between these indicators have not been...
GENERAL RELATIVITY AND METRIC OF LOCAL SUPERCLUSTER
Directory of Open Access Journals (Sweden)
Trunev A. P.
2013-12-01
Full Text Available It is shown that the metric of clusters of galaxies should be universal, depending only on the fundamental constants and compatible with the metric of the universe. There are examples of universal metrics obtained in Einstein's theory of gravitation. On the basis of axisymmetric solutions of Einstein’s equation proposed universal metric describing the properties of galaxies, groups and clusters of galaxies
A possible molecular metric for biological evolvability
Indian Academy of Sciences (India)
Aditya Mittal; B Jayaram
2012-07-01
Proteins manifest themselves as phenotypic traits, retained or lost in living systems via evolutionary pressures. Simply put, survival is essentially the ability of a living system to synthesize a functional protein that allows for a response to environmental perturbations (adaptation). Loss of functional proteins leads to extinction. Currently there are no universally applicable quantitative metrics at the molecular level for either measuring ‘evolvability’ of life or for assessing the conditions under which a living system would go extinct and why. In this work, we show emergence of the first such metric by utilizing the recently discovered stoichiometric margin of life for all known naturally occurring (and functional) proteins. The constraint of having well-defined stoichiometries of the 20 amino acids in naturally occurring protein sequences requires utilization of the full scope of degeneracy in the genetic code, i.e. usage of all codons coding for an amino acid, by only 11 of the 20 amino acids. This shows that the non-availability of individual codons for these 11 amino acids would disturb the fine stoichiometric balance resulting in non-functional proteins and hence extinction. Remarkably, these amino acids are found in close proximity of any given amino acid in the backbones of thousands of known crystal structures of folded proteins. On the other hand, stoichiometry of the remaining 9 amino acids, found to be farther/distal from any given amino acid in backbones of folded proteins, is maintained independent of the number of codons available to synthesize them, thereby providing some robustness and hence survivability.
Quasi-Einstein metrics on hypersurface families
Hall, Stuart James
2012-01-01
We construct quasi-Einstein metrics on some hypersurface families. The hypersurfaces are circle bundles over the product of Fano, K\\"ahler-Einstein manifolds. The quasi-Einstein metrics are related to various gradient K\\"ahler-Ricci solitons constructed by Dancer and Wang and some Hermitian, non-K\\"ahler, Einstein metrics constructed by Wang and Wang on the same manifolds.
Metric Education. Interpretive Report No. 1.
George Washington Univ., Washington, DC. Inst. for Educational Leadership.
This report reviews the findings of two projects funded by the National Institute of Education (NIE) ano conducted by the American Institutes for Research (AIR). The project reports, "Going Metric" and "Metric Inservice Teacher Training," document the impact of metric conversion on the educational systems of Great Britain, New Zeland, Australia,…
Context-dependent ATC complexity metric
Mercado Velasco, G.A.; Borst, C.
2015-01-01
Several studies have investigated Air Traffic Control (ATC) complexity metrics in a search for a metric that could best capture workload. These studies have shown how daunting the search for a universal workload metric (one that could be applied in different contexts: sectors, traffic patterns, cont
Load Balancing Metric with Diversity for Energy Efficient Routing in Wireless Sensor Networks
DEFF Research Database (Denmark)
Moad, Sofiane; Hansen, Morten Tranberg; Jurdak, Raja;
2011-01-01
The expected number of transmission (ETX) represents a routing metric that considers the highly variable link qualities for a specific radio in Wireless Sensor Networks (WSNs). To adapt to these differences, radio diversity is a recently explored solution for WSNs. In this paper, we propose...... an energy balancing metric which explores the diversity in link qualities present at different radios. The goal is to effectively use the energy of the network and therefore extend the network lifetime. The proposed metric takes into account the transmission and reception costs for a specific radio in order...... to choose an energy efficient radio. In addition, the metric uses the remaining energy of nodes in order to regulate the traffic so that critical nodes are avoided. We show by simulations that our metric can improve the network lifetime up to 20%....
Texture metric that predicts target detection performance
Culpepper, Joanne B.
2015-12-01
Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.
Web metrics for library and information professionals
Stuart, David
2014-01-01
This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional.Th...
Einstein metrics in projective geometry
Cap, A.; Gover, A. R.; Macbeth, H. R.
2012-01-01
It is well known that pseudo-Riemannian metrics in the projective class of a given torsion free affine connection can be obtained from (and are equivalent to) the solutions of a certain overdetermined projectively invariant differential equation. This equation is a special case of a so-called first BGG equation. The general theory of such equations singles out a subclass of so-called normal solutions. We prove that non-degerate normal solutions are equivalent to pseudo-Riemannian Einstein met...
Comparing Resource Adequacy Metrics: Preprint
Energy Technology Data Exchange (ETDEWEB)
Ibanez, E.; Milligan, M.
2014-09-01
As the penetration of variable generation (wind and solar) increases around the world, there is an accompanying growing interest and importance in accurately assessing the contribution that these resources can make toward planning reserve. This contribution, also known as the capacity credit or capacity value of the resource, is best quantified by using a probabilistic measure of overall resource adequacy. In recognizing the variable nature of these renewable resources, there has been interest in exploring the use of reliability metrics other than loss of load expectation. In this paper, we undertake some comparisons using data from the Western Electricity Coordinating Council in the western United States.
Metric scales for emotion measurement
Directory of Open Access Journals (Sweden)
Martin Junge
2016-09-01
Full Text Available The scale quality of indirect and direct scalings of the intensity of emotional experiences was investigated from the perspective of representational measurement theory. Study 1 focused on sensory pleasantness and disgust, Study 2 on surprise and amusement, and Study 3 on relief and disappointment. In each study, the emotion intensities elicited by a set of stimuli were estimated using Ordinal Difference Scaling, an indirect probabilistic scaling method based on graded pair comparisons. The obtained scale values were used to select test cases for the quadruple axiom, a central axiom of difference measurement. A parametric bootstrap test was used to decide whether the participants’ difference judgments systematically violated the axiom. Most participants passed this test. The indirect scalings of these participants were then linearly correlated with their direct emotion intensity ratings to determine whether they agreed with them up to measurement error, and hence might be metric as well. The majority of the participants did not pass this test. The findings suggest that Ordinal Difference Scaling allows to measure emotion intensity on a metric scale level for most participants. As a consequence, quantitative emotion theories become amenable to empirical test on the individual level using indirect measurements of emotional experience.
Multifractal Resilience Metrics for Complex Systems?
Schertzer, D. J.; Tchiguirinskaia, I.; Lovejoy, S.
2011-12-01
The term resilience has become extremely fashionable, especially for complex systems, whereas corresponding operational definitions have remained rather elusive (Carpenter et al. 2001). More precisely, the resilience assessment of man-made systems (from nuclear plants to cities) to geophysical extremes require mathematically defined resilience metrics based on some conceptual definition, e.g. the often cited definition of "ecological resilience" (Hollings 1973): "the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks". Surprisingly, whereas it was acknowledged by Folke et al. (2010) that "multiscale resilience is fundamental for understanding the interplay between persistence and change, adaptability and transformability", the relation between resilience and scaling has not been so much questioned, see however Peterson (2000). We argue that is rather indispensable to go well beyond the attractor approach (Pimm and Lawton 1977; Collings and Wollkind 1990;), as well as extensions (Martin et al., 2011) into the framework of the viability theory (Aubin 1991; Aubin et al. 2011). Indeed, both are rather limited to systems that are complex only in time. Scale symmetries are indeed indispensable to reduce the space-time complexity by defining scale independent observables, which are the singularities of the original, scale dependent fields. These singularities enable to define across-scale resilience, instead of resilience at a given scale.
Statistical 2D and 3D shape analysis using Non-Euclidean Metrics
DEFF Research Database (Denmark)
Larsen, Rasmus; Hilger, Klaus Baggesen; Wrobel, Mark Christoph
2002-01-01
We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition. Furtherm......We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition...
Affine and Projective Tree Metric Theorems
Harel, Matan; Pachter, Lior
2011-01-01
The tree metric theorem provides a combinatorial four point condition that characterizes dissimilarity maps derived from pairwise compatible split systems. A similar (but weaker) four point condition characterizes dissimilarity maps derived from circular split systems (Kalmanson metrics). The tree metric theorem was first discovered in the context of phylogenetics and forms the basis of many tree reconstruction algorithms, whereas Kalmanson metrics were first considered by computer scientists, and are notable in that they are a non-trivial class of metrics for which the traveling salesman problem is tractable. We present a unifying framework for these theorems based on combinatorial structures that are used for graph planarity testing. These are (projective) PC-trees, and their affine analogs, PQ-trees. In the projective case, we generalize a number of concepts from clustering theory, including hierarchies, pyramids, ultrametrics and Robinsonian matrices, and the theorems that relate them. As with tree metric...
From Smooth Curves to Universal Metrics
Gurses, Metin; Tekin, Bayram
2016-01-01
A special class of metrics, called universal metrics, solve all gravity theories defined by covariant field equations purely based on the metric tensor. Since we currently lack the knowledge of what the full of quantum corrected field equations of gravity are at a given microscopic length scale, these metrics are particularly important in understanding quantum fields in curved backgrounds in a consistent way. But, finding explicit universal metrics has been a hard problem as there does not seem to be a procedure for it. In this work, we overcome this difficulty and give a construction of universal metrics of d dimensional spacetime from curves constrained to live in a d-1 dimensional Minkowski spacetime or a Euclidean space.
From smooth curves to universal metrics
Gürses, Metin; Şişman, Tahsin ćaǧrı; Tekin, Bayram
2016-08-01
A special class of metrics, called universal metrics, solves all gravity theories defined by covariant field equations purely based on the metric tensor. Since we currently lack the knowledge of what the full quantum-corrected field equations of gravity are at a given microscopic length scale, these metrics are particularly important in understanding quantum fields in curved backgrounds in a consistent way. However, finding explicit universal metrics has been a difficult problem as there does not seem to be a procedure for it. In this work, we overcome this difficulty and give a construction of universal metrics of d -dimensional spacetime from curves constrained to live in a (d -1 )-dimensional Minkowski spacetime or a Euclidean space.
A Brief Overview Of Software Testing Metrics
Directory of Open Access Journals (Sweden)
Premal B. Nirpal,
2011-01-01
Full Text Available Metrics are gaining importance and acceptance in corporate sectors as organizations grow, mature and strive to improve enterprise qualities. Measurement of a test process is a required competence for an effective software test manager for designing and evaluating a cost effective test strategy. Effective management of any process requires quantification, measurement and modeling. Software Metrics provide quantitative approach to the development and validation of the software process models. Metrics help organization to obtain the information it needs to continue to improve its productivity, reduce errors and improve acceptance of processes, products and services and achieve the desired Goal. This paper, focusing on metrics lifecycle, various software testing metrics, need for having metrics, evaluation process and arriving at ideal conclusion have also been discussed in the present paper.
Ramified optimal transportation in geodesic metric spaces
Xia, Qinglan
2009-01-01
An optimal transport path may be viewed as a geodesic in the space of probability measures under a suitable family of metrics. This geodesic may exhibit a tree-shaped branching structure in many applications such as trees, blood vessels, draining and irrigation systems. Here, we extend the study of ramified optimal transportation between probability measures from Euclidean spaces to a geodesic metric space. We investigate the existence as well as the behavior of optimal transport paths under various properties of the metric such as completeness, doubling, or curvature upper boundedness. We also introduce the transport dimension of a probability measure on a complete geodesic metric space, and show that the transport dimension of a probability measure is bounded above by the Minkowski dimension and below by the Hausdorff dimension of the measure. Moreover, we introduce a metric, called "the dimensional distance", on the space of probability measures. This metric gives a geometric meaning to the transport dimen...
Metrics for antibody therapeutics development.
Reichert, Janice M
2010-01-01
A wide variety of full-size monoclonal antibodies (mAbs) and therapeutics derived from alternative antibody formats can be produced through genetic and biological engineering techniques. These molecules are now filling the preclinical and clinical pipelines of every major pharmaceutical company and many biotechnology firms. Metrics for the development of antibody therapeutics, including averages for the number of candidates entering clinical study and development phase lengths for mAbs approved in the United States, were derived from analysis of a dataset of over 600 therapeutic mAbs that entered clinical study sponsored, at least in part, by commercial firms. The results presented provide an overview of the field and context for the evaluation of on-going and prospective mAb development programs. The expansion of therapeutic antibody use through supplemental marketing approvals and the increase in the study of therapeutics derived from alternative antibody formats are discussed. PMID:20930555
DEFF Research Database (Denmark)
Gravesen, Jens
2015-01-01
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...... 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 colour coordinates and an optimisation approach we find new colour coordinates that make the MacAdam ellipses closer to uniform circles than the existing standards....
Metrics for antibody therapeutics development.
Reichert, Janice M
2010-01-01
A wide variety of full-size monoclonal antibodies (mAbs) and therapeutics derived from alternative antibody formats can be produced through genetic and biological engineering techniques. These molecules are now filling the preclinical and clinical pipelines of every major pharmaceutical company and many biotechnology firms. Metrics for the development of antibody therapeutics, including averages for the number of candidates entering clinical study and development phase lengths for mAbs approved in the United States, were derived from analysis of a dataset of over 600 therapeutic mAbs that entered clinical study sponsored, at least in part, by commercial firms. The results presented provide an overview of the field and context for the evaluation of on-going and prospective mAb development programs. The expansion of therapeutic antibody use through supplemental marketing approvals and the increase in the study of therapeutics derived from alternative antibody formats are discussed.
A Metric Conceptual Space Algebra
Adams, Benjamin; Raubal, Martin
The modeling of concepts from a cognitive perspective is important for designing spatial information systems that interoperate with human users. Concept representations that are built using geometric and topological conceptual space structures are well suited for semantic similarity and concept combination operations. In addition, concepts that are more closely grounded in the physical world, such as many spatial concepts, have a natural fit with the geometric structure of conceptual spaces. Despite these apparent advantages, conceptual spaces are underutilized because existing formalizations of conceptual space theory have focused on individual aspects of the theory rather than the creation of a comprehensive algebra. In this paper we present a metric conceptual space algebra that is designed to facilitate the creation of conceptual space knowledge bases and inferencing systems. Conceptual regions are represented as convex polytopes and context is built in as a fundamental element. We demonstrate the applicability of the algebra to spatial information systems with a proof-of-concept application.
The definitive guide to IT service metrics
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.
Common Metrics for Human-Robot Interaction
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.
THE QUALITY METRICS OF INFORMATION SYSTEMS
Zora Arsovski; Slavko Arsovski
2008-01-01
Information system is a special kind of products which is depend upon great number variables related to nature, conditions during implementation and organizational clime and culture. Because that quality metrics of information system (QMIS) has to reflect all previous aspects of information systems. In this paper are presented basic elements of QMIS, characteristics of implementation and operation metrics for IS, team - management quality metrics for IS and organizational aspects of quality m...
Brand Metrics: A Tool to Measure Performance
Rajagopal, MR; Rajagopal, Amritanshu
2007-01-01
An increasing interest in the continuous evaluation of brand performance has been observed in both managers and academics over recent past using metrics approach. This paper discusses the essential components of a brand metrics strategy and application of brand scorecard as an integrated approach to measure the overall performance of brands. The discussion delineates the process as how different constituents of metrics can be linked to business performance. It has also been argued in the pape...
A Note on Discrete Einstein Metric
Ge, Huabin
2015-01-01
In this short note, we prove that the space of all admissible piecewise linear metrics parameterized by length square on a triangulated manifolds is a convex cone. We further study Regge's Einstein-Hilbert action and give a much more reasonable definition of discrete Einstein metric than our former version in \\cite{G}. Finally, we introduce a discrete Ricci flow for three dimensional triangulated manifolds, which is closely related to the existence of discrete Einstein metrics.
A Kernel Classification Framework for Metric Learning
Wang, Faqiang; Zuo, Wangmeng; Zhang, Lei; Meng, Deyu; Zhang, David
2013-01-01
Learning a distance metric from the given training samples plays a crucial role in many machine learning tasks, and various models and optimization algorithms have been proposed in the past decade. In this paper, we generalize several state-of-the-art metric learning methods, such as large margin nearest neighbor (LMNN) and information theoretic metric learning (ITML), into a kernel classification framework. First, doublets and triplets are constructed from the training samples, and a family ...
THE QUALITY METRICS OF INFORMATION SYSTEMS
Directory of Open Access Journals (Sweden)
Zora Arsovski
2008-06-01
Full Text Available Information system is a special kind of products which is depend upon great number variables related to nature, conditions during implementation and organizational clime and culture. Because that quality metrics of information system (QMIS has to reflect all previous aspects of information systems. In this paper are presented basic elements of QMIS, characteristics of implementation and operation metrics for IS, team - management quality metrics for IS and organizational aspects of quality metrics. In second part of this paper are presented results of study of QMIS in area of MIS (Management IS.
Structure of stationary and axisymmetric metrics
International Nuclear Information System (INIS)
We study the structure of stationary and axisymmetric metrics solving the vacuum Einstein equations of general relativity in four and higher dimensions, building on recent work in Phys. Rev. D 70, 124002 (2004). We write the Einstein equations in a new form that naturally identifies the sources for such metrics. The sources live in a one-dimensional subspace and the entire metric is uniquely determined by them. We study in detail the structure of stationary and axisymmetric metrics in four dimensions, and consider as an example the sources of the Kerr black hole
Radiation-dominated area metric cosmology
Schuller, Frederic P
2007-01-01
We provide further crucial support for a refined, area metric structure of spacetime. Based on the solution of conceptual issues, such as the consistent coupling of fermions and the covariant identification of radiation fields on area metric backgrounds, we show that the radiation-dominated epoch of area metric cosmology is equivalent to that epoch in standard Einstein cosmology. This ensures, in particular, successful nucleosynthesis. This surprising result complements the previously derived prediction of a small late-time acceleration of an area metric universe.
About the possibility of a generalized metric
International Nuclear Information System (INIS)
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
Semantic Metrics for Object Oriented Design
Etzkorn, Lethe
2003-01-01
The purpose of this proposal is to research a new suite of object-oriented (OO) software metrics, called semantic metrics, that have the potential to help software engineers identify fragile, low quality code sections much earlier in the development cycle than is possible with traditional OO metrics. With earlier and better Fault detection, software maintenance will be less time consuming and expensive, and software reusability will be improved. Because it is less costly to correct faults found earlier than to correct faults found later in the software lifecycle, the overall cost of software development will be reduced. Semantic metrics can be derived from the knowledge base of a program understanding system. A program understanding system is designed to understand a software module. Once understanding is complete, the knowledge-base contains digested information about the software module. Various semantic metrics can be collected on the knowledge base. This new kind of metric measures domain complexity, or the relationship of the software to its application domain, rather than implementation complexity, which is what traditional software metrics measure. A semantic metric will thus map much more closely to qualities humans are interested in, such as cohesion and maintainability, than is possible using traditional metrics, that are calculated using only syntactic aspects of software.
The Completion of the Manifold of Riemannian Metrics with Respect to its $L^2$ Metric
Clarke, Brian
2009-04-01
This is the author's Ph.D. thesis, submitted to the University of Leipzig. It deals with the $L^2$ Riemannian metric on the manifold of all smooth Riemannian metrics on a fixed closed, finite-dimensional manifold. The main body of the thesis is a description of the completion manifold of metrics with respect to the $L^2$ metric. The primary motivation for studying this problem comes from Teichmueller theory, where similar considerations lead to a completion of the well-known Weil-Petersson metric. We give an application of the main theorem to the completions of Teichmueller space with respect to a class of metrics that generalize the Weil-Petersson metric. We also prove that the $L^2$ metric induces a metric space structure on the manifold of metrics. As the $L^2$ metric is a weak Riemannian metric, this fact does not follow from general results. In addition, we prove several results on the exponential mapping and distance function of a weak Riemannian metric on a Hilbert/Frechet manifold. The statements are ...
Institute of Scientific and Technical Information of China (English)
刘海峰; 刘守生; 姚泽清
2013-01-01
In text categorization, the KNN algorithm is used widely. It is an example-based algorithm. The number of training samples and their position influence the algorithm' s classification performance. A reasonable method for reducing the amount of training data and an optimal weighting way can improve the efficiency of classification. This paper proposes an improved KNN model based on the sample distribution. Firstly, by calculating the distance between the samples, we remove some samples from training set. Secondly, take into account the category deflection; we bring up a better weighting method in order to overcome the defect that the bigger class, higher density of training samples dominated in KNN. The result of experiment shows that the improved KNN classification algorithm improves the efficiency of its classification.%KNN算法是文本分类中广泛应用的算法.作为一种基于实例的算法,训练样本的数量和分布位置影响KNN分类器分类性能.合理的样本剪裁以及样本赋权方法可以提高分类器的效率.提出了一种基于样本分布状况的KNN改进模型.首先基于样本位置对训练集进行删减以节约计算开销,然后针对类偏斜现象对分类器的赋权方式进行优化,改善k近邻选择时大类别、高密度训练样本的占优现象.试验结果表明,本文提出的改进KNN文本分类算法提高了KNN的分类效率.
Using Genetic Algorithms for Building Metrics of Collaborative Systems
Directory of Open Access Journals (Sweden)
Cristian CIUREA
2011-01-01
Full Text Available he paper objective is to reveal the importance of genetic algorithms in building robust metrics of collaborative systems. The main types of collaborative systems in economy are presented and some characteristics of genetic algorithms are described. A genetic algorithm was implemented in order to determine the local maximum and minimum points of the relative complexity function associated to a collaborative banking system. The intelligent collaborative systems based on genetic algorithms, representing the new generation of collaborative systems, are analyzed and the implementation of auto-adaptive interfaces in a banking application is described.
Simple emission metrics for climate impacts
Directory of Open Access Journals (Sweden)
B. Aamaas
2013-06-01
Full Text Available In the context of climate change, emissions of different species (e.g., carbon dioxide and methane are not directly comparable since they have different radiative efficiencies and lifetimes. Since comparisons via detailed climate models are computationally expensive and complex, emission metrics were developed to allow a simple and straightforward comparison of the estimated climate impacts of emissions of different species. Emission metrics are not unique and variety of different emission metrics has been proposed, with key choices being the climate impacts and time horizon to use for comparisons. In this paper, we present analytical expressions and describe how to calculate common emission metrics for different species. We include the climate metrics radiative forcing, integrated radiative forcing, temperature change and integrated temperature change in both absolute form and normalised to a reference gas. We consider pulse emissions, sustained emissions and emission scenarios. The species are separated into three types: CO2 which has a complex decay over time, species with a simple exponential decay, and ozone precursors (NOx, CO, VOC which indirectly effect climate via various chemical interactions. We also discuss deriving Impulse Response Functions, radiative efficiency, regional dependencies, consistency within and between metrics and uncertainties. We perform various applications to highlight key applications of emission metrics, which show that emissions of CO2 are important regardless of what metric and time horizon is used, but that the importance of short lived climate forcers varies greatly depending on the metric choices made. Further, the ranking of countries by emissions changes very little with different metrics despite large differences in metric values, except for the shortest time horizons (GWP20.
Metric of a Slow Rotating Body with Quadrupole Moment from the Erez-Rosen Metric
Frutos-Alfaro, Francisco; Cordero-García, Iván; Ulloa-Esquivel, Oscar
2012-01-01
A metric representing a slow rotating object with quadrupole moment is obtained using the Newman-Janis formalism to include rotation into the weak limit of the Erez-Rosen metric. This metric is intended to tackle relativistic astrometry and gravitational lensing problems in which a quadrupole moment has to be taken into account.
Information metrics (iMetrics): A research specialty with a socio-cognitive identity?
S. Milojević; L. Leydesdorff
2013-01-01
"Bibliometrics", "scientometrics", "informetrics", and "webometrics" can all be considered as manifestations of a single research area with similar objectives and methods, which we call "information metrics" or iMetrics. This study explores the cognitive and social distinctness of iMetrics with resp
Einstein Metrics on Rational Homology Spheres
Boyer, Charles P.; Galicki, Krzysztof
2003-01-01
We prove the existence of Sasakian-Einstein metrics on infinitely many rational homology spheres in all odd dimensions greater than 3. In dimension 5 we obain somewhat sharper results. There are examples where the number of effective parameters in the Einstein metric grows exponentially with dimension.
Advanced Life Support System Value Metric
Jones, Harry W.; Rasky, Daniel J. (Technical Monitor)
1999-01-01
The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have led to the following approach. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are considered to be exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is defined after many trade-offs. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, SVM/[ESM + function (TRL)], with appropriate weighting and scaling. The total value is given by SVM. Cost is represented by higher ESM and lower TRL. The paper provides a detailed description and example application of a suggested System Value Metric and an overall ALS system metric.
Fuzzy Set Field and Fuzzy Metric
Gebru Gebray; B. Krishna Reddy
2014-01-01
The notation of fuzzy set field is introduced. A fuzzy metric is redefined on fuzzy set field and on arbitrary fuzzy set in a field. The metric redefined is between fuzzy points and constitutes both fuzziness and crisp property of vector. In addition, a fuzzy magnitude of a fuzzy point in a field is defined.
Finite Metric Spaces of Strictly Negative Type
DEFF Research Database (Denmark)
Hjorth, Poul; Lisonek, P.; Markvorsen, Steen;
1998-01-01
We prove that, if a finite metric space is of strictly negative type, then its transfinite diameter is uniquely realized by the infinite extender (load vector). Finite metric spaces that have this property include all spaces on two, three, or four points, all trees, and all finite subspaces of Eu...
Weakly contractive maps in altering metric spaces
Turinici, Mihai
2013-01-01
The weakly contractive metric type fixed point result in Berinde [Nonlinear Anal. Forum, 9 (2004), 45-53] is "almost" covered by the related altering metric one due to Khan et al [Bull. Austral. Math. Soc., 30 (1984), 1-9]. Further extensions of these statements are then provided.
Free spaces over some proper metric spaces
Dalet, Aude
2014-01-01
We prove that the Lipschitz-free space over a countable proper metric space is isometric to a dual space and has the metric approximation property. We also show that the Lipschitz-free space over a proper ultrametric space is isometric to the dual of a space which is isomorphic to c_0.
Fixed point theory in metric type spaces
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...
Slowly rotating Curzon-Chazy Metric
Montero-Camacho, Paulo; Gutierrez-Chaves, Carlos
2014-01-01
A new rotation version of the Curzon-Chazy metric is found. This new metric was obtained by means of a perturbation method, in order to include slow rotation. The solution is then proved to fulfill the Einstein field equations using a REDUCE program. Furthermore, the applications of this new solution are discussed.
Invariant metric for nonlinear symplectic maps
Indian Academy of Sciences (India)
Govindan Rangarajan; Minita Sachidanand
2002-03-01
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 demonstrate that the performance of a nonlinear Hamiltonian system is enhanced.
A Complexity Metric for Automated Separation
Aweiss, Arwa
2009-01-01
A metric is proposed to characterize airspace complexity with respect to an automated separation assurance function. The Maneuver Option metric is a function of the number of conflict-free trajectory change options the automated separation assurance function is able to identify for each aircraft in the airspace at a given time. By aggregating the metric for all aircraft in a region of airspace, a measure of the instantaneous complexity of the airspace is produced. A six-hour simulation of Fort Worth Center air traffic was conducted to assess the metric. Results showed aircraft were twice as likely to be constrained in the vertical dimension than the horizontal one. By application of this metric, situations found to be most complex were those where level overflights and descending arrivals passed through or merged into an arrival stream. The metric identified high complexity regions that correlate well with current air traffic control operations. The Maneuver Option metric did not correlate with traffic count alone, a result consistent with complexity metrics for human-controlled airspace.
Trust Metric based Soft Security in Mobile Pervasive Environment
Directory of Open Access Journals (Sweden)
Madhu Sharma Gaur
2014-09-01
Full Text Available In the decentralized and highly dynamic environment like Mobile Pervasive Environments (MPE trust and security measurement are two major challenging issues for community researchers. So far primarily many of architectural frameworks and models developed and being used. In the vision of pervasive computing where mobile applications are growing immensely with the potential of low cost, high performance, and user centric solutions. This paradigm is highly dynamic and heterogeneous and brings along trust and security challenges regarding vulnerabilities and threats due to inherent open connectivity. Despite advances in the technology, there is still a lack of methods to measure the security and level of trust and framework for the assessment and calculation of the degree of the trustworthiness. In this paper, we explore security and trust metrics concerns requirement and challenges to decide the trust computations metric parameters for a self-adaptive self-monitoring trust based security assurance in mobile pervasive environment. The objective is to identify the trust parameters while routing and determine the node behavior for soft security trust metric. In winding up, we put our efforts to set up security assurance model to deal with attacks and vulnerabilities requirements of system under exploration.
Incidental learning of temporal structures conforming to a metrical framework.
Brandon, Melissa; Terry, Josephine; Stevens, Catherine J; Tillmann, Barbara
2012-01-01
Implicit learning of sequential structures has been investigated mostly for visual, spatial, or motor learning, but rarely for temporal structure learning. The few experiments investigating temporal structure learning have concluded that temporal structures can be learned only when coupled with another structural dimension, such as musical pitch or spatial location. In these studies, the temporal structures were without metrical organization and were dependent upon participants' response times (Response-to-Stimulus Intervals). In our study, two experiments investigated temporal structure learning based on Inter-Onset-Intervals in the presence of an uncorrelated second dimension (ordinal structure) with metrically organized temporal structures. Our task was an adaptation of the classical Serial Reaction Time paradigm, using an implicit task in the auditory domain (syllable identification). Reaction times (RT) revealed that participants learned the temporal structures over the exposure blocks (decrease in RT) without a correlated ordinal dimension. The introduction of a test block with a novel temporal structure slowed RT and exemplified the typical implicit learning profile. Post-test results suggested that participants did not have explicit knowledge of the metrical temporal structures. These findings provide the first evidence of the learning of temporal structure with an uncorrelated ordinal structure, and set a foundation for further investigation of temporal cognition.
Topology on locally finite metric spaces
Capraro, Valerio
2011-01-01
The necessity of a theory of General Topology and, most of all, of Algebraic Topology on locally finite metric spaces comes from many areas of research in both Applied and Pure Mathematics: Molecular Biology, Mathematical Chemistry, Computer Science, Topological Graph Theory and Metric Geometry. In this paper we propose the basic notions of such a theory and some applications: we replace the classical notions of continuous function, homeomorphism and homotopic equivalence with the notions of NPP-function, NPP-local-isomorphism and NPP-homotopy (NPP stands for Nearest Point Preserving); we also introduce the notion of NPP-isomorphism. We construct three invariants under NPP-isomorphisms and, in particular, we define the fundamental group of a locally finite metric space. As first applications, we propose the following: motivated by the longstanding question whether there is a purely metric condition which extends the notion of amenability of a group to any metric space, we propose the property SN (Small Neighb...
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.
Geometry of manifolds with area metric
Schuller, F P
2005-01-01
We construct the differential geometry of smooth manifolds equipped with an algebraic curvature map acting as an area measure. Area metric geometry provides a spacetime structure suitable for the discussion of gauge theories and strings, and is considerably more general than Lorentzian geometry. Our construction of geometrically relevant objects, such as an area metric compatible connection and derived tensors, makes essential use of a decomposition theorem due to Gilkey, showing that a general area metric is generated by a finite collection of metrics rather than by a single one. Employing curvature invariants for area metric manifolds we devise an entirely new class of gravity theories with inherently stringy character, and discuss gauge matter actions.
The metrics of science and technology
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...
Algorithms for Game Metrics (Full Version)
Chatterjee, Krishnendu; Majumdar, Rupak; Raman, Vishwanath
2008-01-01
Simulation and bisimulation metrics for stochastic systems provide a quantitative generalization of the classical simulation and bisimulation relations. These metrics capture the similarity of states with respect to quantitative specifications written in the quantitative mu-calculus and related probabilistic logics. We show that game metrics, besides being logically characterized by the quantitative mu-calculus, also provide a bound for discounted and long-run average values of games. We then present algorithms for computing the metrics on Markov decision processes (MDPs), turn-based stochastic games, and concurrent games. For turn-based games and MDPs, we provide a polynomial-time algorithm for the computation of the one-step metric distance between states. The algorithm is based on linear programming. For concurrent games, we show that computing the exact distance between states is at least as hard as computing the value of concurrent reachability games and the square-root-sum problem in computational geome...
FABASOFT BEST PRACTICES AND TEST METRICS MODEL
Directory of Open Access Journals (Sweden)
Nadica Hrgarek
2007-06-01
Full Text Available Software companies have to face serious problems about how to measure the progress of test activities and quality of software products in order to estimate test completion criteria, and if the shipment milestone will be reached on time. Measurement is a key activity in testing life cycle and requires established, managed and well documented test process, defined software quality attributes, quantitative measures, and using of test management and bug tracking tools. Test metrics are a subset of software metrics (product metrics, process metrics and enable the measurement and quality improvement of test process and/or software product. The goal of this paper is to briefly present Fabasoft best practices and lessons learned during functional and system testing of big complex software products, and to describe a simple test metrics model applied to the software test process with the purpose to better control software projects, measure and increase software quality.
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.
A New Metrics for Hierarchical Clustering
Institute of Scientific and Technical Information of China (English)
YANGGuangwen; SHIShuming; WANGDingxing
2003-01-01
Hierarchical clustering is a popular method of performing unsupervised learning. Some metric must be used to determine the similarity between pairs of clusters in hierarchical clustering. Traditional similarity metrics either can deal with simple shapes (i.e. spherical shapes) only or are very sensitive to outliers (the chaining effect). The main contribution of this paper is to propose some potential-based similarity metrics (APES and AMAPES) between clusters in hierarchical clustering, inspired by the concepts of the electric potential and the gravitational potential in electromagnetics and astronomy. The main features of these metrics are: the first, they have strong antijamming capability; the second, they are capable of finding clusters of different shapes such as spherical, spiral, chain, circle, sigmoid, U shape or other complex irregular shapes; the third, existing algorithms and research fruits for classical metrics can be adopted to deal with these new potential-based metrics with no or little modification. Experiments showed that the new metrics are more superior to traditional ones. Different potential functions are compared, and the sensitivity to parameters is also analyzed in this paper.
Altmetrics – a complement to conventional metrics
Melero, Remedios
2015-01-01
Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science - Article-Level Metrics, Altmetric, Impactstory and Plum. PMID:26110028
Altmetrics - a complement to conventional metrics.
Melero, Remedios
2015-01-01
Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science--Article-Level Metrics, Altmetric, Impactstory and Plum.
A Kernel Classification Framework for Metric Learning.
Wang, Faqiang; Zuo, Wangmeng; Zhang, Lei; Meng, Deyu; Zhang, David
2015-09-01
Learning a distance metric from the given training samples plays a crucial role in many machine learning tasks, and various models and optimization algorithms have been proposed in the past decade. In this paper, we generalize several state-of-the-art metric learning methods, such as large margin nearest neighbor (LMNN) and information theoretic metric learning (ITML), into a kernel classification framework. First, doublets and triplets are constructed from the training samples, and a family of degree-2 polynomial kernel functions is proposed for pairs of doublets or triplets. Then, a kernel classification framework is established to generalize many popular metric learning methods such as LMNN and ITML. The proposed framework can also suggest new metric learning methods, which can be efficiently implemented, interestingly, using the standard support vector machine (SVM) solvers. Two novel metric learning methods, namely, doublet-SVM and triplet-SVM, are then developed under the proposed framework. Experimental results show that doublet-SVM and triplet-SVM achieve competitive classification accuracies with state-of-the-art metric learning methods but with significantly less training time. PMID:25347887
An Underwater Color Image Quality Evaluation Metric.
Yang, Miao; Sowmya, Arcot
2015-12-01
Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score. PMID:26513783
Rezaee, Kh.; Azizi, E.; Haddadnia, J.
2016-01-01
Background Epilepsy is a severe disorder of the central nervous system that predisposes the person to recurrent seizures. Fifty million people worldwide suffer from epilepsy; after Alzheimer’s and stroke, it is the third widespread nervous disorder. Objective In this paper, an algorithm to detect the onset of epileptic seizures based on the analysis of brain electrical signals (EEG) has been proposed. 844 hours of EEG were recorded form 23 pediatric patients consecutively with 163 occurrences of seizures. Signals had been collected from Children’s Hospital Boston with a sampling frequency of 256 Hz through 18 channels in order to assess epilepsy surgery. By selecting effective features from seizure and non-seizure signals of each individual and putting them into two categories, the proposed algorithm detects the onset of seizures quickly and with high sensitivity. Method In this algorithm, L-sec epochs of signals are displayed in form of a third-order tensor in spatial, spectral and temporal spaces by applying wavelet transform. Then, after applying general tensor discriminant analysis (GTDA) on tensors and calculating mapping matrix, feature vectors are extracted. GTDA increases the sensitivity of the algorithm by storing data without deleting them. Finally, K-Nearest neighbors (KNN) is used to classify the selected features. Results The results of simulating algorithm on algorithm standard dataset shows that the algorithm is capable of detecting 98 percent of seizures with an average delay of 4.7 seconds and the average error rate detection of three errors in 24 hours. Conclusion Today, the lack of an automated system to detect or predict the seizure onset is strongly felt. PMID:27672628
International Nuclear Information System (INIS)
This case study tests the possibility of prediction for 'success' (or 'winner') components of four stock and shares market indices in a time period of three years from 02-Jul-2009 to 29-Jun-2012.We compare their performance ain two time frames: initial frame three months at the beginning (02/06/2009-30/09/2009) and the final three month frame (02/04/2012-29/06/2012).To label the components, average price ratio between two time frames in descending order is computed. The average price ratio is defined as the ratio between the mean prices of the beginning and final time period. The 'winner' components are referred to the top one third of total components in the same order as average price ratio it means the mean price of final time period is relatively higher than the beginning time period. The 'loser' components are referred to the last one third of total components in the same order as they have higher mean prices of beginning time period. We analyse, is there any information about the winner-looser separation in the initial fragments of the daily closing prices log-returns time series.The Leave-One-Out Cross-Validation with k-NN algorithm is applied on the daily log-return of components using a distance and proximity in the experiment. By looking at the error analysis, it shows that for HANGSENG and DAX index, there are clear signs of possibility to evaluate the probability of long-term success. The correlation distance matrix histograms and 2-D/3-D elastic maps generated from ViDaExpert show that the 'winner' components are closer to each other and 'winner'/'loser' components are separable on elastic maps for HANGSENG and DAX index while for the negative possibility indices, there is no sign of separation
Shi, Y.; Gorban, A. N.; Y Yang, T.
2014-03-01
This case study tests the possibility of prediction for 'success' (or 'winner') components of four stock & shares market indices in a time period of three years from 02-Jul-2009 to 29-Jun-2012.We compare their performance ain two time frames: initial frame three months at the beginning (02/06/2009-30/09/2009) and the final three month frame (02/04/2012-29/06/2012).To label the components, average price ratio between two time frames in descending order is computed. The average price ratio is defined as the ratio between the mean prices of the beginning and final time period. The 'winner' components are referred to the top one third of total components in the same order as average price ratio it means the mean price of final time period is relatively higher than the beginning time period. The 'loser' components are referred to the last one third of total components in the same order as they have higher mean prices of beginning time period. We analyse, is there any information about the winner-looser separation in the initial fragments of the daily closing prices log-returns time series.The Leave-One-Out Cross-Validation with k-NN algorithm is applied on the daily log-return of components using a distance and proximity in the experiment. By looking at the error analysis, it shows that for HANGSENG and DAX index, there are clear signs of possibility to evaluate the probability of long-term success. The correlation distance matrix histograms and 2-D/3-D elastic maps generated from ViDaExpert show that the 'winner' components are closer to each other and 'winner'/'loser' components are separable on elastic maps for HANGSENG and DAX index while for the negative possibility indices, there is no sign of separation.
Wang, Wei
2014-06-22
In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.
Generalized Painlev\\'e-Gullstrand metrics
Lin, Chun-Yu
2008-01-01
An obstruction to the implementation of spatially flat Painleve-Gullstrand(PG) slicings is demonstrated, and explicitly discussed for Reissner-Nordstrom 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.
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...... matrix of a finite metric space is both hypermetric and regular, then it is of strictly negative type. We show that the strictly negative type finite subspaces of spheres are precisely those which do not contain two pairs of antipodal points....
Propagation of light in area metric backgrounds
Energy Technology Data Exchange (ETDEWEB)
Punzi, Raffaele; Wohlfarth, Mattias N R [Zentrum fuer Mathematische Physik und II. Institut fuer Theoretische Physik, Universitaet Hamburg, Luruper Chaussee 149, 22761 Hamburg (Germany); Schuller, Frederic P, E-mail: raffaele.punzi@desy.d, E-mail: fps@aei.mpg.d, E-mail: mattias.wohlfarth@desy.d [Max Planck Institut fuer Gravitationsphysik, Albert Einstein Institut, Am Muehlenberg 1, 14467 Potsdam (Germany)
2009-02-07
The propagation of light in area metric spacetimes, which naturally emerge as refined backgrounds in quantum electrodynamics and quantum gravity, is studied from first principles. In the geometric-optical limit, light rays are found to follow geodesics in a Finslerian geometry, with the Finsler norm being determined by the area metric tensor. Based on this result, and an understanding of the nonlinear relation between ray vectors and wave covectors in such refined backgrounds, we study light deflection in spherically symmetric situations and obtain experimental bounds on the non-metricity of spacetime in the solar system.
Inspecting Baby Skyrmions with Effective Metrics
Gibbons, Gary
2014-01-01
In the present paper we investigate the causal structure of the baby Skyrme model using appropriate geometrical tools. We discuss several features of excitations propagating on top of background solutions and show that the evolution of high frequency waves is governed by a curved effective geometry. Examples are given for which the effective metric describes the interaction between waves and solitonic solutions such as kinks, antikinks and Hedgehogs. In particular, it is shown how violent processes involving the collisions of solitons and antisolitons may induce metrics which are not globaly hyperbolic. We argue that it might be illuminating to calculate the effective metric as a diagnostic test for pathological regimes in numerical simulations.
Software metrics a rigorous and practical approach
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
p-Hausdorff度量%p-Hausdorff metric
Institute of Scientific and Technical Information of China (English)
何日高
2011-01-01
According to the properties of Firey combination,we first introduce the p-Hausdorff metric,which coincides with the well-known Hausdorff metric in the case p = 1.Then we give two important results on the p-Hausdorff metric.%根据Firey组合的属性,引入p-Hausdorff度量,特别地,当p=1时,p-Hausdorff度量就是著名的Hausdorff度量.进一步运用凸几何分析理论证明关于p-Hausdorff度量的2个重要结论.
Metric Entropy of Nonautonomous Dynamical Systems
Directory of Open Access Journals (Sweden)
Kawan Christoph
2014-01-01
Full Text Available We introduce the notion of metric entropy for a nonautonomous dynamical system given by a sequence (Xn; μn of probability spaces and a sequence of measurable maps fn : Xn → Xn+1 with fnμn = μn+1. This notion generalizes the classical concept of metric entropy established by Kolmogorov and Sinai, and is related via a variational inequality to the topological entropy of nonautonomous systems as defined by Kolyada, Misiurewicz, and Snoha. Moreover, it shares several properties with the classical notion of metric entropy. In particular, invariance with respect to appropriately defined isomorphisms, a power rule, and a Rokhlin-type inequality are proved
Holographic computations of the Quantum Information Metric
Trivella, Andrea
2016-01-01
In this note we show how the Quantum Information Metric can be computed holographically using a perturbative approach. In particular when the deformation of the conformal field theory state is induced by a scalar operator the corresponding bulk configuration reduces to a scalar field perturbatively probing the unperturbed background. We study two concrete examples: a CFT ground state deformed by a primary operator and thermofield double state in $d=2$ deformed by a marginal operator. Finally, we generalize the bulk construction to the case of a multi dimensional parameter space and show that the Quantum Information Metric coincides with the metric of the non-linear sigma model for the corresponding scalar fields.
Learnometrics: Metrics for Learning Objects (Learnometrics: metrieken voor leerobjecten)
Ochoa, Xavier
2008-01-01
- Introduction - Quantitative Analysis of the Publication of Learning Objects - Quantiative Analysis of the Reuse of Learning Objects - Metadata Quality Metrics for Learning Objects - Relevance Ranking Metrics for Learning Objects - Metrics Service Architecture and Use Cases - Conclusions
Classroom reconstruction of the Schwarzschild metric
Kassner, Klaus
2015-01-01
A promising way to introduce general relativity in the classroom is to study the physical predictions that follow from 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 weak-field limit of the Schwarzschild metric with a minimum of relatively simple physical assumptions. Since this does not appear sufficient to arrive at a form of the metric useful for more than the most basic predictions (gravitational redshift), the determination of a single additional parameter from experiment is admitted. An attractive experimental candidate is the measurement of the perihelion precession of Mercury, because the result was already known before the completion of general relativity. It is sh...
Thermodynamic motivations of spherically symmetric static metrics
Moradpour, H
2015-01-01
Bearing the thermodynamic arguments together with the two definitions of mass in mind, we try to find metrics with spherical symmetry. We consider the adiabatic condition along with the Gong-Wang mass, and evaluate the $g_{rr}$ element which points to a null hypersurface. In addition, we generalize the thermodynamics laws to this hypersurface to find its temperature and thus the corresponding surface gravity which enables us to get a relation for the $g_{tt}$ element. Finally, we investigate the mathematical and physical properties of the discovered metric in the Einstein relativity framework which shows that the primary mentioned null hypersurface is an event horizon. We also show that if one considers the Misner-Sharp mass in the calculations, the Schwarzschild metric will be got. The relationship between the two mass definitions in each metric is studied. The results of considering the geometrical surface gravity are also addressed.
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.
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.
Medicare Contracting - Redacted Benchmark Metric Reports
U.S. Department of Health & Human Services — The Centers for Medicare and Medicaid Services has compiled aggregate national benchmark cost and workload metrics using data submitted to CMS by the AB MACs and...
Lorentzian Einstein metrics with prescribed conformal infinity
Enciso, Alberto
2014-01-01
We prove that there are asymptotically anti-de Sitter Einstein metrics with prescribed conformal infinity. More precisely we show that, given any suitably small perturbation $\\hat g$ of the conformal metric of the $(n+1)$-dimensional anti-de Sitter space at timelike infinity, which is given by the canonical Lorentzian metric on the $n$-dimensional cylinder, there is a Lorentzian Einstein metric on $(-T,T)\\times \\mathbb{B}^n$ whose conformal geometry is given by $\\hat g$. This is a Lorentzian counterpart of the Graham-Lee theorem in Riemannian geometry and is motivated by the holographic prescription problem in the context of the AdS/CFT correspondence in string theory.
Function contractive maps in partial metric spaces
Turinici, Mihai
2012-01-01
Some fixed point results are given for a class of functional contractions over partial metric spaces. These extend some contributions in the area due to Ilic et al [Math. Comput. Modelling, 55 (2012), 801-809].
Flight Crew State Monitoring Metrics Project
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)....
Evaluating Web Accessibility Metrics for Jordanian Universities
Directory of Open Access Journals (Sweden)
Israa Wahbi Kamal
2016-07-01
Full Text Available University web portals are considered one of the main access gateways for universities. Typically, they have a large candidate audience among the current students, employees, and faculty members aside from previous and future students, employees, and faculty members. Web accessibility is the concept of providing web content universal access to different machines and people with different ages, skills, education levels, and abilities. Several web accessibility metrics have been proposed in previous years to measure web accessibility. We integrated and extracted common web accessibility metrics from the different accessibility tools used in this study. This study evaluates web accessibility metrics for 36 Jordanian universities and educational institute websites. We analyze the level of web accessibility using a number of available evaluation tools against the standard guidelines for web accessibility. Receiver operating characteristic quality measurements is used to evaluate the effectiveness of the integrated accessibility metrics.
MPLS/VPN traffic engineering: SLA metrics
Cherkaoui, Omar; MacGibbon, Brenda; Blais, Michel; Serhrouchni, Ahmed
2001-07-01
Traffic engineering must be concerned with a broad definition of service that includes network availability, reliability and stability, as well as traditional traffic data on loss, throughput, delay and jitter. MPLS and Virtual Private Networks (VPNs) significantly contribute to security and Quality of Service (QoS) within communication networks, but there remains a need for metric measurement and evaluation. The purpose of this paper is to propose a methodology which gives a measure for LSP ( Lfew abel Switching Paths) metrics in VPN MPLS networks. We propose here a statistical method for the evaluation of those metrics. Statistical methodology is very important in this type of study since there is a large amount of data to consider. We use the notions of sample surveys, self-similar processes, linear regression, additive models and bootstrapping. The results obtained allows us to estimate the different metrics for such SLAs.
Effectively nonlocal metric-affine gravity
Golovnev, Alexey; Sandstad, Marit
2015-01-01
In metric-affine theories of gravity such as the C-theories, the spacetime connection is associated to a metric that is nontrivially related to the physical metric. In this article, such theories are rewritten in terms of a single metric and it is shown that they can be recast as effectively nonlocal gravity. With some assumptions, known ghost-free theories with non-singular and cosmologically interesting properties may be recovered. Relations between different formulations are analysed at both perturbative and nonperturbative levels taking carefully into account subtleties with boundary conditions in the presence of integral operators in the action, and equivalences between theories related by nonlocal redefinitions of the fields are verified at the level of equations of motion. This suggests a possible geometrical interpretation of nonlocal gravity as an emergent property of non-Riemannian spacetime structure.
Effectively nonlocal metric-affine gravity
Golovnev, Alexey; Koivisto, Tomi; Sandstad, Marit
2016-03-01
In metric-affine theories of gravity such as the C-theories, the spacetime connection is associated to a metric that is nontrivially related to the physical metric. In this article, such theories are rewritten in terms of a single metric, and it is shown that they can be recast as effectively nonlocal gravity. With some assumptions, known ghost-free theories with nonsingular and cosmologically interesting properties may be recovered. Relations between different formulations are analyzed at both perturbative and nonperturbative levels, taking carefully into account subtleties with boundary conditions in the presence of integral operators in the action, and equivalences between theories related by nonlocal redefinitions of the fields are verified at the level of equations of motion. This suggests a possible geometrical interpretation of nonlocal gravity as an emergent property of non-Riemannian spacetime structure.
RICCI SOLITONS IN CONTACT METRIC MANIFOLDS
Tripathi, Mukut
2011-01-01
In $N(k)$-contact metric manifolds and/or $(k,\\mu)$-manifolds, gradient Ricci solitons, compact Ricci solitons and Ricci solitons with $V$ pointwise collinear with the structure vector field $\\xi $ are studied.
NPScape Metric GIS Data - Conservation Status
National Park Service, Department of the Interior — NPScape conservation status metrics are calculated using data from the USGS Gap Analysis Program (PAD-US), World Protected Areas Database (WDPA), and National...
Classroom reconstruction of the Schwarzschild metric
Kassner, Klaus
2015-11-01
A promising way to introduce general relativity (GR) 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 weak-field limit of the Schwarzschild metric with a minimum of relatively simple physical assumptions, avoiding the field equations but admitting the determination of a single parameter from experiment. An attractive experimental candidate is the measurement of the perihelion precession of Mercury, because the result was already known before the completion of GR. It is shown how to determine the temporal and radial coefficients of the Schwarzschild metric to sufficiently high accuracy to obtain quantitative predictions for all the remaining classical tests of GR.
On Generalized m-th Root Finsler Metrics
Tayebi, A.; Peyghan, E.; M. Shahbazi
2013-01-01
In this paper, we characterize locally dually flat generalized m-th root Finsler metrics. Then we find a condition under which a generalized m-th root metric is projectively related to a m-th root metric. Finally, we prove that if a generalized m-th root metric is conformal to a m-th root metric, then both of them reduce to Riemannian metrics.
Application-adaptive resource scheduling in a computational grid
Institute of Scientific and Technical Information of China (English)
LUAN Cui-ju; SONG Guang-hua; ZHENG Yao
2006-01-01
Selecting appropriate resources for running a job efficiently is one of the common objectives in a computational grid.Resource scheduling should consider the specific characteristics of the application, and decide the metrics to be used accordingly.This paper presents a distributed resource scheduling framework mainly consisting of a job scheduler and a local scheduler. In order to meet the requirements of different applications, we adopt HGSA, a Heuristic-based Greedy Scheduling Algorithm, to schedule jobs in the grid, where the heuristic knowledge is the metric weights of the computing resources and the metric workload impact factors. The metric weight is used to control the effect of the metric on the application. For different applications, only metric weights and the metric workload impact factors need to be changed, while the scheduling algorithm remains the same.Experimental results are presented to demonstrate the adaptability of the HGSA.
Metrics and Energy Landscapes in Irreversible Thermodynamics
Bjarne Andresen
2015-01-01
We describe how several metrics are possible in thermodynamic state space but that only one, Weinhold’s, has achieved widespread use. Lengths calculated based on this metric have been used to bound dissipation in finite-time (irreversible) processes be they continuous or discrete, and described in the energy picture or the entropy picture. Examples are provided from thermodynamics of heat conversion processes as well as chemical reactions. Even losses in economics can be bounded using a therm...
Marketing communication metrics for social media
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...
A Laplacian on Metric Measure Spaces
DEFF Research Database (Denmark)
Kokkendorff, Simon Lyngby
2006-01-01
We introduce a Laplacian on a class of metric measure spaces via a direct pointwise mean value definition. Fundamental properties of this Laplacian, such as its symmetry as an operator on functions satisfying a Neumann or Dirichlet condition, are established.......We introduce a Laplacian on a class of metric measure spaces via a direct pointwise mean value definition. Fundamental properties of this Laplacian, such as its symmetry as an operator on functions satisfying a Neumann or Dirichlet condition, are established....
A new multi-neuron spike-train metric
Houghton, Conor; Sen, Kamal
2008-01-01
The Victor-Purpura spike-train metric has recently been extended to a family of multi-neuron metrics and used to analyze spike trains recorded simultaneously from pairs of proximate neurons. The Victor-Purpura metric is one of the two metrics commonly used for quantifying the distance between two spike trains, the other is the van Rossum metric. Here, we suggest an extension of the van Rossum metric to a multi-neuron metric. We believe this gives a metric which is both natural and easy to cal...
A new multi-neuron spike-train metric
HOUGHTON, CONOR JAMES
2008-01-01
PUBLISHED The Victor-Purpura spike-train metric has recently been extended to a family of multi-neuron metrics and used to analyze spike trains recorded simultaneously from pairs of proximate neurons. The Victor- Purpura metric is one of the two metrics commonly used for quantify- ing the distance between two spike trains, the other is the van Rossum metric. Here, we suggest an extension of the van Rossum metric to a multi-neuron metric. We believe this gives a metric whi...
A metric and frameworks for resilience analysis of engineered and infrastructure systems
International Nuclear Information System (INIS)
In this paper, we have reviewed various approaches to defining resilience and the assessment of resilience. We have seen that while resilience is a useful concept, its diversity in usage complicates its interpretation and measurement. In this paper, we have proposed a resilience analysis framework and a metric for measuring resilience. Our analysis framework consists of system identification, resilience objective setting, vulnerability analysis, and stakeholder engagement. The implementation of this framework is focused on the achievement of three resilience capacities: adaptive capacity, absorptive capacity, and recoverability. These three capacities also form the basis of our proposed resilience factor and uncertainty-weighted resilience metric. We have also identified two important unresolved discussions emerging in the literature: the idea of resilience as an epistemological versus inherent property of the system, and design for ecological versus engineered resilience in socio-technical systems. While we have not resolved this tension, we have shown that our framework and metric promote the development of methodologies for investigating “deep” uncertainties in resilience assessment while retaining the use of probability for expressing uncertainties about highly uncertain, unforeseeable, or unknowable hazards in design and management activities. - Highlights: • While resilience is a useful concept, its diversity in usage complicates its interpretation and measurement. • We proposed a resilience analysis framework whose implementation is encapsulated within resilience metric incorporating absorptive, adaptive, and restorative capacities. • We have shown that our framework and metric can support the investigation of “deep” uncertainties in resilience assessment or analysis. • We have discussed the role of quantitative metrics in design for ecological versus engineered resilience in socio-technical systems. • Our resilience metric supports
Integrated Metrics for Improving the Life Cycle Approach to Assessing Product System Sustainability
Directory of Open Access Journals (Sweden)
Wesley Ingwersen
2014-03-01
Full Text Available Life cycle approaches are critical for identifying and reducing environmental burdens of products. While these methods can indicate potential environmental impacts of a product, current Life Cycle Assessment (LCA methods fail to integrate the multiple impacts of a system into unified measures of social, economic or environmental performance related to sustainability. Integrated metrics that combine multiple aspects of system performance based on a common scientific or economic principle have proven to be valuable for sustainability evaluation. In this work, we propose methods of adapting four integrated metrics for use with LCAs of product systems: ecological footprint, emergy, green net value added, and Fisher information. These metrics provide information on the full product system in land, energy, monetary equivalents, and as a unitless information index; each bundled with one or more indicators for reporting. When used together and for relative comparison, integrated metrics provide a broader coverage of sustainability aspects from multiple theoretical perspectives that is more likely to illuminate potential issues than individual impact indicators. These integrated metrics are recommended for use in combination with traditional indicators used in LCA. Future work will test and demonstrate the value of using these integrated metrics and combinations to assess product system sustainability.
Isometry groups of proper metric spaces
Niemiec, Piotr
2012-01-01
Given a locally compact Polish space X, a necessary and sufficient condition for a group G of homeomorphisms of X to be the full isometry group of (X,d) for some proper metric d on X is given. It is shown that every locally compact Polish group G acts freely on GxY as the full isometry group of GxY with respect to a certain proper metric on GxY, where Y is an arbitrary locally compact Polish space with (card(G),card(Y)) different from (1,2). Locally compact Polish groups which act effectively and almost transitively on complete metric spaces as full isometry groups are characterized. Locally compact Polish non-Abelian groups on which every left invariant metric is automatically right invariant are characterized and fully classified. It is demonstrated that for every locally compact Polish space X having more than two points the set of proper metrics d such that Iso(X,d) = {id} is dense in the space of all proper metrics on X.
Metric of Rotating Charged Spherical Mass in Vacuum for Vector Graviton Metric Theory of Gravitation
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Based on the vector graviton metric theory of gravitation (VGM) suggested by one of the authors of this article, using the method of null tetrad and analytic continuation, this paper gives the metric of the rotating charged spherical mass in VGM. The result shows once again that a replacement of G by G* = G(1 - G M /2r) in general relativity will yield the corresponding result in VGM for the metric in vacuum.
Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.
Energy Technology Data Exchange (ETDEWEB)
Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K; Melander, Darryl J.; Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Robert Charles,
2015-01-01
Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.
New text clustering algorithm based on CF tree and KNN graph partition%一种CF树结合KNN图划分的文本聚类算法
Institute of Scientific and Technical Information of China (English)
仰孝富; 齐建东; 吉鹏飞; 朱文飞
2015-01-01
In order to improve the effect of text clustering, and to mend the flaws of traditional clustering algorithm in parameter setting and algorithm stability, a new text clustering algorithm TCBIBK(a Text Clustering algorithm Based on Improved BIRCH and K-nearest neighbor)is presented. TCBIBK uses BIRCH clustering algorithm as the prototype. During the process of clustering, besides analyzing the distance between text objects and clusters, TCBIBK also analyzes the distance between clusters and clusters, takes the active cluster merging or segmentation, and sets the dynamic threshold. Combined with KNN classification algorithm, TCBIBK improves the algorithm stability under the premise of ensuring the good effi-ciency of clustering. When applied to text clustering, TCBIBK can improve the text clustering effect. The results of com-parative experiment shows that this algorithm can greatly improve the validity and stability of text clustering.%为了提升文本聚类效果，改善传统聚类算法在参数设定，稳定性等方面存在的不足，提出新的文本聚类算法TCBIBK（a Text Clustering algorithm Based on Improved BIRCH and K-nearest neighbor）。该算法以BIRCH聚类算法为原型，聚类过程中除判断文本对象与簇的距离外，增加判断簇与簇之间的距离，采取主动的簇合并或分裂，设置动态的阈值。同时结合KNN分类算法，在保证良好聚类效率前提下提升聚类稳定性，将TCBIBK算法应用于文本聚类，能够提高文本聚类效果。对比实验结果表明，该算法聚类有效性与稳定性都得到较大提高。
Iris Recognition Based on Grouping KNN and Rectangle Convention%基于组合K近邻与矩阵变换的虹膜识别
Institute of Scientific and Technical Information of China (English)
章慧; 陈智勇; 严云洋
2011-01-01
研究人眼虹膜识别问题,因实际虹膜内边界并不是标准圆,引起识别精度差,影响有效的特征提取.传统利用圆模板定位的算法存在瞳孔遗留或纹理损失且定位时间长等问题,为提高虹膜定位精度,降低识别时间,提出了一种新的虹膜识别算法.首先对图像进行去除光斑等预处理,将含有虹膜图像的圆环变换为极坐标系下的矩形,在矩形坐标上以点、线检测确定虹膜轮廓,并对EMD提取纹理分布特征,根据比对距离寻找每个待测样本的K个近邻,以简单投票决策输出识别结果.基于CASIA虹膜图像库进行仿真,结果表明,识别率高达99％,并明显降低了识别时间,使虹膜定位可有效提升识别精度.%In iris recognition, as a large amount of experiments show, the inner edge of iris is not an ideal circle, thus edges may incorporate some information that does not belong to the iris or some iris texture information is cut though traditional localization method using round template. To improve the accuracy of iris location, reduce the recognition time, this paper developet a new iris recognition algorithm. Firstly, the light pot within the pupil was filled in the original image, then the image was unfolded into a rectangle and the circle detection was substituted bythe point and line detection in the rectangle image to find the inner and outer edge. Secondly, texture features were extracted by EMD. Thirdly, the K nearest neighbors ( KNN) of each test sample were found based on distance of Ma-halanibis. Lastly, recognition results were decided by majority voting method. The recognition accuracy of simulation experiments based on CASIA iris image database is up to 99% and requires less running time. The results show that compared with circle template, rectangle convention locates the iris more accurately, and effectively raises the recognition accuracy.
SOFTWARE METRICS VALIDATION METHODOLOGIES IN SOFTWARE ENGINEERING
Directory of Open Access Journals (Sweden)
K.P. Srinivasan
2014-12-01
Full Text Available In the software measurement validations, assessing the validation of software metrics in software engineering is a very difficult task due to lack of theoretical methodology and empirical methodology [41, 44, 45]. During recent years, there have been a number of researchers addressing the issue of validating software metrics. At present, software metrics are validated theoretically using properties of measures. Further, software measurement plays an important role in understanding and controlling software development practices and products. The major requirement in software measurement is that the measures must represent accurately those attributes they purport to quantify and validation is critical to the success of software measurement. Normally, validation is a collection of analysis and testing activities across the full life cycle and complements the efforts of other quality engineering functions and validation is a critical task in any engineering project. Further, validation objective is to discover defects in a system and assess whether or not the system is useful and usable in operational situation. In the case of software engineering, validation is one of the software engineering disciplines that help build quality into software. The major objective of software validation process is to determine that the software performs its intended functions correctly and provides information about its quality and reliability. This paper discusses the validation methodology, techniques and different properties of measures that are used for software metrics validation. In most cases, theoretical and empirical validations are conducted for software metrics validations in software engineering [1-50].
Cleanroom Energy Efficiency: Metrics and Benchmarks
Energy Technology Data Exchange (ETDEWEB)
International SEMATECH Manufacturing Initiative; Mathew, Paul A.; Tschudi, William; Sartor, Dale; Beasley, James
2010-07-07
Cleanrooms are among the most energy-intensive types of facilities. This is primarily due to the cleanliness requirements that result in high airflow rates and system static pressures, as well as process requirements that result in high cooling loads. Various studies have shown that there is a wide range of cleanroom energy efficiencies and that facility managers may not be aware of how energy efficient their cleanroom facility can be relative to other cleanroom facilities with the same cleanliness requirements. Metrics and benchmarks are an effective way to compare one facility to another and to track the performance of a given facility over time. This article presents the key metrics and benchmarks that facility managers can use to assess, track, and manage their cleanroom energy efficiency or to set energy efficiency targets for new construction. These include system-level metrics such as air change rates, air handling W/cfm, and filter pressure drops. Operational data are presented from over 20 different cleanrooms that were benchmarked with these metrics and that are part of the cleanroom benchmark dataset maintained by Lawrence Berkeley National Laboratory (LBNL). Overall production efficiency metrics for cleanrooms in 28 semiconductor manufacturing facilities in the United States and recorded in the Fabs21 database are also presented.
Graphlet Based Metrics for the Comparison of Gene Regulatory Networks
Martin, Alberto J. M.; Dominguez, Calixto; Contreras-Riquelme, Sebastián; Holmes, David S.; Perez-Acle, Tomas
2016-01-01
Understanding the control of gene expression remains one of the main challenges in the post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene expression levels. These variations underlay almost all relevant biological phenomena, including disease and adaptation to environmental conditions. However, computational tools to identify how regulation changes are scarce. Regulation of gene expression is usually depicted in the form of a gene regulatory network (GRN). Structural changes in a GRN over time and conditions represent variations in the regulation of gene expression. Like other biological networks, GRNs are composed of basic building blocks called graphlets. As a consequence, two new metrics based on graphlets are proposed in this work: REConstruction Rate (REC) and REC Graphlet Degree (RGD). REC determines the rate of graphlet similarity between different states of a network and RGD identifies the subset of nodes with the highest topological variation. In other words, RGD discerns how th GRN was rewired. REC and RGD were used to compare the local structure of nodes in condition-specific GRNs obtained from gene expression data of Escherichia coli, forming biofilms and cultured in suspension. According to our results, most of the network local structure remains unaltered in the two compared conditions. Nevertheless, changes reported by RGD necessarily imply that a different cohort of regulators (i.e. transcription factors (TFs)) appear on the scene, shedding light on how the regulation of gene expression occurs when E. coli transits from suspension to biofilm. Consequently, we propose that both metrics REC and RGD should be adopted as a quantitative approach to conduct differential analyses of GRNs. A tool that implements both metrics is available as an on-line web server (http://dlab.cl/loto). PMID:27695050
Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set
Directory of Open Access Journals (Sweden)
Jinna Li
2012-01-01
Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.
14 CFR 1260.115 - Metric system of measurement.
2010-01-01
... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Metric system of measurement. 1260.115....115 Metric system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for...
Demonstration of the Symmetry Properties of Gravitational Metric Fields
Institute of Scientific and Technical Information of China (English)
邵亮; H.NODA; 邵丹; 邵常贵
2002-01-01
We calculate some Wilson loop functionals in a static sphere-symmetrical diagonal metric field and a gravitational metric field established by a cosmic string. Using the direction change of vector when it is parallel transported in the metric field of cosmic string, the cone symmetry of the metric field is shown.
Graev metrics on free products and HNN extensions
Slutsky, Konstantin
2011-01-01
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 metric spaces
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.
43 CFR 12.915 - Metric system of measurement.
2010-10-01
... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Metric system of measurement. 12.915... Requirements § 12.915 Metric system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred...
34 CFR 74.15 - Metric system of measurement.
2010-07-01
... 34 Education 1 2010-07-01 2010-07-01 false Metric system of measurement. 74.15 Section 74.15... Metric system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for...
A proposal test of the space-time metricity.
Grassi, A. M.; Strini, G.
Among the standard hypothesis about gravitational theories, there is the "metricity" hypothesis for the space-time metric. Hehl, McCrea, Ne'eman and others have proposed a non-metricity. With the help of simple additional hypothesis, based on a previous experiment by Harris et al., the authors propose a metricity test by means of spectroscopic tests on meteorites.
Evaluating Search Engine Relevance with Click-Based Metrics
Radlinski, Filip; Kurup, Madhu; Joachims, Thorsten
Automatically judging the quality of retrieval functions based on observable user behavior holds promise for making retrieval evaluation faster, cheaper, and more user centered. However, the relationship between observable user behavior and retrieval quality is not yet fully understood. In this chapter, we expand upon, Radlinski et al. (How does clickthrough data reflect retrieval quality, In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), 43-52, 2008), presenting a sequence of studies investigating this relationship for an operational search engine on the arXiv.org e-print archive. We find that none of the eight absolute usage metrics we explore (including the number of clicks observed, the frequency with which users reformulate their queries, and how often result sets are abandoned) reliably reflect retrieval quality for the sample sizes we consider. However, we find that paired experiment designs adapted from sensory analysis produce accurate and reliable statements about the relative quality of two retrieval functions. In particular, we investigate two paired comparison tests that analyze clickthrough data from an interleaved presentation of ranking pairs, and find that both give accurate and consistent results. We conclude that both paired comparison tests give substantially more accurate and sensitive evaluation results than the absolute usage metrics in our domain.
Enhanced Accident Tolerant LWR Fuels: Metrics Development
Energy Technology Data Exchange (ETDEWEB)
Shannon Bragg-Sitton; Lori Braase; Rose Montgomery; Chris Stanek; Robert Montgomery; Lance Snead; Larry Ott; Mike Billone
2013-09-01
The Department of Energy (DOE) Fuel Cycle Research and Development (FCRD) Advanced Fuels Campaign (AFC) is conducting research and development on enhanced Accident Tolerant Fuels (ATF) for light water reactors (LWRs). This mission emphasizes the development of novel fuel and cladding concepts to replace the current zirconium alloy-uranium dioxide (UO2) fuel system. The overall mission of the ATF research is to develop advanced fuels/cladding with improved performance, reliability and safety characteristics during normal operations and accident conditions, while minimizing waste generation. The initial effort will focus on implementation in operating reactors or reactors with design certifications. To initiate the development of quantitative metrics for ATR, a LWR Enhanced Accident Tolerant Fuels Metrics Development Workshop was held in October 2012 in Germantown, MD. This paper summarizes the outcome of that workshop and the current status of metrics development for LWR ATF.
Metric Learning for Hyperspectral Image Segmentation
Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca
2011-01-01
We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.
Flowing Liquid Crystal Simulating the Schwarzschild Metric
Pereira, Erms R
2009-01-01
We show how to simulate the equatorial section of the Schwarzschild metric through a flowing liquid crystal in its nematic phase. Inside a liquid crystal in the nematic phase, a traveling light ray feels an effective metric, whose properties are linked to perpendicular and parallel refractive indexes, $n_o$ e $n_e$ respectively, of the rod-like molecule of the liquid crystal. As these indexes depend on the scalar order parameter of the liquid crystal, the Beris-Edwards hydrodynamic theory is used to connect the order parameter with the velocity of a liquid crystal flow at each point. This way we calculate a radial velocity profile that simulates the equatorial section of the Schwarzschild metric, in the region outside of Schwarzschild's radius, in the nematic phase of the liquid crystal. In our model, the higher flow velocity can be of the order of some meters per second.
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.
Social Metrics Applied to Smart Tourism
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.
Rainbow Rindler metric and Unruh effect
Yadav, Gaurav; Majhi, Bibhas Ranjan
2016-01-01
The energy of a particle moving on a spacetime, in principle, can affect the background metric. The modifications to it depend on the ratio of energy of the particle and the Planck energy, known as rainbow gravity. Here we find the explicit expressions for the coordinate transformations from rainbow Minkowski spacetime to accelerated frame. The corresponding metric is also obtained which we call as rainbow-Rindler metric. So far we are aware of, no body has done it in a concrete manner. Here this is found from the first principle and hence all the parameters are properly identified. The advantage of this is that the calculated Unruh temperature is compatible with the Hawking temperature of the rainbow black hole horizon, obtained earlier. Since the accelerated frame has several importance in revealing various properties of gravity, we believe that the present result will not only fill that gap, but also help to explore different aspects of rainbow gravity paradigm.
Smgcd: metrics for biological sequence data
International Nuclear Information System (INIS)
In the realm of bioinformatics, the key challenges are to manage, store and retrieve the biological data efficiently. It can be classified in to structured, unstructured and semi-structured contents. Typically, the semi-structured biological data comprised of biological sequences. The complex biological sequences produce huge volume of biological data which further produce much more problems for its management, storage and retrieval. This paper proposed metrics; namely, symmetry measure, molecular weight measure, similarity or diversity measure, size base measure, size gap measure, complexity measure and size complexity diversity measure to manage the raised problems in biological data sequences. These metrics measure the sequence complexity, molecular weights, length with gaps and without gaps, its symmetry and similarity through mathematical formulations. The metrics are demonstrated and validated using the proposed hybrid technique which combines empirical evidence with theoretical formulation. This research opens new horizons for efficient management to measure the functionality and quality of metadata for single and multiple biological sequences. (author)
Single Kerr-Schild metrics: a double view
Energy Technology Data Exchange (ETDEWEB)
McIntosh, C.B.G.; Hickman, M.S.
1988-08-01
Real-vacuum single Kerr-Schild (ISKS) metrics are discussed and new results proved. It is shown that if they Weyl tensor of such a metric has a twist-free expanding principal null direction, then it belongs to the Schwarzchild family of metrics-there are no Petrov type-II Robinson-Trautman metrics of Kerr-Schild type. If such a metric has twist then it belongs either to the Kerr family or else its Weyl tensor is of Petrov type II. The main part of the paper is concerned with complexified versions of Kerr-Schild metrics. The general real ISKS metric is written in double Kerr-Schild (IDKS) form. The H and l potentials which generate IDKS metrics are determined for the general vacuum ISKS metric and given explicitly for the Schwarzchild and Kerr families of metrics.
Fast Link Adaptation for MIMO-OFDM
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Kant, Shashi; Wehinger, Joachim;
2010-01-01
We investigate link-quality metrics (LQMs) based on raw bit-error-rate, effective signal-to-interference-plus-noise ratio, and mutual information (MI) for the purpose of fast link adaptation (LA) in communication systems employing orthogonal frequency-division multiplexing and multiple-input–mult......We investigate link-quality metrics (LQMs) based on raw bit-error-rate, effective signal-to-interference-plus-noise ratio, and mutual information (MI) for the purpose of fast link adaptation (LA) in communication systems employing orthogonal frequency-division multiplexing and multiple...
Enhancing the quality metric of protein microarray image
Institute of Scientific and Technical Information of China (English)
王立强; 倪旭翔; 陆祖康; 郑旭峰; 李映笙
2004-01-01
The novel method of improving the quality metric of protein microarray image presented in this paper reduces impulse noise by using an adaptive median filter that employs the switching scheme based on local statistics characters; and achieves the impulse detection by using the difference between the standard deviation of the pixels within the filter window and the current pixel of concern. It also uses a top-hat filter to correct the background variation. In order to decrease time consumption, the top-hat filter core is cross structure. The experimental results showed that, for a protein microarray image contaminated by impulse noise and with slow background variation, the new method can significantly increase the signal-to-noise ratio, correct the trends in the background, and enhance the flatness of the background and the consistency of the signal intensity.
Calculation and optimization of thresholds for sets of software metrics
Herbold, Steffen; Grabowski, Jens; Waack, Stephan
2011-01-01
In this article, we present a novel algorithmic method for the calculation of thresholds for a metric set. To this aim, machine learning and data mining techniques are utilized. We define a data-driven methodology that can be used for efficiency optimization of existing metric sets, for the simplification of complex classification models, and for the calculation of thresholds for a metric set in an environment where no metric set yet exists. The methodology is independent of the metric set an...
THE ROLE OF ARTICLE LEVEL METRICS IN SCIENTIFIC PUBLISHING
Vladimir TRAJKOVSKI
2016-01-01
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 ...
On 2-dimensional Kaehler metrics with one holomorphic isometry
Chimento, Samuele
2016-01-01
We show how to write any Kaehler metric of complex dimension 2 admitting a holomorphic isometry as a simple 1-real-function deformation of a Gibbons-Hawking metric. Hyper-Kaehler metrics with a tri-holomorphic isometry (Gibbons-Hawking metrics) or with a mono-holomorphic isometry are recovered for particular values of the additional function. The new general metric can be used as an Ansatz in several interesting physical problems.
Positive Semidefinite Metric Learning Using Boosting-like Algorithms
Shen, Chunhua; Kim, Junae; Wang, Lei; Hengel, Anton van den
2011-01-01
The success of many machine learning and pattern recognition methods relies heavily upon the identification of an appropriate distance metric on the input data. It is often beneficial to learn such a metric from the input training data, instead of using a default one such as the Euclidean distance. In this work, we propose a boosting-based technique, termed BoostMetric, for learning a quadratic Mahalanobis distance metric. Learning a valid Mahalanobis distance metric requires enforcing the co...
New Einstein Metrics in Dimension Five
Boyer, Charles P.; Galicki, Krzysztof
2001-01-01
The purpose of this note is to introduce a new method for proving the existence of Sasakian-Einstein metrics on certain simply connected odd dimensional manifolds. We then apply this method to prove the existence of new Sasakian-Einstein metrics on $\\scriptstyle{S^2\\times S^3}$ and on $\\scriptstyle{(S^2\\times S^3)# (S^2\\times S^3).}$ These give the first known examples of non-regular Sasakian-Einstein 5-manifolds. Our method involves describing the Sasakian-Einstein structures as links of cer...
Information metric and Euclidean Janus corresponence
Bak, Dongsu
2015-01-01
We consider the quantum information metric of a family of CFTs perturbed by an exactly marginal operator, which has the dual description of the Euclidean Janus geometries. We first review its two dimensional case dual to the three dimensional Janus geometry, which is recently proposed in arXiv:1507.07555. We generalize this correspondence to higher dimensions and get a precise agreement of the both sides. We also propose that the mixed-state information metric of the same family of CFTs is dual to the Euclidean version of the Janus time-dependent black hole geometry.
Information metric and Euclidean Janus correspondence
Dongsu Bak
2016-01-01
We consider the quantum information metric of a family of CFTs perturbed by an exactly marginal operator, which has the dual description of the Euclidean Janus geometries. We first clarify its two dimensional case dual to the three dimensional Janus geometry, which recently appeared in arXiv:1507.07555 [2] . We generalize this correspondence to higher dimensions and get a precise agreement between the both sides. We also show that the mixed-state information metric of the same family of CFTs ...
Information metric and Euclidean Janus correspondence
Bak, Dongsu
2016-05-01
We consider the quantum information metric of a family of CFTs perturbed by an exactly marginal operator, which has the dual description of the Euclidean Janus geometries. We first clarify its two dimensional case dual to the three dimensional Janus geometry, which recently appeared in arxiv:arXiv:1507.07555[2]. We generalize this correspondence to higher dimensions and get a precise agreement between the both sides. We also show that the mixed-state information metric of the same family of CFTs has a dual description in the Euclidean version of the Janus time-dependent black hole geometry.
Cohesion Metrics for Ontology Design and Application
Directory of Open Access Journals (Sweden)
Haining Yao
2005-01-01
Full Text Available Recently, domain specific ontology development has been driven by research on the Semantic Web. Ontologies have been suggested for use in many application areas targeted by the Semantic Web, such as dynamic web service composition and general web service matching. Fundamental characteristics of these ontologies must be determined in order to effectively make use of them: for example, Sirin, Hendler and Parsia have suggested that determining fundamental characteristics of ontologies is important for dynamic web service composition. Our research examines cohesion metrics for ontologies. The cohesion metrics examine the fundamental quality of cohesion as it relates to ontologies.
Spacetime metric from linear electrodynamics, 2
Hehl, F W; Rubilar, G F; Hehl, Friedrich W.; Obukhov, Yuri N.; Rubilar, Guillermo F.
1999-01-01
Following Kottler, É.Cartan, and van Dantzig, we formulate the Maxwell equations in a metric independent form in terms of the field strength $F=(E,B)$ and the excitation $H=({\\cal D}, {\\cal H})$. We assume a linear constitutive law between $H$ and $F$. First we split off a pseudo-scalar (axion) field from the constitutive tensor; its remaining 20 components can be used to define a duality operator $^#$ for 2-forms. If we enforce the constraint $^{##}=-1$, then we can derive of that the conformally invariant part of the {\\em metric} of spacetime.
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.
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.
Metric Conversion and the School Shop
Jackman, Arthur A.
1976-01-01
Cost of metric conversion in school shops is examined, and the author categories all the shops in the school and gives useful information on which shops are the easiest to convert, which are most complicated, where resistance is most likely to be met, and where conversion is most urgent. The math department is seen as catalyst. (Editor/HD)
Two-sorted metric temporal logics
Montanari, A.; Rijke, M. de
1995-01-01
Temporal logic has been successfully used for modeling and analyzing the behavior of reactive and concurrent systems.One shortcoming of (standard) temporal logic is that it is inadequate for real-time applications, because it only deals with qualitative timing properties.This is overcome by metric t
Validation metrics for turbulent plasma transport
Holland, C.
2016-06-01
Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.
Random shortest path metrics with applications
Engels, Christian; Manthey, Bodo; Raghavendra Rao, B.V.; Brieden, A.; Görgülü, Z.-K.; Krug, T.; Kropat, E.; Meyer-Nieberg, S.; Mihelcic, G.; Pickl, S.W.
2012-01-01
We consider random metric instances for optimization problems obtained as follows: Every edge of a complete graph gets a weight drawn independently at random. And then the length of an edge is the length of a shortest path with respect to these weights that connects its two endpoints. We prove that
Strong Ideal Convergence in Probabilistic Metric Spaces
Indian Academy of Sciences (India)
Celaleddin Şençimen; Serpil Pehlivan
2009-06-01
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 space and investigate some properties of these concepts.
Metrical musings on Littlewood and friends
DEFF Research Database (Denmark)
Haynes, A.; Jensen, Jonas Lindstrøm; Kristensen, Simon
We prove a metrical result on a family of conjectures related to the Littlewood conjecture, namely the original Littlewood conjecture, the mixed Littlewood conjecture of de Mathan and Teulié and a hybrid between a conjecture of Cassels and the Littlewood conjecture. It is shown that the set of nu...
Business model metrics: an open repository
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 per
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.
Product fixed points in ordered metric spaces
Turinici, Mihai
2011-01-01
All product fixed point results in ordered metric spaces based on linear contractive conditions are but a vectorial form of the fixed point statement due to Nieto and Rodriguez-Lopez [Order, 22 (2005), 223-239], under the lines in Matkowski [Bull. Acad. Pol. Sci. (Ser. Sci. Math. Astronom. Phys.), 21 (1973), 323-324].
Vestibular Influence on Auditory Metrical Interpretation
Phillips-Silver, J.; Trainor, L.J.
2008-01-01
When we move to music we feel the beat, and this feeling can shape the sound we hear. Previous studies have shown that when people listen to a metrically ambiguous rhythm pattern, moving the body on a certain beat-adults, by actively bouncing themselves in synchrony with the experimenter, and babies, by being bounced passively in the…
Assessing Software Quality Through Visualised Cohesion Metrics
Directory of Open Access Journals (Sweden)
Timothy Shih
2001-05-01
Full Text Available Cohesion is one of the most important factors for software quality as well as maintainability, reliability and reusability. Module cohesion is defined as a quality attribute that seeks for measuring the singleness of the purpose of a module. The module of poor quality can be a serious obstacle to the system quality. In order to design a good software quality, software managers and engineers need to introduce cohesion metrics to measure and produce desirable software. A highly cohesion software is thought to be a desirable constructing. In this paper, we propose a function-oriented cohesion metrics based on the analysis of live variables, live span and the visualization of processing element dependency graph. We give six typical cohesion examples to be measured as our experiments and justification. Therefore, a well-defined, well-normalized, well-visualized and well-experimented cohesion metrics is proposed to indicate and thus enhance software cohesion strength. Furthermore, this cohesion metrics can be easily incorporated with software CASE tool to help software engineers to improve software quality.
Metric on state space of Markov chain
Rozinas, M. R.
2010-01-01
We consider finite irreducible Markov chains. It was shown that mean hitting time from one state to another satisfies the triangle inequality. Hence, sum of mean hitting time between couple of states in both directions is a metric on the space of states.
Note: why is the metric invertible?
Energy Technology Data Exchange (ETDEWEB)
Deser, S [Department of Physics, Brandeis University, Waltham, MA 02454 (United States); Lauritsen Laboratory, California Institute of Technology, Pasadena, CA 91125 (United States)
2006-07-07
We raise, and provide an (unsatisfactory) answer to the title's question: why, unlike all other fields, does the gravitational 'metric' variable not have zero vacuum? After formulating the question, but without begging it, we exhibit additions to the conventional action that express the existence of the inverse through a field equation. (comments, replies and notes)
Note: why is the metric invertible?
Deser, S.
2006-01-01
We raise, and provide an (unsatisfactory) answer to the title's question: why, unlike all other fields, does the gravitational 'metric' variable not have zero vacuum? After formulating the question, but without begging it, we exhibit additions to the conventional action that express the existence of the inverse through a field equation.
Thermodynamical properties of metric fluctuations during inflation
Bellini, M
2001-01-01
I study a thermodynamical approach to scalar metric perturbations during the inflationary stage. In the power-law expanding universe here studied, I find a negative heat capacity as a manifestation of superexponential growing for the number of states in super Hubble scales. The power spectrum depends on the Gibbons-Hawking and Hagedorn temperatures.
Outsourced similarity search on metric data assets
DEFF Research Database (Denmark)
Yiu, Man Lung; Assent, Ira; Jensen, Christian Søndergaard;
2012-01-01
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...
A new universal colour image fidelity metric
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 fi
Classifying climate change adaptation frameworks
Armstrong, Jennifer
2014-05-01
Complex socio-ecological demographics are factors that must be considered when addressing adaptation to the potential effects of climate change. As such, a suite of deployable climate change adaptation frameworks is necessary. Multiple frameworks that are required to communicate the risks of climate change and facilitate adaptation. Three principal adaptation frameworks have emerged from the literature; Scenario - Led (SL), Vulnerability - Led (VL) and Decision - Centric (DC). This study aims to identify to what extent these adaptation frameworks; either, planned or deployed are used in a neighbourhood vulnerable to climate change. This work presents a criterion that may be used as a tool for identifying the hallmarks of adaptation frameworks and thus enabling categorisation of projects. The study focussed on the coastal zone surrounding the Sizewell nuclear power plant in Suffolk in the UK. An online survey was conducted identifying climate change adaptation projects operating in the study area. This inventory was analysed to identify the hallmarks of each adaptation project; Levels of dependency on climate model information, Metrics/units of analysis utilised, Level of demographic knowledge, Level of stakeholder engagement, Adaptation implementation strategies and Scale of adaptation implementation. The study found that climate change adaptation projects could be categorised, based on the hallmarks identified, in accordance with the published literature. As such, the criterion may be used to establish the matrix of adaptation frameworks present in a given area. A comprehensive summary of the nature of adaptation frameworks in operation in a locality provides a platform for further comparative analysis. Such analysis, enabled by the criterion, may aid the selection of appropriate frameworks enhancing the efficacy of climate change adaptation.
Research on SVM KNN Classification Algorithm Based on Hadoop Platform%基于Hadoop平台的SVM KNN分类算法的研究
Institute of Scientific and Technical Information of China (English)
李正杰; 黄刚
2016-01-01
数据的变革带来了前所未有的发展，对丰富且复杂的结构化、半结构化或者是非结构化数据的监测、分析、采集、存储以及应用，已经成为了数据信息时代发展的主流，分类和处理海量数据包含的信息，需要有更好的解决方法。传统的数据挖掘分类方式显然已经不能满足需求，面对这些问题，这里对数据挖掘的一些分类算法进行分析和改进，对算法进行结合，提出了改进的SVM KNN分类算法。在这个基础上，利用Hadoop云计算平台，将研究后的分类算法在MapReduce模型中进行并行化应用，使改进后的算法能够适用于大数据的处理。最后用数据集对算法进行实验验证，通过对比传统的SVM分类算法，结果表明改进后的算法达到了高效、快速、准确、低成本的要求，可以有效地进行大数据分类工作。%The reform of data has brought the unprecedented development,to monitor,analyze,collect,store and apply to the rich and complex structured,semi-structured or unstructured data has become the mainstream of the development of the information age. To classi-fy and deal with the information contained in mass data,it’ s needed to have a better solution. The traditional data mining classification method cannot meet the demand any longer. To face these problems,it analyzes and improves the classification algorithm in data mining in this paper. Combined with the algorithms,an improved SVM KNN classification algorithm is proposed. Then on this basis,by utilizing Hadoop cloud computing platform,the new classification algorithm is put into MapReduce model for parallelization application,so the im-proved algorithm can be applied to large data processing. Finally,data set is used to conduct experimental verification on the algorithm. By comparing with traditional SVM classification algorithm,the results show that the improved algorithm has become more efficient,fast, accurate
Directory of Open Access Journals (Sweden)
Joseph Chrol-Cannon
Full Text Available Reservoir computing provides a simpler paradigm of training recurrent networks by initialising and adapting the recurrent connections separately to a supervised linear readout. This creates a problem, though. As the recurrent weights and topology are now separated from adapting to the task, there is a burden on the reservoir designer to construct an effective network that happens to produce state vectors that can be mapped linearly into the desired outputs. Guidance in forming a reservoir can be through the use of some established metrics which link a number of theoretical properties of the reservoir computing paradigm to quantitative measures that can be used to evaluate the effectiveness of a given design. We provide a comprehensive empirical study of four metrics; class separation, kernel quality, Lyapunov's exponent and spectral radius. These metrics are each compared over a number of repeated runs, for different reservoir computing set-ups that include three types of network topology and three mechanisms of weight adaptation through synaptic plasticity. Each combination of these methods is tested on two time-series classification problems. We find that the two metrics that correlate most strongly with the classification performance are Lyapunov's exponent and kernel quality. It is also evident in the comparisons that these two metrics both measure a similar property of the reservoir dynamics. We also find that class separation and spectral radius are both less reliable and less effective in predicting performance.
Chrol-Cannon, Joseph; Jin, Yaochu
2014-01-01
Reservoir computing provides a simpler paradigm of training recurrent networks by initialising and adapting the recurrent connections separately to a supervised linear readout. This creates a problem, though. As the recurrent weights and topology are now separated from adapting to the task, there is a burden on the reservoir designer to construct an effective network that happens to produce state vectors that can be mapped linearly into the desired outputs. Guidance in forming a reservoir can be through the use of some established metrics which link a number of theoretical properties of the reservoir computing paradigm to quantitative measures that can be used to evaluate the effectiveness of a given design. We provide a comprehensive empirical study of four metrics; class separation, kernel quality, Lyapunov's exponent and spectral radius. These metrics are each compared over a number of repeated runs, for different reservoir computing set-ups that include three types of network topology and three mechanisms of weight adaptation through synaptic plasticity. Each combination of these methods is tested on two time-series classification problems. We find that the two metrics that correlate most strongly with the classification performance are Lyapunov's exponent and kernel quality. It is also evident in the comparisons that these two metrics both measure a similar property of the reservoir dynamics. We also find that class separation and spectral radius are both less reliable and less effective in predicting performance.
Directory of Open Access Journals (Sweden)
Santosh Kumar S
2011-10-01
Full Text Available A mobile ad hoc network is collection of self configuring and adaption of wireless link between communicating devices (mobile devices to form an arbitrary topology and multihop wireless connectivity without the use of existing infrastructure. It requires efficient dynamic routing protocol to determine the routes subsequent to a set of rules that enables two or more devices to communicate with each others. This paper basically classifies and evaluates the mobility metrics into two categories- direct mobility metrics and derived mobility metrics. These two mobility metrics has been used to measure different mobility models, this paper considers some of mobility models i.e Random Waypoint Model, Reference Point Group Mobility Model, Random Direction Mobility Model, Random Walk Mobility Model, Probabilistic Random Walk, Gauss Markov, Column Mobility Model, Nomadic Community Mobility Model and Manhattan Grid Model.
Measuring success : metrics that link supply chain management to aircraft readiness
McDoniel, Patrick S.; Balestreri, William G.
2002-01-01
This thesis evaluates and analyzes current strategic management planning methods that develop performance metrics linking supply chain management to aircraft readiness. Our primary focus is the Marine Aviation Logistics Squadron. Utilizing the Logistics Management Institute's DoD Supply Chain Implementation Guide and adapted SCOR model, we applied the six step process for developing a strategic logistics management plan for implementing supply chain management for use at the MALS, and subsequ...
The metric on field space, functional renormalization, and metric-torsion quantum gravity
Reuter, Martin; Schollmeyer, Gregor M.
2016-04-01
Searching for new non-perturbatively renormalizable quantum gravity theories, functional renormalization group (RG) flows are studied on a theory space of action functionals depending on the metric and the torsion tensor, the latter parameterized by three irreducible component fields. A detailed comparison with Quantum Einstein-Cartan Gravity (QECG), Quantum Einstein Gravity (QEG), and "tetrad-only" gravity, all based on different theory spaces, is performed. It is demonstrated that, over a generic theory space, the construction of a functional RG equation (FRGE) for the effective average action requires the specification of a metric on the infinite-dimensional field manifold as an additional input. A modified FRGE is obtained if this metric is scale-dependent, as it happens in the metric-torsion system considered.
A Possible Fluid Source for a Kerr-like Metric
Frutos-Alfaro, Francisco; Araya-Arguedas, Miguel
2014-01-01
A new Kerr-like metric with quadrupole moment is obtained by means of perturbing the Kerr spacetime. The form of this new metric is simple as the Kerr metric. By comparison with the exterior Hartle-Thorne metric, it is shown that it could be matched to an interior solution. Moreover, a description of a possible matching of this new metric with an interior fluid source using the Haggag method is presented. This metric may represent the spacetime of a real astrophysical object.
Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper
2015-01-01
Adaptive LightingAdaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled i...
Stanic, Biljana
2015-01-01
Software fault prediction (SFP) has an important role in the process of improving software product quality by identifying fault-prone modules. Constructing quality models includes a usage of metrics that describe real world entities defined by numbers or attributes. Examining the nature of machine learning (ML), researchers proposed its algorithms as suitable for fault prediction. Moreover, information that software metrics contain will be used as statistical data necessary to build models fo...
Biomechanical metrics of aesthetic perception in dance.
Bronner, Shaw; Shippen, James
2015-12-01
The brain may be tuned to evaluate aesthetic perception through perceptual chunking when we observe the grace of the dancer. We modelled biomechanical metrics to explain biological determinants of aesthetic perception in dance. Eighteen expert (EXP) and intermediate (INT) dancers performed développé arabesque in three conditions: (1) slow tempo, (2) slow tempo with relevé, and (3) fast tempo. To compare biomechanical metrics of kinematic data, we calculated intra-excursion variability, principal component analysis (PCA), and dimensionless jerk for the gesture limb. Observers, all trained dancers, viewed motion capture stick figures of the trials and ranked each for aesthetic (1) proficiency and (2) movement smoothness. Statistical analyses included group by condition repeated-measures ANOVA for metric data; Mann-Whitney U rank and Friedman's rank tests for nonparametric rank data; Spearman's rho correlations to compare aesthetic rankings and metrics; and linear regression to examine which metric best quantified observers' aesthetic rankings, p < 0.05. The goodness of fit of the proposed models was determined using Akaike information criteria. Aesthetic proficiency and smoothness rankings of the dance movements revealed differences between groups and condition, p < 0.0001. EXP dancers were rated more aesthetically proficient than INT dancers. The slow and fast conditions were judged more aesthetically proficient than slow with relevé (p < 0.0001). Of the metrics, PCA best captured the differences due to group and condition. PCA also provided the most parsimonious model to explain aesthetic proficiency and smoothness rankings. By permitting organization of large data sets into simpler groupings, PCA may mirror the phenomenon of chunking in which the brain combines sensory motor elements into integrated units of behaviour. In this representation, the chunk of information which is remembered, and to which the observer reacts, is the elemental mode shape of
A Novel Performance Metric for Building an Optimized Classifier
Directory of Open Access Journals (Sweden)
Mohammad Hossin
2011-01-01
Full Text Available Problem statement: Typically, the accuracy metric is often applied for optimizing the heuristic or stochastic classification models. However, the use of accuracy metric might lead the searching process to the sub-optimal solutions due to its less discriminating values and it is also not robust to the changes of class distribution. Approach: To solve these detrimental effects, we propose a novel performance metric which combines the beneficial properties of accuracy metric with the extended recall and precision metrics. We call this new performance metric as Optimized Accuracy with Recall-Precision (OARP. Results: In this study, we demonstrate that the OARP metric is theoretically better than the accuracy metric using four generated examples. We also demonstrate empirically that a naïve stochastic classification algorithm, which is Monte Carlo Sampling (MCS algorithm trained with the OARP metric, is able to obtain better predictive results than the one trained with the conventional accuracy metric. Additionally, the t-test analysis also shows a clear advantage of the MCS model trained with the OARP metric over the accuracy metric alone for all binary data sets. Conclusion: The experiments have proved that the OARP metric leads stochastic classifiers such as the MCS towards a better training model, which in turn will improve the predictive results of any heuristic or stochastic classification models.
On the Stochastic Rank of Metric Functions
Balov, Nikolay H
2008-01-01
For a class of integral operators with kernels metric functions on manifold we find some necessary and sufficient conditions to have finite rank. The problem we pose has a stochastic nature and boils down to the following alternative question. For a random sample of discrete points, what will be the probability the symmetric matrix of pairwise distances to have full rank? When the metric is an analytic function, the question finds full and satisfactory answer. As an important application, we consider a class of tensor systems of equations formulating the problem of recovering a manifold distribution from its covariance field and solve this problem for representing manifolds such as Euclidean space and unit sphere.
Machine Learning for ATLAS DDM Network Metrics
Lassnig, Mario; The ATLAS collaboration
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.
Obtaining the spacetime metric from cosmological observations
Lu, Teresa Hui-Ching
2007-01-01
Recent galaxy redshift surveys have brought in a large amount of accurate cosmological data out to redshift 0.3, and future surveys are expected to achieve a high degree of completeness out to a redshift exceeding 1. Consequently, a numerical programme for determining the metric of the universe from observational data will soon become practical; and thereby realise the ultimate application of Einstein's equations. Apart from detailing the cosmic geometry, this would allow us to verify and quantify homogeneity, rather than assuming it, as has been necessary up to now, and to do that on a metric level, and not merely at the mass distribution level. This paper is the beginning of a project aimed at such a numerical implementation. The primary observational data from our past light cone consists of galaxy redshifts, apparent luminosities, angular diameters and number densities, together with source evolution functions, absolute luminosities, true diameters and masses of sources. Here we start with the simplest ca...
Metrics for measuring distances in configuration spaces
Energy Technology Data Exchange (ETDEWEB)
Sadeghi, Ali, E-mail: ali.sadeghi@unibas.ch; Ghasemi, S. Alireza; Schaefer, Bastian; Mohr, Stephan; Goedecker, Stefan [Department of Physics, Universität Basel, Klingelbergstr. 82, 4056 Basel (Switzerland); Lill, Markus A. [Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana 47907 (United States)
2013-11-14
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.
Metrics for measuring distances in configuration spaces.
Sadeghi, Ali; Ghasemi, S Alireza; Schaefer, Bastian; Mohr, Stephan; Lill, Markus A; Goedecker, Stefan
2013-11-14
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. PMID:24320265
Metric for Early Measurement of Software Complexity
Directory of Open Access Journals (Sweden)
Ghazal Keshavarz,
2011-06-01
Full Text Available Software quality depends on several factors such as on time delivery; within budget and fulfilling user's needs. Complexity is one of the most important factors that may affect the quality. Therefore, measuring and controlling the complexity result in improving the quality. So far, most of the researches have tried to identify and measure the complexity in design and code phase. However, whenwe have the code or design for software, it is too late to control complexity. In this article, with emphasis on Requirement Engineering process, we analyze the causes of software complexity, particularly in the first phase of software development, and propose a requirement based metric. This metric enables a software engineer to measure the complexity before actual design and implementation and choosestrategies that are appropriate to the software complexity degree, thus saving on cost and human resource wastage and, more importantly, leading to lower maintenance costs.
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.
Data Complexity Metrics for XML Web Services
Directory of Open Access Journals (Sweden)
MISRA, S.
2009-06-01
Full Text Available Web services that are based on eXtensible Markup Language (XML technologies enable integration of diverse IT processes and systems and have been gaining extraordinary acceptance from the basic to the most complicated business and scientific processes. The maintainability is one of the important factors that affect the quality of the Web services that can be seen a kind of software project. The effective management of any type of software projects requires modelling, measurement, and quantification. This study presents a metric for the assessment of the quality of the Web services in terms of its maintainability. For this purpose we proposed a data complexity metric that can be evaluated by analyzing WSDL (Web Service Description Language documents used for describing Web services.
The Metric Dimension of Regular Bipartite Graphs
Saputro, S W; Salman, A N M; Suprijanto, D; Baca, And M
2011-01-01
A set of vertices $W$ resolves a graph $G$ if every vertex is uniquely determined by its vector of distances to the vertices in $W$. A metric dimension of $G$ is the minimum cardinality of a resolving set of $G$. A bipartite graph G(n,n) is a graph whose vertex set $V$ can be partitioned into two subsets $V_1$ and $V_2,$ with $|V_1|=|V_2|=n,$ such that every edge of $G$ joins $V_1$ and $V_2$. The graph $G$ is called $k$-regular if every vertex of $G$ is adjacent to $k$ other vertices. In this paper, we determine the metric dimension of $k$-regular bipartite graphs G(n,n) where $k=n-1$ or $k=n-2$.
A Taxonomy of Metrics for Hosted Databases
Directory of Open Access Journals (Sweden)
Jordan Shropshire
2006-04-01
Full Text Available The past three years has seen exponential growth in the number of organizations who have elected to entrust core information technology functions to application service providers. Of particular interest is the outsourcing of critical systems such as corporate databases. Major banks and financial service firms are contracting with third party organizations, sometimes overseas, for their database needs. These sophisticated contracts require careful supervision by both parties. Due to the complexities of web- based applications and the complicated nature of databases, an entire class of software suites has been developed to measure the quality of service the database is providing. This article investigates the performance metrics which have evolved to satisfy this need and describes a taxonomy of performance metrics for hosted databases.
New Quality Metrics for Web Search Results
Metaxas, Panagiotis Takis; Ivanova, Lilia; Mustafaraj, Eni
Web search results enjoy an increasing importance in our daily lives. But what can be said about their quality, especially when querying a controversial issue? The traditional information retrieval metrics of precision and recall do not provide much insight in the case of web information retrieval. In this paper we examine new ways of evaluating quality in search results: coverage and independence. We give examples on how these new metrics can be calculated and what their values reveal regarding the two major search engines, Google and Yahoo. We have found evidence of low coverage for commercial and medical controversial queries, and high coverage for a political query that is highly contested. Given the fact that search engines are unwilling to tune their search results manually, except in a few cases that have become the source of bad publicity, low coverage and independence reveal the efforts of dedicated groups to manipulate the search results.
A universal metric for ferroic energy materials
Yibole, Hargen; Zhang, Lian
2016-01-01
After almost 20 years of intensive research on magnetocaloric effects near room temperature, magnetic refrigeration with first-order magnetocaloric materials has come close to real-life applications. Many materials have been discussed as potential candidates to be used in multicaloric devices. However, phase transitions in ferroic materials are often hysteretic and a metric is needed to estimate the detrimental effects of this hysteresis. We propose the coefficient of refrigerant performance, which compares the net work in a reversible cycle with the positive work on the refrigerant, as a universal metric for ferroic materials. Here, we concentrate on examples from magnetocaloric materials and only consider one barocaloric experiment. This is mainly due to lack of data on electrocaloric materials. It appears that adjusting the field-induced transitions and the hysteresis effects can minimize the losses in first-order materials. This article is part of the themed issue ‘Taking the temperature of phase transitions in cool materials’. PMID:27402924
A universal metric for ferroic energy materials.
Brück, Ekkes; Yibole, Hargen; Zhang, Lian
2016-08-13
After almost 20 years of intensive research on magnetocaloric effects near room temperature, magnetic refrigeration with first-order magnetocaloric materials has come close to real-life applications. Many materials have been discussed as potential candidates to be used in multicaloric devices. However, phase transitions in ferroic materials are often hysteretic and a metric is needed to estimate the detrimental effects of this hysteresis. We propose the coefficient of refrigerant performance, which compares the net work in a reversible cycle with the positive work on the refrigerant, as a universal metric for ferroic materials. Here, we concentrate on examples from magnetocaloric materials and only consider one barocaloric experiment. This is mainly due to lack of data on electrocaloric materials. It appears that adjusting the field-induced transitions and the hysteresis effects can minimize the losses in first-order materials.This article is part of the themed issue 'Taking the temperature of phase transitions in cool materials'. PMID:27402924
Asymptotic properties of the C-Metric
Sladek, Pavel
2010-01-01
The aim of this article is to analyze the asymptotic properties of the C-metric, using a general method specified in work of Tafel and coworkers, [1], [2], [3]. By finding an appropriate conformal factor $\\Omega$, it allows the investigation of the asymptotic properties of a given asymptotically flat spacetime. The news function and Bondi mass aspect are computed, their general properties are analyzed, as well as the small mass, small acceleration, small and large Bondi time limits.
Towards Perceptually Driven Segmentation Evaluation Metrics
Drelie Gelasca, E.; Ebrahimi, T.; Farias, M; Carli, M; Mitra, S.
2004-01-01
To be reliable, an automatic segmentation evaluation metric has to be validated by subjective tests. In this paper, a formal protocol for subjective tests for segmentation quality assessment is presented. The most common artifacts produced by segmentation algorithms are identified and an extensive analysis of their effects on the perceived quality is performed. A psychophysical experiment was performed to assess the quality of video with segmentation errors. The results show how an objective ...
Generalized Symmetric Divergence Measures and Metric Spaces
da Costa, G A T F
2011-01-01
Recently, Taneja studied two one parameter generalizations of J-divergence, Jensen-Shannon divergence and Arithmetic-Geometric divergence. These two generalizations in particular contain measures like: Hellinger discrimination, symmetric chi-square divergence, and triangular discrimination. These measures are well known in the literature of Statistics and Information theory. In this paper our aim is to prove metric space properties for square root of these two symmetric generalized divergence measures.
Anisotropic rectangular metric for polygonal surface remeshing
Pellenard, Bertrand
2013-06-18
We propose a new method for anisotropic polygonal surface remeshing. Our algorithm takes as input a surface triangle mesh. An anisotropic rectangular metric, defined at each triangle facet of the input mesh, is derived from both a user-specified normal-based tolerance error and the requirement to favor rectangle-shaped polygons. Our algorithm uses a greedy optimization procedure that adds, deletes and relocates generators so as to match two criteria related to partitioning and conformity.
Rainbow metric from quantum gravity: anisotropic cosmology
Assanioussi, Mehdi; Dapor, Andrea
2016-01-01
In this paper we present a construction of effective cosmological models which describe the propagation of a massive quantum scalar field on a quantum anisotropic cosmological spacetime. Each obtained effective model is represented by a rainbow metric in which particles of distinct momenta propagate on different classical geometries. Our analysis shows that upon certain assumptions and conditions on the parameters determining such anisotropic models, we surprisingly obtain a unique deformatio...
Coercive Inequalities on Metric Measure Spaces
Hebisch, W.; Zegarlinski, B.
2009-01-01
We study coercive inequalities on finite dimensional metric spaces with probability measures which do not have volume doubling property. This class of inequalities includes Poincar\\'e and Log-Sobolev inequality. Our main result is proof of Log-Sobolev inequality on Heisenberg group equipped with either heat kernel measure or "gaussian" density build from optimal control distance. As intermediate results we prove so called U-bounds.
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.
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.
Riemann surface with almost positive definite metric
Institute of Scientific and Technical Information of China (English)
CHEN Zhi-guo
2005-01-01
In this paper, we consider and resolve a geometric problem by using μ(z)-homeomorphic theory, which is the generalization of quasiconforrnal mappings. A sufficient condition is given such that a C1-two-real-dimensional connected orientable manifold with almost positive definite metric can be made into a Riemann surface by the method of isothermal coordinates. The result obtained here is actually a generalization of Chern's work in 1955.
Structural complexity metrics for UML class diagrams
Institute of Scientific and Technical Information of China (English)
KONG Qing-yan; LUN Li-jun; WANG Yi-he; DING Xue-mei
2008-01-01
In order to evaluate the structural complexity of class diagrams systematically and deeply, a new guiding framework of structural complexity is presented. An index system of structural complexity for class dia-grams is given. This article discusses the formal description of class diagrams, and presents the method of for-mally structural complexity metrics for class diagrams from associations, dependencies, aggregations, generali-zations and so on. An applicable example proves the feasibility of the presented method.
The Planck Vacuum and the Schwarzschild Metrics
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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.
Network Delay Inference from Additive Metrics
Bhamidi, Shankar; Rajagopal, Ram; Roch, Sebastien
2006-01-01
We demonstrate the use of computational phylogenetic techniques to solve a central problem in inferential network monitoring. More precisely, we design a novel algorithm for multicast-based delay inference, i.e. the problem of reconstructing the topology and delay characteristics of a network from end-to-end delay measurements on network paths. Our inference algorithm is based on additive metric techniques widely used in phylogenetics. It runs in polynomial time and requires a sample of size ...
Teleparallel Gravitational Energy in the Gamma Metric
Salti, M
2006-01-01
The Moller energy(due to matter and fields including gravity) distribution of the gamma metric is studied in tele-parallel gravity. The result is the same as those obtained in general relativity by Virbhadra in the Weinberg complex and Yang-Radincshi in the Moller definition. Our result is also independent of the three teleparallel dimensionless coupling constants, which means that it is valid not only in the teleparallel equivalent of general relativity, but also in any teleparallel model.
Spacetime metric from linear electrodynamics. III
Rubilar, G F; Hehl, F W; Rubilar, Guillermo F.; Obukhov, Yuri N.; Hehl, Friedrich W.
2001-01-01
We extend our previous results on the wave propagation in a spacetime with a linear electromagnetic spacetime relation to the most general case in which the corresponding constitutive tensor is asymmetric. We find the corresponding Fresnel equation governing the geometry of light rays and show that it is always quartic in the wave covectors. The conditions for the wave covectors to define a single or a double (birefringence) light-cone structure are discussed and the corresponding conformal metric is constructed.
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.
Design Metrics Which Predict Source Code Quality
Hartson, H.Rex; Smith, Eric C.; Henry, Sallie M.; Selig, Calvin
1987-01-01
Since the inception of software engineering, the major goal has been to control the development and maintenance of reliable software. To this end, many different design methodologies have been presented as a means to improve software quality through semantic clarity and syntactic accuracy during the specification and design phases of the software life cycle. On the other end of the life cycle, software quality metrics have been proposed to supply quantitative measures of the resultant softwar...
FABASOFT BEST PRACTICES AND TEST METRICS MODEL
Nadica Hrgarek
2007-01-01
Software companies have to face serious problems about how to measure the progress of test activities and quality of software products in order to estimate test completion criteria, and if the shipment milestone will be reached on time. Measurement is a key activity in testing life cycle and requires established, managed and well documented test process, defined software quality attributes, quantitative measures, and using of test management and bug tracking tools. Test metrics are a subset o...
Dehn Filling and Einstein Metrics in Higher Dimensions
Anderson, Michael T.
2006-01-01
We prove that many features of Thurston's Dehn surgery theory for hyperbolic 3-manifolds generalize to Einstein metrics in any dimension. In particular, this gives large, infinite families of new Einstein metrics on compact manifolds.
BANACH CONTRACTION PRINCIPLE ON CONE RECTANGULAR METRIC SPACES
Directory of Open Access Journals (Sweden)
Ismat Beg
2009-08-01
Full Text Available We introduce the notion of cone rectangular metric space and prove {sc Banach} contraction mapping principle in cone rectangular metric space setting. Our result extends recent known results.
How to evaluate objective video quality metrics reliably
DEFF Research Database (Denmark)
Korhonen, Jari; Burini, Nino; You, Junyong;
2012-01-01
The typical procedure for evaluating the performance of different objective quality metrics and indices involves comparisons between subjective quality ratings and the quality indices obtained using the objective metrics in question on the known video sequences. Several correlation indicators can...
Regular black hole metrics and the weak energy condition
Energy Technology Data Exchange (ETDEWEB)
Balart, Leonardo, E-mail: leonardo.balart@ufrontera.cl [I.C.B. – Institut Carnot de Bourgogne, UMR 5209, CNRS, Faculté des Sciences Mirande, Université de Bourgogne, 9 Avenue Alain Savary, BP 47870, 21078 Dijon Cedex (France); Departamento de Ciencias Físicas, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Casilla 54-D, Temuco (Chile); Vagenas, Elias C., E-mail: elias.vagenas@ku.edu.kw [Theoretical Physics Group, Department of Physics, Kuwait University, P.O. Box 5969, Safat 13060 (Kuwait)
2014-03-07
In this work we construct a family of spherically symmetric, static, charged regular black hole metrics in the context of Einstein-nonlinear electrodynamics theory. The construction of the charged regular black hole metrics is based on three requirements: (a) the weak energy condition should be satisfied, (b) the energy–momentum tensor should have the symmetry T{sub 0}{sup 0}=T{sub 1}{sup 1}, and (c) these metrics have to asymptotically behave as the Reissner–Nordström black hole metric. In addition, these charged regular black hole metrics depend on two parameters which for specific values yield regular black hole metrics that already exist in the literature. Furthermore, by relaxing the third requirement, we construct more general regular black hole metrics which do not behave asymptotically as a Reissner–Nordström black hole metric.
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.
Multi-Armed Bandits in Metric Spaces
Kleinberg, Robert; Upfal, Eli
2008-01-01
In a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of trials so as to maximize the total payoff of the chosen strategies. While the performance of bandit algorithms with a small finite strategy set is quite well understood, bandit problems with large strategy sets are still a topic of very active investigation, motivated by practical applications such as online auctions and web advertisement. The goal of such research is to identify broad and natural classes of strategy sets and payoff functions which enable the design of efficient solutions. In this work we study a very general setting for the multi-armed bandit problem in which the strategies form a metric space, and the payoff function satisfies a Lipschitz condition with respect to the metric. We refer to this problem as the "Lipschitz MAB problem". We present a complete solution for the multi-armed problem in this setting. That is, for every metric space (L,X) we define an isometry invariant which bounds f...
An information theoretic approach for privacy metrics
Directory of Open Access Journals (Sweden)
Michele Bezzi
2010-12-01
Full Text Available Organizations often need to release microdata without revealing sensitive information. To this scope, data are anonymized and, to assess the quality of the process, various privacy metrics have been proposed, such as k-anonymity, l-diversity, and t-closeness. These metrics are able to capture different aspects of the disclosure risk, imposing minimal requirements on the association of an individual with the sensitive attributes. If we want to combine them in a optimization problem, we need a common framework able to express all these privacy conditions. Previous studies proposed the notion of mutual information to measure the different kinds of disclosure risks and the utility, but, since mutual information is an average quantity, it is not able to completely express these conditions on single records. We introduce here the notion of one-symbol information (i.e., the contribution to mutual information by a single record that allows to express and compare the disclosure risk metrics. In addition, we obtain a relation between the risk values t and l, which can be used for parameter setting. We also show, by numerical experiments, how l-diversity and t-closeness can be represented in terms of two different, but equally acceptable, conditions on the information gain..
Metric-torsion preheating: cosmic dynamo mechanism?
de Andrade, L C Garcia
2014-01-01
Earlier Bassett et al [Phys Rev D 63 (2001) 023506] investigated the amplification of large scale magnetic fields during preheating and inflation in several different models. They argued that in the presence of conductivity resonance effect is weakened. From a dynamo equation in spacetimes endowed with torsion recently derived by Garcia de Andrade [Phys Lett B 711: 143 (2012)] it is shown that a in a universe with pure torsion in Minkowski spacetime the cosmological magnetic field is enhanced by ohmic or non-conductivity effect, which shows that the metric-torsion effects is worth while of being studied. In this paper we investigated the metric-torsion preheating perturbation, which leads to the seed cosmological magnetic field in the universe with torsion is of the order of $B_{seed}\\sim{10^{-37}Gauss}$ which is several orders of magnitude weaker than the decoupling value obtained from pure metric preheating of $10^{-15}Gauss$. Despite of the weakness of the magnetic field this seed field may seed the galact...
Models, Metrics, and Measurement in Developmental Psychology
Directory of Open Access Journals (Sweden)
Zachary Stein
2009-06-01
Full Text Available Developmental psychology is currently used to measure psychologicalphenomena and by some, to re-design communities. While we generally support theseuses, we are concerned about quality control standards guiding the production of usableknowledge in the discipline. In order to address these issues precisely, we provide anoverview of the discipline's various facets. We distinguish between developmentalmodels and developmental metrics and relate each to different types of quality-controldevices. In our view, models are either explanatory or descriptive, and their quality isevaluated in terms of specific types of disciplinary discourse. Metrics are eithercalibrated measures or soft measures, and their quality is evaluated in terms of specificpsychometric parameters. Following a discussion on how developmentalists makemetrics, and on a variety of metrics that have been made, we discuss the two keypsychometric quality-control parameters, validity and reliability. This sets the stage for alimited and exploratory literature review concerning the quality of a set of existingmetrics. We reveal a conspicuous lack of psychometric rigor on the part of some of themost popular developmental approaches and invite remedies for this situation.
Ghost free massive gravity with singular reference metrics
Zhang, Hongsheng; Li, Xin-Zhou
2016-06-01
An auxiliary metric (reference metric) is inevitable in massive gravity theory. In the scenario of the gauge/gravity duality, massive gravity with a singular reference metric is used to study momentum dissipation, which describes the electric and heat conductivity for normal conductors. We demonstrate in detail that the de Rham-Gabadadze-Tolley (dRGT) massive gravity with a singular reference metric is ghost free.
What can article-level metrics do for you?
Directory of Open Access Journals (Sweden)
Martin Fenner
2013-10-01
Full Text Available 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.
Exposing Useful Trends in Metric Data Through Group Level Analysis
Kafura, Dennis G.; Canning, James
1985-01-01
In this paper the results of experiments which applied both structure and code metrics to three large scale systems are presented. This metric research is distinct in that trends in the data are uncovered through the use of group level analysis. Components are partitioned into groups based on their various metric values and on observed measures of complexity (ie. errors, coding time). Crosstabulation data is given which indicates that trends between some of the metrics ...
The Non-Metricity Formulation of General Relativity
Mol, Igor
2014-01-01
After recalling the differential geometry of non-metric connections in the formalism of differential forms, we introduce the idea of a Non-Metricity (NM) connection, whose connection $1$--forms coincides with the non-metricity $1$--forms for a class of cobase fields. Then we formulate a theory of gravitation (equivalent to General Relativity (GR)) which admits a geometrical interpretation in a flat torsionless space where the gravitational field is completely manifest in the non-metricity of ...
Kahler-Einstein metrics, Bergman metrics, and higher alpha-invariants
Macbeth, Heather
The question of the existence of Kahler-Einstein metrics on a Kahler manifold M has been a subject of study for decades. The Kahler manifolds on which this question may be studied divide naturally into three types. For two of these types the question was long ago settled by Yau and Aubin. For the third type, Fano manifolds, the question is (despite great recent progress) open for many individual manifolds. In the first part of this thesis we define algebraic invariants Bm,k(M) of a Fano manifold M, which codify certain properties of M 's Bergman metrics. We prove a criterion (Theorem 1.1.1) in terms of these invariants Bm,k( M) for the existence of a Kahler-Einstein metric on M. The proof of Theorem 1.1.1 relies on Szekelyhidi's deep recent partial C0-estimate, and on a new family of estimates for Fano manifolds. We furthermore introduce a very general hypothesis on Bergman metrics, Conjecture 6.1.2, offering some partial results (Section 6.3) in evidence. Modulo this conjecture, we prove a variation of Theorem 1.1.1, which gives a criterion for the existence of a Kahler-Einstein metric on M in terms of the well-known alpha-invariants, alpha m,k(M). This result extends a theorem of Tian. The second part of this thesis concerns Riemannian manifolds more generally. We give a characterization (Theorem 1.2.1) of conformal classes realizing a compact manifold's Yamabe invariant. This characterization is the analogue of an observation of Nadirashvili for metrics realizing the maximal first eigenvalue, and of Fraser and Schoen for metrics realizing the maximal first Steklov eigenvalue.
FIXED POINT RESULTS ON METRIC-TYPE SPACES
Institute of Scientific and Technical Information of China (English)
Monica COSENTINO; Peyman SALIMI; Pasquale VETRO
2014-01-01
In this paper we obtain fixed point and common fixed point theorems for self-mappings defined on a metric-type space, an ordered metric-type space or a normal cone metric space. Moreover, some examples and an application to integral equations are given to illustrate the usability of the obtained results.
28 CFR 70.15 - Metric system of measurement.
2010-07-01
... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Metric system of measurement. 70.15... AND OTHER NON-PROFIT ORGANIZATIONS Pre-Award Requirements § 70.15 Metric system of measurement. The... that the metric system is the preferred measurement system for U.S. trade and commerce. The...
Security Metrics: A Solution in Search of a Problem
Rosenblatt, Joel
2008-01-01
Computer security is one of the most complicated and challenging fields in technology today. A security metrics program provides a major benefit: looking at the metrics on a regular basis offers early clues to changes in attack patterns or environmental factors that may require changes in security strategy. The term "security metrics" loosely…
Geodesics in the space of K\\"ahler cone metrics
Calama, Simone
2012-01-01
In this paper, we prove the existence and uniqueness of the weak cone geodesics in the space of K\\"ahler cone metrics by solving the singular, homogeneous complex Monge-Amp\\`{e}re equation. As an application, we prove the metric space structure of the appropriate subspace of the space of K\\"ahler cone metrics.
Fixed Point Theorems in Quaternion-Valued Metric Spaces
Directory of Open Access Journals (Sweden)
Ahmed El-Sayed Ahmed
2014-01-01
Full Text Available The aim of this paper is twofold. First, we introduce the concept of quaternion metric spaces which generalizes both real and complex metric spaces. Further, we establish some fixed point theorems in quaternion setting. Secondly, we prove a fixed point theorem in normal cone metric spaces for four self-maps satisfying a general contraction condition.
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...
Understanding Acceptance of Software Metrics--A Developer Perspective
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…
Linear Connections on Normal Almost Contact Manifolds with Norden Metric
Teofilova, Marta
2011-01-01
Families of linear connections are constructed on almost contact manifolds with Norden metric. An analogous connection to the symmetric Yano connection is obtained on a normal almost contact manifold with Norden metric and closed structural 1-form. The curvature properties of this connection are studied on two basic classes of normal almost contact manifolds with Norden metric.
Candidate control design metrics for an agile fighter
Murphy, Patrick C.; Bailey, Melvin L.; Ostroff, Aaron J.
1991-01-01
Success in the fighter combat environment of the future will certainly demand increasing capability from aircraft technology. These advanced capabilities in the form of superagility and supermaneuverability will require special design techniques which translate advanced air combat maneuvering requirements into design criteria. Control design metrics can provide some of these techniques for the control designer. Thus study presents an overview of control design metrics and investigates metrics for advanced fighter agility. The objectives of various metric users, such as airframe designers and pilots, are differentiated from the objectives of the control designer. Using an advanced fighter model, metric values are documented over a portion of the flight envelope through piloted simulation. These metric values provide a baseline against which future control system improvements can be compared and against which a control design methodology can be developed. Agility is measured for axial, pitch, and roll axes. Axial metrics highlight acceleration and deceleration capabilities under different flight loads and include specific excess power measurements to characterize energy meneuverability. Pitch metrics cover both body-axis and wind-axis pitch rates and accelerations. Included in pitch metrics are nose pointing metrics which highlight displacement capability between the nose and the velocity vector. Roll metrics (or torsion metrics) focus on rotational capability about the wind axis.
GENERAL RELATIVITY AND METRICS OF INHOMOGENEOUS ROTATING UNIVERSE
Directory of Open Access Journals (Sweden)
Trunev A. P.
2014-01-01
Full Text Available The metric of inhomogeneous rotating Universe is discussed. There are examples of universal metrics obtained in Einstein's theory of gravitation. On the basis of solutions of Einstein’s equation we have proposed universal metric describing the properties of galaxies, groups and clusters of galaxies in inhomogeneous rotating Universe
45 CFR 2543.15 - Metric system of measurement.
2010-10-01
... 45 Public Welfare 4 2010-10-01 2010-10-01 false Metric system of measurement. 2543.15 Section 2543...-PROFIT ORGANIZATIONS Pre-Award Requirements § 2543.15 Metric system of measurement. The Metric Conversion... system is the preferred measurement system for U.S. trade and commerce. The Act requires each...
22 CFR 226.15 - Metric system of measurement.
2010-04-01
... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Metric system of measurement. 226.15 Section....S. NON-GOVERNMENTAL ORGANIZATIONS Pre-award Requirements § 226.15 Metric system of measurement. (a...) declares that the metric system is the preferred measurement system for U.S. trade and commerce....
45 CFR 74.15 - Metric system of measurement.
2010-10-01
... 45 Public Welfare 1 2010-10-01 2010-10-01 false Metric system of measurement. 74.15 Section 74.15... ORGANIZATIONS, AND COMMERCIAL ORGANIZATIONS Pre-Award Requirements § 74.15 Metric system of measurement. The... that the metric system is the preferred measurement system for U.S. trade and commerce. The...
22 CFR 145.15 - Metric system of measurement.
2010-04-01
... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Metric system of measurement. 145.15 Section... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade...
32 CFR 22.530 - Metric system of measurement.
2010-07-01
... CFR, 1991 Comp., p. 343), states that: (1) The metric system is the preferred measurement system for U... 32 National Defense 1 2010-07-01 2010-07-01 false Metric system of measurement. 22.530 Section 22... of measurement. (a) Statutory requirement. The Metric Conversion Act of 1975, as amended by...
40 CFR 30.15 - Metric system of measurement.
2010-07-01
... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Metric system of measurement. 30.15... measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205), declares that the metric system is the preferred measurement system for U.S. trade and commerce. The...
15 CFR 14.15 - Metric system of measurement.
2010-01-01
... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Metric system of measurement. 14.15... COMMERCIAL ORGANIZATIONS Pre-Award Requirements § 14.15 Metric system of measurement. The Metric Conversion... system is the preferred measurement system for U.S. trade and commerce. The Act requires each...
36 CFR 1210.15 - Metric system of measurement.
2010-07-01
... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Metric system of measurement... system of measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade...
24 CFR 84.15 - Metric system of measurement.
2010-04-01
... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Metric system of measurement. 84.15... measurement. The Metric Conversion Act, as amended by the Omnibus Trade and Competitiveness Act (15 U.S.C. 205) declares that the metric system is the preferred measurement system for U.S. trade and commerce. The...
32 CFR 32.15 - Metric system of measurement.
2010-07-01
... comply with requirements concerning the use of the metric system at 32 CFR 22.530. ... 32 National Defense 1 2010-07-01 2010-07-01 false Metric system of measurement. 32.15 Section 32..., HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Pre-Award Requirements § 32.15 Metric system of...
Tide or Tsunami? The Impact of Metrics on Scholarly Research
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…
Performance Comparison of QOS Metrics for a Distributed Pricing Scheme
Directory of Open Access Journals (Sweden)
S.S. Prasad
2011-06-01
Full Text Available De-centralized nature of nodes, in ad-hoc networks, results in the users adapting their operations independently. Such operations are mostly biased up on the figures and data available for the parameter s which are imperative for superior performance or, i n other words, improved Quality of Performance (QoS of the nodes. In centrally controlled networks foll owing cooperative game theory principles, collectiv e operations are performed by the nodes for better Qo S of the network. Although nodes in decentralized networks undertake individual operations, the final outcome of the whole network and thus the performa nce of the nodes in the network are influenced by the o perations of other nodes. Hence, a distributed reso urce allocation approach in such a scenario can be model ed as a non-cooperative game. Asynchronous Distributed Pricing (ADP is one such virtual prici ng algorithm in which a user’s payoff is determined by the difference between how much a given performance metric is valued and how much is paid for it. User service demands and priorities are modeled using nu merically emulated QoS metrics termed as utility functions. The network objective is to maximize the sum of all users’ payoff. However, for convergence of the sum of all users’ payoff to a global maximum, t he determination of the QoS metric’s utility functi on with sufficient concavity is essential. Although su permodularity conditions have been previously defin ed and determined to obtain suitable utility functions , we have numerically and analytically illustrated that the convergence performance characteristics fluctuates with the choice of QoS metrics in the algorithm for similar utility functions as well. We have assessed the optimality of utility functions under Signal-t o- Interference-plus-Noise ratio and Signal-to-Interfe rence ratio based calculations. This paper also exp lores into the difference in performance characteristics obtained by the addition of a
Almost-isometry between Teichm\\"{u}ller metric and length-spectra metric on moduli space
Liu, Lixin
2010-01-01
We prove an analogue of Farb-Masur's theorem that the length-spectra metric on moduli space is "almost isometric" to a simple model $\\mathcal {V}(S)$ which is induced by the cone metric over the complex of curves. As an application, we know that the Teichm\\"{u}ller metric and the length-spectra metric are "almost isometric" on moduli space, while they are not even quasi-isometric on Teichm\\"{u}ller space.
Approximate Kerr-Newman-like Metric with Quadrupole
Frutos-Alfaro, Francisco
2016-01-01
The Kerr metric is known to present issues when trying to find an interior solution. In this work we continue in our efforts to construct a more realistic exterior metric for astrophysical objects. A new approximate metric representing the spacetime of a charged, rotating and slightly-deformed body is obtained by perturbing the Kerr-Newman metric to include the mass-quadrupole and quadrupole-quadrupole orders. It has a simple form, because is Kerr-Newman-like. Its post-linear form without charge coincides with post-linear quadrupole-quadrupole metrics already found.
On the Efficiency of Image Metrics for Evaluating the Visual Quality of 3D Models.
Lavoue, Guillaume; Larabi, Mohamed Chaker; Vasa, Libor
2016-08-01
3D meshes are deployed in a wide range of application processes (e.g., transmission, compression, simplification, watermarking and so on) which inevitably introduce geometric distortions that may alter the visual quality of the rendered data. Hence, efficient model-based perceptual metrics, operating on the geometry of the meshes being compared, have been recently introduced to control and predict these visual artifacts. However, since the 3D models are ultimately visualized on 2D screens, it seems legitimate to use images of the models (i.e., snapshots from different viewpoints) to evaluate their visual fidelity. In this work we investigate the use of image metrics to assess the visual quality of 3D models. For this goal, we conduct a wide-ranging study involving several 2D metrics, rendering algorithms, lighting conditions and pooling algorithms, as well as several mean opinion score databases. The collected data allow (1) to determine the best set of parameters to use for this image-based quality assessment approach and (2) to compare this approach to the best performing model-based metrics and determine for which use-case they are respectively adapted. We conclude by exploring several applications that illustrate the benefits of image-based quality assessment. PMID:26394428
Directory of Open Access Journals (Sweden)
Abeer Albalawneh
2015-09-01
Full Text Available Jordan is characterized as a “water scarce” country. Therefore, conserving ecosystem services such as water regulation and soil retention is challenging. In Jordan, rainwater harvesting has been adapted to meet those challenges. However, the spatial composition and configuration features of a target landscape are rarely considered when selecting a rainwater-harvesting site. This study aimed to introduce landscape spatial features into the schemes for selecting a proper water-harvesting site. Landscape metrics analysis was used to quantify 10 metrics for three potential landscapes (i.e., Watershed 104 (WS 104, Watershed 59 (WS 59, and Watershed 108 (WS 108 located in the Jordanian Badia region. Results of the metrics analysis showed that the three non–vegetative land cover types in the three landscapes were highly suitable for serving as rainwater harvesting sites. Furthermore, Analytic Hierarchy Process (AHP was used to prioritize the fitness of the three target sites by comparing their landscape metrics. Results of AHP indicate that the non-vegetative land cover in the WS 104 landscape was the most suitable site for rainwater harvesting intervention, based on its dominance, connectivity, shape, and low degree of fragmentation. Our study advances the water harvesting network design by considering its landscape spatial pattern.
DEFF Research Database (Denmark)
Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper
2015-01-01
Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled in ways that meaningfully adapt according to people’s situations and design intentions. This book discusses...... distributed differently into an architectural body. We also examine what might occur when light is dynamic and able to change colour, intensity and direction, and when it is adaptive and can be brought into interaction with its surroundings. In short, what happens to an architectural space when artificial...
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.
Inheritance Hierarchy Based Reuse & Reusability Metrics in OOSD
Directory of Open Access Journals (Sweden)
Nasib S. Gill,
2011-06-01
Full Text Available Reuse and reusability are two major aspects in object oriented software which can be measured from inheritance hierarchy. Reusability is the prerequisite of reuse but both may or may not bemeasured using same metric. This paper characterizes metrics of reuse and reusability in Object Oriented Software Development (OOSD. Reuse metrics compute the extent to which classes have been reused and reusability metrics computes the extent to which classes can be reused. In this paper five new metrics namely- Breadth of Inheritance Tree (BIT, Method Reuse Per Inheritance Relation (MRPIR,Attribute Reuse Per Inheritance Relation (ARPIR, Generality of Class (GC and Reuse Probability (RP have been proposed. These metrics help to evaluate reuse and reusability of object oriented software.Four extensively validated existing object oriented metrics, namely- Depth of Inheritance Tree (DIT, Number of Children (NOC, Method Inheritance Factor (MIF and Attribute Inheritance Factor (AIFhave been selected and investigated for comparison with proposed metrics. All metrics can be computed from inheritance hierarchies and classified according to their characteristics. Further, metrics areevaluated against a case study. These metrics are helpful in comparing alternative inheritance hierarchies at design time to select best alternative, so that the development time and cost can be reduced.
Metric Compatible or Noncompatible Finsler--Ricci Flows
Vacaru, Sergiu I
2011-01-01
There were elaborated different models of Finsler geometry using the Cartan (metric compatible), or Berwald and Chern (metric non-compatible) connections, the Ricci flag curvature etc. In a series of works, we studied (non)commutative metric compatible Finsler and nonholonomic generalizations of the Ricci flow theory [see S. Vacaru, J. Math. Phys. 49 (2008) 043504; 50 (2009) 073503 and references therein. The goal of this work is to prove that there are some models of Finsler gravity and geometric evolution theories with generalized Perelman's functionals, and correspondingly derived nonholonomic Hamilton evolution equations, when metric noncompatible Finsler connections are involved. Following such an approach, we have to consider distortion tensors, uniquely defined by the Finsler metric, from the Cartan and/or the canonical metric compatible connections. We conclude that, in general, it is not possible to elaborate self-consistent models of geometric evolution with arbitrary Finsler metric noncompatible co...
Metrication: An economic wake-up call for US industry
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.
Balanced metrics for vector bundles and polarised manifolds
DEFF Research Database (Denmark)
Garcia Fernandez, Mario; Ross, Julius
2012-01-01
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...... 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...
The mathematics of non-linear metrics for nested networks
Wu, Rui-Jie; Shi, Gui-Yuan; Zhang, Yi-Cheng; Mariani, Manuel Sebastian
2016-10-01
Numerical analysis of data from international trade and ecological networks has shown that the non-linear fitness-complexity metric is the best candidate to rank nodes by importance in bipartite networks that exhibit a nested structure. Despite its relevance for real networks, the mathematical properties of the metric and its variants remain largely unexplored. Here, we perform an analytic and numeric study of the fitness-complexity metric and a new variant, called minimal extremal metric. We rigorously derive exact expressions for node scores for perfectly nested networks and show that these expressions explain the non-trivial convergence properties of the metrics. A comparison between the fitness-complexity metric and the minimal extremal metric on real data reveals that the latter can produce improved rankings if the input data are reliable.
Hybrid metric-Palatini brane system
Fu, Qi-Ming; Zhao, Li; Gu, Bao-Min; Yang, Ke; Liu, Yu-Xiao
2016-07-01
It is known that the metric and Palatini formalisms of gravity theories have their own interesting features but also suffer from some different drawbacks. Recently, a novel gravity theory called hybrid metric-Palatini gravity was put forward to cure or improve their individual deficiencies. The action of this gravity theory is a hybrid combination of the usual Einstein-Hilbert action and a f (R ) term constructed by the Palatini formalism. Interestingly, it seems that the existence of a light and long-range scalar field in this gravity may modify the cosmological and galactic dynamics without conflicting with the laboratory and Solar System tests. In this paper, we focus on the tensor and scalar perturbations of the thick branes in this novel gravity theory. We consider two models as examples, namely, the thick branes constructed by a background scalar field and by pure gravity. The thick branes in both models have no inner structure. However, affected by the hybrid combination of the metric and Palatini formalisms, the graviton zero mode in the first model has inner structure when the parameter in this model is larger than its critical value, which is different from the cases of general relativity and Palatini f (R ) gravity. We find that the effective four-dimensional gravity can be reproduced on the brane for both models and the scalar zero mode in the model without a background scalar field cannot be localized on the brane, which avoids a fifth force. Moreover, the stability of both brane systems against the linear perturbations can also be ensured.
Invariant distances and metrics in complex analysis
Jarnicki, Marek
2013-01-01
As in the field of ""Invariant Distances and Metrics in Complex Analysis"" there was and is a continuous progress this is the second extended edition of the corresponding monograph. This comprehensive book is about the study of invariant pseudodistances (non-negative functions on pairs of points) and pseudometrics (non-negative functions on the tangent bundle) in several complex variables. It is an overview over a highly active research area at the borderline between complex analysis, functional analysis and differential geometry. New chapters are covering the Wu, Bergman and several other met
Evaluating and Estimating the WCET Criticality Metric
DEFF Research Database (Denmark)
Jordan, Alexander
2014-01-01
Static analysis tools that are used for worst-case execution time (WCET) analysis of real-time software just provide partial information on an analyzed program. Only the longest-executing path, which currently determines the WCET bound is indicated to the programmer. This limited view can prevent...... 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...
Comment on "Conformally flat stationary axisymmetric metrics"
Barnes, A; Senovilla, José MM
2003-01-01
Garcia and Campuzano claim to have found a previously overlooked family of stationary and axisymmetric conformally flat spacetimes, contradicting an old theorem of Collinson. In both these papers it is tacitly assumed that the isometry group is orthogonally transitive. Under the same assumption, we point out here that Collinson's result still holds if one demands the existence of an axis of symmetry on which the axial Killing vector vanishes. On the other hand if the assumption of orthogonal transitivity is dropped, a wider class of metrics is allowed and it is possible to find explicit counterexamples to Collinson's result.
Metric Gauge Fields in Deformed Special Relativity
Cardone, F; Petrucci, A
2014-01-01
We show that, in the framework of Deformed Special Relativity (DSR), namely a (four-dimensional) generalization of the (local) space-time struc- ture based on an energy-dependent "deformation" of the usual Minkowski geometry, two kinds of gauge symmetries arise, whose spaces either coin- cide with the deformed Minkowski space or are just internal spaces to it. This is why we named them "metric gauge theories". In the case of the internal gauge ?elds, they are a consequence of the deformed Minkowski space (DMS) possessing the structure of a generalized Lagrange space. Such a geometrical structure allows one to de?ne curvature and torsion in the DMS.
Rotating Black Holes and the Kerr Metric
Kerr, Roy Patrick
2008-10-01
Since it was first discovered in 1963 the Kerr metric has been used by relativists as a test-bed for conjectures on worm-holes, time travel, closed time-like loops, and the existence or otherwise of global Cauchy surfaces. More importantly, it has also used by astrophysicists to investigate the effects of collapsed objects on their local environments. These two groups of applications should not be confused. Astrophysical Black Holes are not the same as the Kruskal solution and its generalisations.
Adaptive Sampling in Hierarchical Simulation
Energy Technology Data Exchange (ETDEWEB)
Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R
2007-07-09
We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.
Kwakkel, Jan; Haasnoot, Marjolijn
2015-04-01
In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the
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.
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.
Superradiance on the Reissner-Nordstrom metric
Di Menza, Laurent
2014-01-01
In this article, we study the superradiance of charged scalar fields on the sub-extremal Reissner-Nordstrom metric, a mechanism by which such fields can extract energy from a static spherically symmetric charged black hole. A geometrical way of measuring the amount of energy extracted is proposed. Then we investigate the question numerically. The toy-model and the numerical methods used in our simulations are presented and the problem of long time measurement of the outgoing energy flux is discussed. We provide a numerical example of a field exhibiting a behaviour analogous to the Penrose process: an incoming wave packet which splits, as it approaches the black hole, into an incoming part with negative energy and an outgoing part with more energy than the initial incoming one. We also show another type of superradiant solution for which the energy extraction is more important. Hyperradiant behaviour is not observed, which is an indication that the Reissner-Nordstrom metric is linearly stable in the sub-extrem...
Hybrid metric-Palatini brane system
Fu, Qi-Ming; Liu, Yu-Xiao
2016-01-01
It is known that the metric and Palatini formalisms of gravity theories have their own interesting features but also suffer from some different drawbacks. Recently, a novel gravity theory called hybrid metric-Palatini gravity was put forward to cure or improve their individual deficiencies. The action of this gravity theory is a hybrid combination of the usual Einstein-Hilbert action and a $f(\\mathcal{R})$ term constructed by the Palatini formalism. Interestingly, it seems that the existence of a light and long-range scalar field in this gravity may modify the cosmological and galactic dynamics without conflicting with the laboratory and Solar System tests. In this paper we focus on the tensor perturbation of thick branes in this novel gravity theory. We consider two models as examples, namely, the thick branes constructed by a background scalar field and by pure gravity. The thick branes in both models have no inner structure. However, the graviton zero mode in the first model has inner structure when the pa...
Hausdorff metric BV discontinuity of sweeping processes
Klein, Olaf; Recupero, Vincenzo
2016-06-01
Sweeping processes are a class of evolution differential inclusions arising in elastoplasticity and were introduced by J.J. Moreau in the early seventies. The solution operator of the sweeping processes represents a relevant example of rate independent operator. As a particular case we get the so called play operator, which is a typical example of a hysteresis operator. The continuity properties of these operators were studied in several works. In this note we address the continuity with respect to the strict metric in the space of functions of bounded variation with values in the metric space of closed convex subsets of a Hilbert space. We provide counterexamples showing that for all BV-formulations of the sweeping process the corresponding solution operator is not continuous when its domain is endowed with the strict topology of BV and its codomain is endowed with the L1-topology. This is at variance with the play operator which has a BV-extension that is continuous in this case.
Harmonic gauge perturbations of the Schwarzschild metric
Berndtson, Mark V
1996-01-01
The satellite observatory LISA will be capable of detecting gravitational waves from extreme mass ratio inspirals (EMRIs), such as a small black hole orbiting a supermassive black hole. The gravitational effects of the much smaller mass can be treated as the perturbation of a known background metric, here the Schwarzschild metric. The perturbed Einstein field equations form a system of ten coupled partial differential equations. We solve the equations in the harmonic gauge, also called the Lorentz gauge or Lorenz gauge. Using separation of variables and Fourier transforms, we write the frequency domain solutions in terms of six radial functions which satisfy decoupled ordinary differential equations. The six functions are the Zerilli and five generalized Regge-Wheeler functions of spin 2,1,0. We use the solutions to calculate the gravitational self-force for circular orbits. The self-force gives the first order perturbative corrections to the equations of motion. Section 1.2 of the thesis has a more detailed ...
Fanpage metrics analysis. "Study on content engagement"
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.
Two-Basket Approach and Emission Metrics
Tanaka, K.; Schmale, J.; von Schneidemesser, E.
2013-12-01
Cutting the emissions of Short-Lived Climate-Forcing Air Pollutants (SLCPs) gains increasing global attention as a mitigation policy option because of direct benefits for climate and co-benefits such as improvements in air quality. Including SLCPs as target components to abate within a single basket (e.g. the Kyoto Protocol) would, however, face issues with regard to: i) additional assumptions that are required to compare SLCP emissions and CO2 emissions within a basket in terms of climatic effects, especially because of the difference in lifetimes, ii) the accountability of non-climatic effects in the emission trading between SLCPs and CO2. The idea of a two-basket approach was originally proposed as a climatic analogue to the Montreal Protocol dealing with ozone depleting substances (Jackson 2009; Daniel et al. 2012; Smith et al. 2013). In a two-basket approach, emissions are allowed to be traded within a basket but not across the baskets. While this approach potentially ensures scientifically supported emission trading (e.g. (Smith et al. 2013)), this approach leaves open the important issue of how to determine the relative weight between two baskets. Determining the weight cannot be answered by science alone, as the question involves a value judgment as stressed in metric studies (e.g. (Tanaka et al. 2010; Tanaka et al. 2013)). We discuss emission metrics in the context of a two-basket approach and present policy implications of such an approach. In a two-basket approach, the weight between two baskets needs to be determined a priori or exogenously. Here, an opportunity arises to present synergetic policy options targeted at mitigating climate change and air pollution simultaneously. In other words, this could be a strategy to encourage policymakers to consider cross-cutting issues. Under a two-basket climate policy, policymakers would be exposed to questions such as: - What type of damages caused by climate change does one choose to avoid? - To what extent
DEFF Research Database (Denmark)
Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper
2015-01-01
Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled in ways that meaningfully adapt according to people’s situations and design intentions. This book discusses...... the investigations of lighting scenarios carried out in two test installations: White Cube and White Box. The test installations are discussed as large-scale experiential instruments. In these test installations we examine what could potentially occur when light using LED technology is integrated and...
WTR: A Reputation Metric for Distributed Hash Tables Based on a Risk and Credibility Factor
Institute of Scientific and Technical Information of China (English)
Xavier Bonnaire; Erika Rosas
2009-01-01
The growing number of popular peer to peer applications during the last five years has implied for researchers to focus on how to build trust in such very large scale distributed systems Reputation systems have shown to be a very good solution to build trust in presence of malicious nodes.We propose in this paper a new metric for reputation systems on top of a Distributed Hash Table that uses a notion of risk to make the applications aware of certain behaviours of malicious nodes.We show that our metric iS able to significantly reduce the number of malicious transactions.and that it also provides very strong resistance to several traditional attacks of reputations systems.We also show that our solution can easily scale.and can be adapted to various Distributed Hash Tables.
Harrell, William
1999-01-01
Provides information on various adaptive technology resources available to people with disabilities. (Contains 19 references, an annotated list of 129 websites, and 12 additional print resources.) (JOW)
National Aeronautics and Space Administration — Advanced Diagnostics and Prognostics Testbed (ADAPT) Project Lead: Scott Poll Subject Fault diagnosis in electrical power systems Description The Advanced...
Long-term energy planning with uncertain environmental performance metrics
International Nuclear Information System (INIS)
Highlights: • Environmental performance uncertainty considered in a long-term energy planning model. • Application to electricity generation planning in British Columbia. • Interactions with climate change mitigation and adaptation strategy are assessed. • Performance risk-hedging impacts the technology investment strategy. • Sensitivity of results to model formulation is discussed. - Abstract: Environmental performance (EP) uncertainties span a number of energy technology options, and pose planning risk when the energy system is subject to environmental constraints. This paper presents two approaches to integrating EP uncertainty into the long-term energy planning framework. The methodologies consider stochastic EP metrics across multiple energy technology options, and produce a development strategy that hedges against the risk of exceeding environmental targets. Both methods are compared within a case study of emission-constrained electricity generation planning in British Columbia, Canada. The analysis provides important insight into model formulation and the interactions with concurrent environmental policy uncertainties. EP risk is found to be particularly important in situations where environmental constraints become increasingly stringent. Model results indicate allocation of a modest risk premium in these situations can provide valuable hedging against EP risk
Creane, Arthur; Maher, Eoghan; Sultan, Sherif; Hynes, Niamh; Kelly, Daniel J; Lally, Caitríona
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. PMID:22086167
Measurable Control System Security through Ideal Driven Technical Metrics
Energy Technology Data Exchange (ETDEWEB)
Miles McQueen; Wayne Boyer; Sean McBride; Marie Farrar; Zachary Tudor
2008-01-01
The Department of Homeland Security National Cyber Security Division supported development of a small set of security ideals as a framework to establish measurable control systems security. Based on these ideals, a draft set of proposed technical metrics was developed to allow control systems owner-operators to track improvements or degradations in their individual control systems security posture. The technical metrics development effort included review and evaluation of over thirty metrics-related documents. On the bases of complexity, ambiguity, or misleading and distorting effects the metrics identified during the reviews were determined to be weaker than necessary to aid defense against the myriad threats posed by cyber-terrorism to human safety, as well as to economic prosperity. Using the results of our metrics review and the set of security ideals as a starting point for metrics development, we identified thirteen potential technical metrics - with at least one metric supporting each ideal. Two case study applications of the ideals and thirteen metrics to control systems were then performed to establish potential difficulties in applying both the ideals and the metrics. The case studies resulted in no changes to the ideals, and only a few deletions and refinements to the thirteen potential metrics. This led to a final proposed set of ten core technical metrics. To further validate the security ideals, the modifications made to the original thirteen potential metrics, and the final proposed set of ten core metrics, seven separate control systems security assessments performed over the past three years were reviewed for findings and recommended mitigations. These findings and mitigations were then mapped to the security ideals and metrics to assess gaps in their coverage. The mappings indicated that there are no gaps in the security ideals and that the ten core technical metrics provide significant coverage of standard security issues with 87% coverage. Based
Similarity Metrics for Closed Loop Dynamic Systems
Whorton, Mark S.; Yang, Lee C.; Bedrossian, Naz; Hall, Robert A.
2008-01-01
To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and
Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report
Energy Technology Data Exchange (ETDEWEB)
Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Miner, Nadine E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Military & Energy Systems Analysis (6114, M/S 1188); Wilson, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Resilience and Regulatory Effects (6921, M/S 1138); Le, Hai D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Kao, Gio K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Networked System Survivability & Assurance (5629, M/S 0671); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Software Systems R& D (9525, M/S 1188); Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Jr., Robert C. [SAIC, Inc., Albuquerque, NM (United States)
2015-01-01
Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.
Metric and Kernel Learning using a Linear Transformation
Jain, Prateek; Davis, Jason V; Dhillon, Inderjit S
2009-01-01
Metric and kernel learning are important in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional data, while existing kernel learning algorithms are often limited to the transductive setting and do not generalize to new data points. In this paper, we study metric learning as a problem of learning a linear transformation of the input data. We show that for high-dimensional data, a particular framework for learning a linear transformation of the data based on the LogDet divergence can be efficiently kernelized to learn a metric (or equivalently, a kernel function) over an arbitrarily high dimensional space. We further demonstrate that a wide class of convex loss functions for learning linear transformations can similarly be kernelized, thereby considerably expanding the potential applications of metric learning. We demonstrate our learning approach by applying it to large-scale real world problems in computer vision and tex...
Performance metrics for the evaluation of hyperspectral chemical identification systems
Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay
2016-02-01
Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.
Clean Cities 2014 Annual Metrics Report
Energy Technology Data Exchange (ETDEWEB)
Johnson, Caley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Singer, Mark [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2015-12-22
Each year, the U.S. Department of Energy asks its Clean Cities program coordinators to submit annual reports of their activities and accomplishments for the previous calendar year. Data and information are submitted via an online database that is maintained as part of the Alternative Fuels Data Center (AFDC) at the National Renewable Energy Laboratory (NREL). Coordinators submit a range of data that characterize the membership, funding, projects, and activities of their coalitions. They also submit data about sales of alternative fuels, deployment of alternative fuel vehicles (AFVs) and hybrid electric vehicles (HEVs), idle-reduction (IR) initiatives, fuel economy activities, and programs to reduce vehicle miles traveled (VMT). NREL analyzes the data and translates them into petroleum-use reduction impacts, which are summarized in this 2014 Annual Metrics Report.
Clean Cities 2013 Annual Metrics Report
Energy Technology Data Exchange (ETDEWEB)
Johnson, C.; Singer, M.
2014-10-01
Each year, the U.S. Department of Energy asks its Clean Cities program coordinators to submit annual reports of their activities and accomplishments for the previous calendar year. Data and information are submitted via an online database that is maintained as part of the Alternative Fuels Data Center (AFDC) at the National Renewable Energy Laboratory (NREL). Coordinators submit a range of data that characterize the membership, funding, projects, and activities of their coalitions. They also submit data about sales of alternative fuels, deployment of alternative fuel vehicles (AFVs) and hybrid electric vehicles (HEVs), idle-reduction (IR) initiatives, fuel economy activities, and programs to reduce vehicle miles traveled (VMT). NREL analyzes the data and translates them into petroleum-use reduction impacts, which are summarized in this 2013 Annual Metrics Report.
Metric projection for dynamic multiplex networks
Jurman, Giuseppe
2016-01-01
Evolving multiplex networks are a powerful model for representing the dynamics along time of different phenomena, such as social networks, power grids, biological pathways. However, exploring the structure of the multiplex network time series is still an open problem. Here we propose a two-steps strategy to tackle this problem based on the concept of distance (metric) between networks. Given a multiplex graph, first a network of networks is built for each time steps, and then a real valued time series is obtained by the sequence of (simple) networks by evaluating the distance from the first element of the series. The effectiveness of this approach in detecting the occurring changes along the original time series is shown on a synthetic example first, and then on the Gulf dataset of political events.
Dust ball physics and the Schwarzschild metric
Kassner, Klaus
2016-01-01
A physics-first derivation of the Schwarzschild metric is given. Gravitation is described in terms of the effects of tidal forces (or of spacetime curvature) on the volume of a small ball of test particles (a dust ball), freely falling after all particles were at rest with respect to each other initially. The possibility to express Einstein's equation this way and some of its ramifications have been enjoyably discussed by Baez and Bunn [Am. J. Phys. 73, 644 (2005)]. Since the formulation avoids the use of tensors, neither advanced tensor calculus nor sophisticated differential geometry are needed in the calculation. The derivation is not lengthy and it has visual appeal, so it may be useful in teaching.
Nonintegrability of the Zipoy-Voorhees metric
Lukes-Gerakopoulos, Georgios
2012-08-01
The low frequency gravitational wave detectors like the evolved Laser Interferometer Space Antenna/New Gravitational Wave Observatory (eLISA/NGO) will give us the opportunity to test whether the supermassive compact objects lying at the centers of galaxies are indeed Kerr black holes. One way to do such a test is to compare the gravitational wave signals with templates of perturbed black hole spacetimes, the so-called bumpy black hole spacetimes. The Zipoy-Voorhees (ZV) spacetime (known also as the γ spacetime) can be included in the bumpy black hole family, since it can be considered as a perturbation of the Schwarzschild spacetime background. Several authors have suggested that the ZV metric corresponds to an integrable system. Contrary to this integrability conjecture, the present article shows by numerical examples that, in general, ZV belongs to the family of nonintegrable systems.
A Metric Encoding for Bounded Model Checking
Pradella, Matteo; Morzenti, Angelo; San Pietro, Pierluigi
In Bounded Model Checking, both the system model and the checked property are translated into a Boolean formula to be analyzed by a SAT-solver. We introduce a new encoding technique which is particularly optimized for managing quantitative future and past metric temporal operators, typically found in properties of hard real time systems. The encoding is simple and intuitive in principle, but it is made more complex by the presence, typical of the Bounded Model Checking technique, of backward and forward loops used to represent an ultimately periodic infinite domain by a finite structure. We report and comment on the new encoding technique and on an extensive set of experiments carried out to assess its feasibility and effectiveness.
Metric Learning to Enhance Hyperspectral Image Segmentation
Thompson, David R.; Castano, Rebecca; Bue, Brian; Gilmore, Martha S.
2013-01-01
Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.
Symmetries and pre-metric electromagnetism
Delphenich, D
2005-01-01
The equations of pre-metric electromagnetism are formulated as an exterior differential system on the bundle of exterior differential 2-forms over the spacetime manifold. The general form for the symmetry equations of the system is computed and then specialized to various possible forms for an electromagnetic constitutive law, namely, uniform linear, non-uniform linear, and uniform nonlinear. It is shown that in the uniform linear case, one has four possible ways of prolonging the symmetry Lie algebra, including prolongation to a Lie algebra of infinitesimal projective transformations of a real four-dimensional projective space. In the most general non-uniform linear case, th effect of non-uniformity on symmetry seems inconclusive in the absence of further specifics, and in the uniform nonlinear case, the overall difference from the uniform linear case amounts to a deformation of the electromagnetic constitutive tensor by the electromagnetic fields strengths, which induces a corresponding deformation of the s...
Rainbow metric from quantum gravity: anisotropic cosmology
Assanioussi, Mehdi
2016-01-01
In this paper we present a construction of effective cosmological models which describe the propagation of a massive quantum scalar field on a quantum anisotropic cosmological spacetime. Each obtained effective model is represented by a rainbow metric in which particles of distinct momenta propagate on different classical geometries. Our analysis shows that upon certain assumptions and conditions on the parameters determining such anisotropic models, we surprisingly obtain a unique deformation parameter $\\beta$ in the modified dispersion relation of the modes. Hence inducing an isotropic deformation despite the general starting considerations. We then ensure the recovery of the dispersion relation realized in the isotropic case, studied in [arXiv:1412.6000], when some proper symmetry constraints are imposed, and we estimate the value of the deformation parameter for this case in loop quantum cosmology context.
MESUR metrics from scholarly usage of resources
CERN. Geneva; Van de Sompel, Herbert
2007-01-01
Usage data is increasingly regarded as a valuable resource in the assessment of scholarly communication items. However, the development of quantitative, usage-based indicators of scholarly impact is still in its infancy. The Digital Library Research & Prototyping Team at the Los Alamos National Laboratory's Research library has therefore started a program to expand the set of usage-based tools for the assessment of scholarly communication items. The two-year MESUR project, funded by the Andrew W. Mellon Foundation, aims to define and validate a range of usage-based impact metrics, and issue guidelines with regards to their characteristics and proper application. The MESUR project is constructing a large-scale semantic model of the scholarly community that seamlessly integrates a wide range of bibliographic, citation and usage data. Functioning as a reference data set, this model is analyzed to characterize the intricate networks of typed relationships that exist in the scholarly community. The resulting c...
New Metrics for Observatory Publication Statistics
Rots, A.; Winkelman, S.; Becker, G.
2012-09-01
We are proposing several new publication metrics that are more meaningful and less sensitive to observatory-specific characteristics than the traditional ones. They fall into three main categories: speed of publication; fraction of observing time published; and archival usage. Citation of results is a fourth category, but it lends itself less well to definite statements. Applied to the bibliography of the Chandra X-ray Observatory, the median time from observation to publication is 2.36 years; after about seven years 90% of the observing time is published; the total annual publication output of the mission is 60-70% of the cumulative observing time available, assuming a two year lag between data retrieval and publication; and after seven years approximately 60% of available exposure time is published more than twice.
A nonlocal metric formulation of MOND
International Nuclear Information System (INIS)
We study a class of nonlocal, but causal, covariant and conserved field equations for the metric. Although nonlocal, these equations do not seem to possess extra graviton solutions in weak field perturbation theory. Indeed, the equations reduce to those of general relativity when the Ricci scalar vanishes throughout spacetime. When a static matter source is present, we show how these equations can be adjusted to reproduce Milgrom's modified Newtonian dynamics in the weak field regime, while reducing to general relativity for strong fields. We compute the angular deflection of light in the weak field regime and demonstrate that it is the same as for general relativity, resulting in far too little lensing if no dark matter is present. We also study the field equations for a general Robertson-Walker geometry. An interesting feature of our equations is that they become conformally invariant in the MOND (modified nonrelativistic dynamics) limit
Quantitative metric theory of continued fractions
Indian Academy of Sciences (India)
J Hančl; A Haddley; P Lertchoosakul; R Nair
2016-05-01
Quantitative versions of the central results of the metric theory of continued fractions were given primarily by C. De Vroedt. In this paper we give improvements of the bounds involved . For a real number , let $$x=c_0+\\dfrac{1}{c_1+\\dfrac{1}{c_2+\\dfrac{1}{c_3+\\dfrac{1}{c_4+_\\ddots}}}}.$$ A sample result we prove is that given $\\epsilon > 0$, $$(c_1(x)\\cdots c_n(x))^{\\frac{1}{n}}=\\prod^\\infty_{k=1}\\left( 1+\\frac{1}{k(k+2)}\\right)^{\\frac{\\log \\, k}{\\log \\, 2}}+o\\left(n^{-\\frac{1}{2}}(\\log \\, n)^{\\frac{3}{2}}(\\log \\, \\log \\, n)^{\\frac{1}{2}+\\epsilon}\\right)$$
Economic metrics for wind energy projects
Directory of Open Access Journals (Sweden)
Wagner Sousa de Oliveira, Antonio Jorge Fernandes, Joaquim Jose Borges Gouveia
2011-11-01
Full Text Available This paper presents an overview of economic metrics for wind energy projects. The attractiveness of the proposed wind energy can vary considerably between evaluation of the private and public sector. The financing structure is very important influencing factor for the attractiveness of wind energy project. In many cases, the economic activities practiced by economic agents of financing the project in order to earn sufficient income to meet the investors‘ needs and other economic agents involved. They are also characterized the assessment indicators and economic-financial management of projects implemented renewable energy exclusively for onshore wind energy systems. All indicators presented should be used in economic engineering analysis to meet specific information needs for decision making in situations of investment opportunity for renewable energy projects.