Classification in Medical Image Analysis Using Adaptive Metric KNN
Chen, Chen; Chernoff, Konstantin; Karemore, Gopal Raghunath; Lo, Pechin Chien Pau; Nielsen, Mads; Lauze, Francois Bernard
2010-01-01
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...
Adaptive Metric Kernel Regression
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
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...
Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search
Mei, Gang; Xu, Nengxiong; Xu, Liangliang
2016-01-01
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-Nearest Neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is ...
Multiclass Boosting with Adaptive Group-Based kNN and Its Application in Text Categorization
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
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 .
Adaptive Metric Learning for Saliency Detection.
Li, Shuang; Lu, Huchuan; Lin, Zhe; Shen, Xiaohui; Price, Brian
2015-11-01
In this paper, we propose a novel adaptive metric learning algorithm (AML) for visual saliency detection. A key observation is that the saliency of a superpixel can be estimated by the distance from the most certain foreground and background seeds. Instead of measuring distance on the Euclidean space, we present a learning method based on two complementary Mahalanobis distance metrics: 1) generic metric learning (GML) and 2) specific metric learning (SML). GML aims at the global distribution of the whole training set, while SML considers the specific structure of a single image. Considering that multiple similarity measures from different views may enhance the relevant information and alleviate the irrelevant one, we try to fuse the GML and SML together and experimentally find the combining result does work well. Different from the most existing methods which are directly based on low-level features, we devise a superpixelwise Fisher vector coding approach to better distinguish salient objects from the background. We also propose an accurate seeds selection mechanism and exploit contextual and multiscale information when constructing the final saliency map. Experimental results on various image sets show that the proposed AML performs favorably against the state-of-the-arts. PMID:26054067
A Unified View of Adaptive Variable-Metric Projection Algorithms
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.
Witten's perturbation on strata with general adapted metrics
López, Jesús A. Álvarez; Calaza, Manuel
2015-01-01
Let $M$ be a stratum of a compact stratified space $A$. It is equipped with a general adapted metric $g$, which is slightly more general than the adapted metrics of Nagase and Brasselet-Hector-Saralegi. In particular, $g$ has a general type, which is an extension of the type of an adapted metric. A restriction on this general type is assumed, and then $g$ is called good. We consider the maximum/minimun ideal boundary condition, $d_{\\text{max/min}}$, of the compactly supported de~Rham complex ...
Stability and Performance Metrics for Adaptive Flight Control
Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens
2009-01-01
This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.
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...
A low-cost compact metric adaptive optics system
Mansell, Justin D.; Henderson, Brian; Wiesner, Brennen; Praus, Robert; Coy, Steve
2007-09-01
The application of adaptive optics has been hindered by the cost, size, and complexity of the systems. We describe here progress we have made toward creating low-cost compact turn-key adaptive optics systems. We describe our new low-cost deformable mirror technology developed using polymer membranes, the associated USB interface drive electronics, and different ways that this technology can be configured into a low-cost compact adaptive optics system. We also present results of a parametric study of the stochastic parallel gradient descent (SPGD) control algorithm.
Density estimation using KNN and a potential model
Lu, Yonggang; Qiao, Jiangang; Liao, Li; Yang, Wuyang
2013-10-01
Density-based clustering methods are usually more adaptive than other classical methods in that they can identify clusters of various shapes and can handle noisy data. A novel density estimation method is proposed using both the knearest neighbor (KNN) graph and a hypothetical potential field of the data points to capture the local and global data distribution information respectively. An initial density score computed using KNN is used as the mass of the data point in computing the potential values. Then the computed potential is used as the new density estimation, from which the final clustering result is derived. All the parameters used in the proposed method are determined from the input data automatically. The new clustering method is evaluated by comparing with K-means++, DBSCAN, and CSPV. The experimental results show that the proposed method can determine the number of clusters automatically while producing competitive clustering results compared to the other three methods.
Interesting Metrics Based Adaptive Prediction Technique for Knowledge Discovery
G. Anbukkarasy; N. Sairam
2013-01-01
Prediction is considered as an important factor to predict the future results from the existing information. Decision tree methodology is widely used for predicting the results. But this is not efficient to handle the large, heterogeneous or multi-featured type of data sources. So an adaptive prediction method is proposed by combining the statistical analysis approach of the data mining methods along with the decision tree prediction methodology. So when dealing with large and multi-server ba...
Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning
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
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.
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...
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.
Multiple Closed-Form Local Metric Learning for K-Nearest Neighbor Classifier
Ye, Jianbo
2013-01-01
Many researches have been devoted to learn a Mahalanobis distance metric, which can effectively improve the performance of kNN classification. Most approaches are iterative and computational expensive and linear rigidity still critically limits metric learning algorithm to perform better. We proposed a computational economical framework to learn multiple metrics in closed-form.
Efficient and Flexible KNN Query Processing in Real-Life Road Networks
Lu, Yang; Bui, Bin; Zhao, Jiakui;
2008-01-01
included into the RNG index, which enables the index to support both distance-based and time-based KNN queries and continuous KNN queries. Our work extends previous ones by taking into account more practical scenarios, such as complexities in real-life road networks and time-based KNN queries. Extensive...
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...
A Novel Approach for the Diagnosis of Diabetes and Liver Cancer using ANFIS and Improved KNN
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.
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...
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 ...
Cogntive Consistency Analysis in Adaptive Bio-Metric Authentication System Design
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
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 hybrid KNN-MLP algorithm to diagnose bipolar disorder
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.
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)
AN EFFICIENT TEXT CLASSIFICATION USING KNN AND NAIVE BAYESIAN
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.
kNN method on KASCADE-grande data
KASCADE-grande, located at Forschungszentrum Karlsruhe, is a multi-detector experiment for the measurement of extensive air showers induced by primary cosmic rays in the energy range of 1014-1018 eV. The ''k-Nearest Neighbours'' (KNN) method is a classification procedure applied for a preliminary study of the cosmic ray composition in this energy range. Simulations of different primary particles are used as reference samples. In order to find for each real event the k-Nearest Neighbours in the reference sample, the Mahalanobis distance in the space defined by the muon size, the shower size and age (obtained from the NKG fit of the lateral distribution of the charged particles) is calculated. The probability of the event to be part of one of the simulated primary groups is the percentage of the k neighbours belonging to it. Preliminary results of the application of this technique to KASCADE-grande data with respect to simulated samples are reported
GPU-FS-kNN: a software tool for fast and scalable kNN computation using GPUs.
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
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.
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...
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
A Novel Approach to Face Recognition using Image Segmentation based on SPCA-KNN Method
P. Kamencay
2013-04-01
Full Text Available In this paper we propose a novel method for face recognition using hybrid SPCA-KNN (SIFT-PCA-KNN approach. The proposed method consists of three parts. The first part is based on preprocessing face images using Graph Based algorithm and SIFT (Scale Invariant Feature Transform descriptor. Graph Based topology is used for matching two face images. In the second part eigen values and eigen vectors are extracted from each input face images. The goal is to extract the important information from the face data, to represent it as a set of new orthogonal variables called principal components. In the final part a nearest neighbor classifier is designed for classifying the face images based on the SPCA-KNN algorithm. The algorithm has been tested on 100 different subjects (15 images for each class. The experimental result shows that the proposed method has a positive effect on overall face recognition performance and outperforms other examined methods.
Indexing the bit-code and distance for fast KNN search in high-dimensional spaces
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.
A Weighted Discrete KNN Method for Mandarin Speech and Emotion Recognition
Pao, Tsang-Long; Liao, Wen-Yuan; Chen, Yu-Te
2008-01-01
In this chapter, we present a speech emotion recognition system to compare several classifiers on the clean speech and noisy speech. Our proposed WD-KNN classifier outperforms the other three KNN-based classifiers at every SNR level and achieves highest accuracy from clean speech to 20dB noisy speech when compared with all other classifiers. Similar to (Neiberg et al, 2006), GMM is a feasible technique for emotion classification on the frame level and the results of GMM are better than perfor...
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 ...
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).
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.
A Statistical Approach for Iris Recognition Using K-NN Classifier
Dolly Choudhary
2013-04-01
Full Text Available Irish recognition has always been an attractive goal for researchers. The identification of the person based on iris recognition is very popular due to the uniqueness of the pattern of iris. Although a number of methods for iris recognition have been proposed by many researchers in the last few years. This paper proposes statistical texture feature based iris matching method for recognition using K-NN classifier. Statistical texture measures such as mean, standard deviation, entropy, skewness etc., and six features are computed of normalized iris image. K-NN classifier matches the input iris with the trained iris images by calculating the Euclidean distance between two irises. The performance of the system is evaluated on 500 iris images, which gives good classification accuracy with reduced FAR/FRR.
Processing and characterizations of BNT-KNN ceramics for actuator applications
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.
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
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.
A Statistical Approach for Iris Recognition Using K-NN Classifier
Dolly Choudhary; Ajay Kumar Singh; Shamik Tiwari
2013-01-01
Irish recognition has always been an attractive goal for researchers. The identification of the person based on iris recognition is very popular due to the uniqueness of the pattern of iris. Although a number of methods for iris recognition have been proposed by many researchers in the last few years. This paper proposes statistical texture feature based iris matching method for recognition using K-NN classifier. Statistical texture measures such as mean, standard deviation, entropy, skewness...
Performance Analysis of kNN on large datasets using CUDA & Pthreads : Comparing between CPU & GPU
Kankatala, Sriram
2015-01-01
Several organizations have large databases which are growing at a rapid rate day by day, which need to be regularly maintained. Content based searches are similar searched based on certain features that are obtained from various multi media data. For various applications like multimedia content retrieval, data mining, pattern recognition, etc., performing the nearest neighbor search is a challenging task in multidimensional data. The important factors in nearest neighbor search kNN are search...
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...
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...
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
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).
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.
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 ...
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.
Lead-free KNN-modified piezoceramics of the system (Li,Na,K)(Nb,Ta,Sb)O3 were prepared by conventional solid-state sintering. The X-ray diffraction patterns revealed a perovskite phase, together with some minor secondary phase, which was assigned to K3LiNb6O17, tetragonal tungsten-bronze (TTB). A structural evolution toward a pure tetragonal structure with the increasing sintering time was observed, associated with the decrease of TTB phase. A correlation between higher tetragonality and higher piezoelectric response was clearly evidenced. Contrary to the case of the LiTaO3 modified KNN, very large abnormal grains with TTB structure were not detected. As a consequence, the simultaneous modification by tantalum and antimony seems to induce during sintering a different behaviour from the one of LiTaO3 modified KNN.
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,...
Evaluation of normalization methods for cDNA microarray data by k-NN classification
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
Evaluation of normalization methods for cDNA microarray data by k-NN classification
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
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.
A ROBUST GA/KNN BASED HYPOTHESIS VERIFICATION SYSTEM FOR VEHICLE DETECTION
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.
Composition studies by kNN procedure with KASCADE-Grande data
KASCADE-Grande, located at Forschungszentrum Karlsruhe, is a multi-detector experiment for the measurement of extensive air showers induced by primary cosmic rays in the energy range of 1014-1018 eV. The ''k-Nearest Neighbours'' (kNN) method is a classification procedure applied for a preliminary study of the cosmic ray composition in this energy range. Simulations of different primary particles are used as reference samples. In order to find for each real event the k Nearest Neighbours in the reference sample, the Mahalanobis distance in the space defined by the choosen observables is calculated. The probability of the event to be part of one of the simulated primary groups is the percentage of the k neighbours belonging to it. An attempt to separate light from heavy primaries in the energy range of KASCADE-Grande is here reported.
Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric
Rumen Andonov
2015-10-01
Full Text Available In this work, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN scheme classifies up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.
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
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...
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.
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...
Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms
Shengyun Liang
2015-11-01
Full Text Available The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers participated in functional movement tests, including walking and sit-to-stand (STS. A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN, pseudo nearest neighbor (PNN, local mean pseudo nearest neighbor (LMPNN classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population.
Performance Analysis of Random Forests with SVM and KNN in Classification of Ancient Kannada Scripts
Soumya A
2014-07-01
Full Text Available Ancient inscriptions which reveal the details of yester years are difficult to interpret by modern readers and efforts are being made in automating such tasks of deciphering historical records. The Kannada script which is used to write in Kannada language has gradually evolved from the ancient script known as Brahmi. Kannada script has traveled a long way from the earlier Brahmi model and has undergone a number of changes during the regimes of Ashoka, Shatavahana, Kadamba, Ganga, Rashtrakuta, Chalukya, Hoysala , Vijayanagara and Wodeyar dynasties. In this paper we discuss on Classification of ancient Kannada Scripts during three different periods Ashoka, Kadamba and Satavahana. A reconstructed grayscale ancient Kannada epigraph image is input, which is binarized using Otsu’s method. Normalized Central and Zernike Moment features are extracted for classification. The RF Classifier designed is tested on handwritten base characters belonging to Ashoka, Satavahana and Kadamba dynasties. For each dynasty, 105 handwritten samples with 35 base characters are considered. The classification rates for the training and testing base characters from Satavahana period, for varying number of trees and thresholds of RF are determined. Finally a Comparative analysis of the Classification rates is made for the designed RF with SVM and k-NN classifiers, for the ancient Kannada base characters from 3 different eras Ashoka, Kadamba and Satavahana period.
Improved Apriori and KNN approach for Virtual machine based intrusion detection
Suneetha Valluru#1 , Mrs N. Rajeswari#2
2012-10-01
Full Text Available Nowadays, as information systems are usually more accessible to the world wide web, the advantage of secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs that based on sophisticated algorithms as an alternative to current signature-base detections are really in demand. Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS, may discover the new pattern due to massive network data, to scale back the workload of the manual compilation intrusion behavior patterns and normal behavior patterns.Virtualization is now a more popular service hosting platform. Recently, intrusion detection systems (IDSs which utilize virtualization are now introduced. A particular challenge inside current virtualization-based IDS systems is considered in this project. In this particular proposed system a new chi-square based feature selection that evaluates the relative importance of individual features. After feature selection proposed techniques like KNN and Modified apriori are applied on the data with less false positive rates.
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.
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...
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
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.
Algebraic mesh quality metrics
KNUPP,PATRICK
2000-04-24
Quality metrics for structured and unstructured mesh generation are placed within an algebraic framework to form a mathematical theory of mesh quality metrics. The theory, based on the Jacobian and related matrices, provides a means of constructing, classifying, and evaluating mesh quality metrics. The Jacobian matrix is factored into geometrically meaningful parts. A nodally-invariant Jacobian matrix can be defined for simplicial elements using a weight matrix derived from the Jacobian matrix of an ideal reference element. Scale and orientation-invariant algebraic mesh quality metrics are defined. the singular value decomposition is used to study relationships between metrics. Equivalence of the element condition number and mean ratio metrics is proved. Condition number is shown to measure the distance of an element to the set of degenerate elements. Algebraic measures for skew, length ratio, shape, volume, and orientation are defined abstractly, with specific examples given. Combined metrics for shape and volume, shape-volume-orientation are algebraically defined and examples of such metrics are given. Algebraic mesh quality metrics are extended to non-simplical elements. A series of numerical tests verify the theoretical properties of the metrics defined.
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
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...
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...
Regina Lopes Schimitt
2011-01-01
Full Text Available INTRODUÇÃO: O ritmo social é um conceito que integra a relação entre Zeitgebers (sincronizadores sociais e os marcadores de tempo endógenos, e pode ser avaliado com a Escala de Ritmo Social (Social Rhythm Metric-17, SRM-17. O objetivo deste estudo foi realizar a adaptação da versão brasileira da SRM-17 para o português angolano, comparando as duas escalas em populações que utilizam o mesmo idioma mas apresentam diferenças culturais. MÉTODOS: A versão brasileira da SRM-17 foi submetida à avaliação de 10 estudantes universitários angolanos, que analisaram o grau de clareza de cada um dos 15 itens do instrumento usando uma escala visual analógica de 10 cm e propuseram modificações ao texto. Foi realizada revisão dos resultados para a elaboração da versão final, bem como prova de leitura e relatório final. RESULTADOS: A versão final angolana manteve uma equivalência de itens com relação à versão em português brasileiro. A versão avaliada demonstrou um grau satisfatório de clareza e equivalência semântica na maioria dos itens. Porém, alguns itens apresentaram um escore na clareza inferior à média aritmética de compreensão global do instrumento (8,38±1,0. CONCLUSÃO: Apesar de o português ser o idioma oficial nos dois países, há diferenças culturais significativas nas duas populações. Este trabalho apresenta uma versão adaptada à realidade angolana de um instrumento específico para aferir ritmo social. O processo de adaptação transcultural deve efetivar-se com estudos de validação do instrumento final em uma amostra maior da população, onde também poderão ser avaliadas as equivalências operacional, de medida e funcional.INTRODUCTION: Social rhythm is a concept that correlates social Zeitgebers (synchronizers with endogenous markers of time, and can be assessed with the Social Rhythm Metric-17 (SRM-17. The aim of this study was to adapt the Brazilian version of the SRM-17 to Angolan
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...
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
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.
Metrics, Media and Advertisers: Discussing Relationship
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.
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.
Surveillance Metrics Sensitivity Study
Bierbaum, R; Hamada, M; Robertson, A
2011-11-01
In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculations and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.
Surveillance metrics sensitivity study.
Hamada, Michael S. (Los Alamos National Laboratory); Bierbaum, Rene Lynn; Robertson, Alix A. (Lawrence Livermore Laboratory)
2011-09-01
In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculations and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.
Metrics for Probabilistic Geometries
Tosi, Alessandra; Hauberg, Søren; Vellido, Alfredo; Lawrence, Neil D.
We investigate the geometrical structure of probabilistic generative dimensionality reduction models using the tools of Riemannian geometry. We explicitly define a distribution over the natural metric given by the models. We provide the necessary algorithms to compute expected metric tensors where...
Metrics for Secretarial, Stenography.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of secretarial, stenography students, this instructional package is one of three for the business and office occupations cluster, 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,…
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of students interested in transportation, this instructional package is one of five for the marketing and distribution cluster, 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,…
Metrics for Food Distribution.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of students interested in food distribution, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…
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…
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.
面向轨迹数据流的KNN近似查询%KNN Approximate Query for Trajectory Data Stream
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
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 .
M. Punithavalli
2012-01-01
Full Text Available The high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so that the testing process can concentrate only on those regions. This will improve the testing process and indirectly help to reduce development life cycle, project risks, resource and infrastructure costs. Measuring quality using software metrics for fault identification is gaining wide interest in software industry as they help to reduce time and cost. Existing system use either traditional simple metrics or object oriented metrics during fault detection combined with single classifier prediction system. This study combines the use of simple and object oriented metrics and uses a multiple classifier prediction system to identify module faults. In this study, a total of 20 metrics combining both traditional and OO metrics are used for fault detection. To analyze the performance of these metrics on fault module detection, the study proposes the use of ensemble classifiers that uses three frequently used classifiers, Back Propagation Neural Network (BPNN, Support Vector Machine (SVM and K-Nearest Neighbour (KNN. A novel classifier aggregation method is proposed to combine the classification results. Four methods, Sequential Selection, Random Selection with No Replacement, Selection with Bagging and Selection with Boosting, are used to generate different variants of input dataset. The three classifiers were grouped together as 2-classifier and 3-classifier prediction ensemble models. A total of 16 ensemble models were proposed for fault prediction. The performance of the proposed prediciton models was analyzed using accuracy, precision, recall and F
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.
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'.
2007-01-01
Full Text Available Many software and IT projects fail in completing theirs objectives because different causes of which the management of the projects has a high weight. In order to have successfully projects, lessons learned have to be used, historical data to be collected and metrics and indicators have to be computed and used to compare them with past projects and avoid failure to happen. This paper presents some metrics that can be used for the IT project management.
Mass Customization Measurements Metrics
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....
Ion IVAN
2007-09-01
Full Text Available The objectives of IT projects are presented. The quality requirements that these projects must fulfill are established. Quality and evaluation indicators for running IT projects are built and verified. Project quality characteristics are presented and discussed. Model refinement for IT project metrics is treated and a software structure is proposed. For an IT project which is designed for software development, quality evaluation and project implementation mode metrics are used.
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.
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...
Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm
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.
Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm
Han, Soohee; Kim, Junghwan; Park, Choung-Hwan; Yoon, Hee-Cheon; Heo, Joon
2009-01-01
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. PMID:22408540
Metric derived numbers and continuous metric differentiability via homeomorphisms
Duda, Jakub; Maleva, Olga
2006-01-01
We define the notions of unilateral metric derivatives and ``metric derived numbers'' in analogy with Dini derivatives (also referred to as ``derived numbers'') and establish their basic properties. We also prove that the set of points where a path with values in a metric space with continuous metric derivative is not ``metrically differentiable'' (in a certain strong sense) is $\\sigma$-symmetrically porous and provide an example of a path for which this set is uncountable. In the second part...
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...
On Ptolemaic metric simplicial complexes
Buckley, S M; Wraith, D J
2009-01-01
We show that under certain mild conditions, a metric simplicial complex which satisfies the Ptolemy inequality is a CAT(0) space. Ptolemy's inequality is closely related to inversions of metric spaces. For a large class of metric simplicial complexes, we characterize those which are isometric to Euclidean space in terms of metric inversions.
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.
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_...
Evaluation metrics for biostatistical and epidemiological collaborations.
Rubio, Doris McGartland; Del Junco, Deborah J; Bhore, Rafia; Lindsell, Christopher J; Oster, Robert A; Wittkowski, Knut M; Welty, Leah J; Li, Yi-Ju; Demets, Dave
2011-10-15
Increasing demands for evidence-based medicine and for the translation of biomedical research into individual and public health benefit have been accompanied by the proliferation of special units that offer expertise in biostatistics, epidemiology, and research design (BERD) within academic health centers. Objective metrics that can be used to evaluate, track, and improve the performance of these BERD units are critical to their successful establishment and sustainable future. To develop a set of reliable but versatile metrics that can be adapted easily to different environments and evolving needs, we consulted with members of BERD units from the consortium of academic health centers funded by the Clinical and Translational Science Award Program of the National Institutes of Health. Through a systematic process of consensus building and document drafting, we formulated metrics that covered the three identified domains of BERD practices: the development and maintenance of collaborations with clinical and translational science investigators, the application of BERD-related methods to clinical and translational research, and the discovery of novel BERD-related methodologies. In this article, we describe the set of metrics and advocate their use for evaluating BERD practices. The routine application, comparison of findings across diverse BERD units, and ongoing refinement of the metrics will identify trends, facilitate meaningful changes, and ultimately enhance the contribution of BERD activities to biomedical research. PMID:21284015
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.
Kerr metric, static observers and Fermi coordinates
The coordinate transformation which maps the Kerr metric written in standard Boyer-Lindquist coordinates to its corresponding form adapted to the natural local coordinates of an observer at rest at a fixed position in the equatorial plane, i.e., Fermi coordinates for the neighbourhood of a static observer world line, is derived and discussed in a way which extends to any uniformly circularly orbiting observer there
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
3D Face Recognition based on Radon Transform, PCA, LDA using KNN and SVM
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.
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
Teukolsky, Saul A.
2015-06-01
This review describes the events leading up to the discovery of the Kerr metric in 1963 and the enormous impact the discovery has had in the subsequent 50 years. The review discusses the Penrose process, the four laws of black hole mechanics, uniqueness of the solution, and the no-hair theorems. It also includes Kerr perturbation theory and its application to black hole stability and quasi-normal modes. The Kerr metric's importance in the astrophysics of quasars and accreting stellar-mass black hole systems is detailed. A theme of the review is the ‘miraculous’ nature of the solution, both in describing in a simple analytic formula the most general rotating black hole, and in having unexpected mathematical properties that make many calculations tractable. Also included is a pedagogical derivation of the solution suitable for a first course in general relativity.
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...
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...
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...
Weighted metric multidimensional scaling
Greenacre, Michael J.
2004-01-01
This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide...
Paul E. Roege; Zachary A. Collier; James Mancillas; John A. McDonagh; Igor Linkov
2014-09-01
Energy lies at the backbone of any advanced society and constitutes an essential prerequisite for economic growth, social order and national defense. However there is an Achilles heel to today?s energy and technology relationship; namely a precarious intimacy between energy and the fiscal, social, and technical systems it supports. Recently, widespread and persistent disruptions in energy systems have highlighted the extent of this dependence and the vulnerability of increasingly optimized systems to changing conditions. Resilience is an emerging concept that offers to reconcile considerations of performance under dynamic environments and across multiple time frames by supplementing traditionally static system performance measures to consider behaviors under changing conditions and complex interactions among physical, information and human domains. This paper identifies metrics useful to implement guidance for energy-related planning, design, investment, and operation. Recommendations are presented using a matrix format to provide a structured and comprehensive framework of metrics relevant to a system?s energy resilience. The study synthesizes previously proposed metrics and emergent resilience literature to provide a multi-dimensional model intended for use by leaders and practitioners as they transform our energy posture from one of stasis and reaction to one that is proactive and which fosters sustainable growth.
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)
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.
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.
Metric-torsional conformal gravity
When in general geometric backgrounds the metric is accompanied by torsion, the metric conformal properties should correspondingly be followed by analogous torsional conformal properties; however a combined metric torsional conformal structure has never been found which provides a curvature that is both containing metric-torsional degree of freedom and conformally invariant: in this Letter we construct such a metric-torsional conformal curvature. We proceed by building the most general action, then deriving the most general system of field equations; we check their consistency by showing that both conservation laws and trace condition are verified. Final considerations and comments are outlined.
Heidorn, Thomas
1999-01-01
Während die Markpreisrisiken (Zinsen, Aktien und Währungen) mit Hilfe des RiskMetrics-Ansatzes gut beschrieben werden können und dafür relativ überzeugende Derivate zur Absicherung unerwünschter Risiken zur Verfügung stehen, hat diese Entwicklung im Kreditbereich erst begonnen. Bei der Bewertung von Ausfällen konkurrieren einerseits optionstheoretische Ansätze mit der Möglichkeit, historische Ausfallwahrscheinlichkeiten für die Bewertung von Kreditrisiken zu benutzen. Dieser Ansatz für eine K...
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...
Camanho, Xián O.; Dadhich, Naresh; Molina, Alfred
2015-09-01
We study pure Lovelock vacuum and perfect fluid equations for Kasner-type metrics. These equations correspond to a single Nth 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 also comment on a closely related family of exponential solutions and on the possibility of solutions with complex Kasner exponents. We show that the latter imply the existence of closed timelike curves in the geometry.
Completion of a Dislocated Metric Space
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.
Clarke, Brian
2011-01-01
We consider geometries on the space of Riemannian metrics conformally equivalent to the widely studied Ebin L^2 metric. Among these we characterize a distinguished metric that can be regarded as a generalization of Calabi's metric on the space of K\\"ahler metrics to the space of Riemannian metrics, and we study its geometry in detail. Unlike the Ebin metric, the geodesic equation involves non-local terms, and we solve it explicitly by using a constant of the motion. We then determine its completion, which gives the first example of a metric on the space of Riemannian metrics whose completion is strictly smaller than that of the Ebin metric.
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...
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 ...
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.
Metric adjusted skew information
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...
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
Canonical metrics on complex manifold
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
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.
Metric-adjusted skew information
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 < p = 2 of the WYD-information is a special case of...... (unbounded) metric-adjusted skew information....
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
50+ Metrics for Calendar Mining
Kelemen, Zádor Dániel; Miglász, Dániel
2016-01-01
In this report we propose 50+ metrics which can be measured by organizations in order to identify improvements in various areas such as meeting efficiency, capacity planning or leadership skills, just to new a few. The notion of calendar mining is introduced and support is provided for performing the measurement by a reference data model and queries for all metrics defined.
Extending Cosmology: The Metric Approach
Mendoza, Sergio
2012-01-01
Comment: 2012, Extending Cosmology: The Metric Approach, Open Questions in Cosmology; Review article for an Intech "Open questions in cosmology" book chapter (19 pages, 3 figures). Available from: http://www.intechopen.com/books/open-questions-in-cosmology/extending-cosmology-the-metric-approach
Metrics for Soft Goods Merchandising.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of students interested in soft goods merchandising, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…
Metrics for Hard Goods Merchandising.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of students interested in hard goods merchandising, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…
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...
The Conformal Flow of Metrics and the General Penrose Inequality
Han, Qing
2014-01-01
In this note we show how to adapt Bray's conformal flow of metrics, so that it may be applied to the Penrose inequality for general initial data sets of the Einstein equations. This involves coupling the conformal flow with the generalized Jang equation.
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
Variable metric conjugate gradient methods
Barth, T.; Manteuffel, T.
1994-07-01
1.1 Motivation. In this paper we present a framework that includes many well known iterative methods for the solution of nonsymmetric linear systems of equations, Ax = b. Section 2 begins with a brief review of the conjugate gradient method. Next, we describe a broader class of methods, known as projection methods, to which the conjugate gradient (CG) method and most conjugate gradient-like methods belong. The concept of a method having either a fixed or a variable metric is introduced. Methods that have a metric are referred to as either fixed or variable metric methods. Some relationships between projection methods and fixed (variable) metric methods are discussed. The main emphasis of the remainder of this paper is on variable metric methods. In Section 3 we show how the biconjugate gradient (BCG), and the quasi-minimal residual (QMR) methods fit into this framework as variable metric methods. By modifying the underlying Lanczos biorthogonalization process used in the implementation of BCG and QMR, we obtain other variable metric methods. These, we refer to as generalizations of BCG and QMR.
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.
Issues in Benchmark Metric Selection
Crolotte, Alain
It is true that a metric can influence a benchmark but will esoteric metrics create more problems than they will solve? We answer this question affirmatively by examining the case of the TPC-D metric which used the much debated geometric mean for the single-stream test. We will show how a simple choice influenced the benchmark and its conduct and, to some extent, DBMS development. After examining other alternatives our conclusion is that the “real” measure for a decision-support benchmark is the arithmetic mean.
Daylight metrics and energy savings
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.
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.
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.
Mining metrics for buried treasure
Konkowski, D A
2004-01-01
The same but different: That might describe two metrics. On the surface CLASSI may show two metrics are locally equivalent, but buried beneath one may be a wealth of further structure. This was beautifully describeed in a paper by M.A.H. MacCallum in 1998. Here I will illustrate the effect with two flat metrics -- one describing ordinary Minkowski spacetime and the other describing a three-parameter family of Gal'tsov-Letelier-Tod spacetimes. I will dig out the beautiful hidden classical singularity structure of the latter (a structure first noticed by Tod in 1994) and then show how quantum considerations can illuminate the riches. I will then discuss how quantum structure can help us understand classical singularities and metric parameters in a variety of exact solutions mined from the Exact Solutions book.
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)
Metrical Diophantine approximation for quaternions
Dodson, Maurice
2011-01-01
The metrical theory of Diophantine approximation for quaternions is developed using recent results in the general theory. In particular, Quaternionic analogues of the classical theorems of Khintchine, Jarnik and Jarnik-Besicovitch are established.
Metrical Diophantine approximation for quaternions
Dodson, Maurice; Everitt, Brent
2014-11-01
Analogues of the classical theorems of Khintchine, Jarnik and Jarnik-Besicovitch in the metrical theory of Diophantine approximation are established for quaternions by applying results on the measure of general `lim sup' sets.
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.
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...
Nonlocal Metric Realizations of MOND
Woodard, R. P.
2014-01-01
I discuss relativistic extensions of MOND in which the metric couples normally to matter. I argue that MOND might be a residual effect from the vacuum polarization of infrared gravitons produced during primordial inflation. If so, MOND corrections to the gravitational field equations would be nonlocal. Nonocality also results when one constructs metric field equations which reproduce the Tully-Fisher relation, along with sufficient weak lensing. I give the full field equations for the simples...
Phantom metrics with Killing spinors
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.
Validity of Ligand Efficiency Metrics
Murray, Christopher W; Erlanson, Daniel A.; Hopkins, Andrew L.; Keserü, György M; Leeson, Paul D.; Rees, David C.; Reynolds, Charles H.; Richmond, Nicola J.
2014-01-01
A recent viewpoint article (Improving the plausibility of success with inefficient metrics. ACS Med. Chem. Lett.2014, 5, 2–5) argued that the standard definition of ligand efficiency (LE) is mathematically invalid. In this viewpoint, we address this criticism and show categorically that the definition of LE is mathematically valid. LE and other metrics such as lipophilic ligand efficiency (LLE) can be useful during the multiparameter optimization challenge faced by med...
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...
Candelas, Philip; McOrist, Jock
2016-01-01
Heterotic vacua of string theory are realised, at large radius, by a compact threefold with vanishing first Chern class together with a choice of stable holomorphic vector bundle. These form a wide class of potentially realistic four-dimensional vacua of string theory. Despite all their phenomenological promise, there is little understanding of the metric on the moduli space of these. What is sought is the analogue of special geometry for these vacua. The metric on the moduli space is important in phenomenology as it normalises D-terms and Yukawa couplings. It is also of interest in mathematics, since it generalises the metric, first found by Kobayashi, on the space of gauge field connections, to a more general context. Here we construct this metric, correct to first order in alpha', in two ways: first by postulating a metric that is invariant under background gauge transformations of the gauge field, and also by dimensionally reducing heterotic supergravity. These methods agree and the resulting metric is Ka...
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
Method Points: towards a metric for method complexity
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.
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.
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
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。
Clarke, Brian; Rubinstein, Yanir A.
2011-01-01
We consider geometries on the space of Riemannian metrics conformally equivalent to the widely studied Ebin L^2 metric. Among these we characterize a distinguished metric that can be regarded as a generalization of Calabi's metric on the space of K\\"ahler metrics to the space of Riemannian metrics, and we study its geometry in detail. Unlike the Ebin metric, the geodesic equation involves non-local terms, and we solve it explicitly by using a constant of the motion. We then determine its comp...
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 ...
Metrics for measuring net-centric data strategy implementation
Kroculick, Joseph B.
2010-04-01
An enterprise data strategy outlines an organization's vision and objectives for improved collection and use of data. We propose generic metrics and quantifiable measures for each of the DoD Net-Centric Data Strategy (NCDS) data goals. Data strategy metrics can be adapted to the business processes of an enterprise and the needs of stakeholders in leveraging the organization's data assets to provide for more effective decision making. Generic metrics are applied to a specific application where logistics supply and transportation data is integrated across multiple functional groups. A dashboard presents a multidimensional view of the current progress to a state where logistics data shared in a timely and seamless manner among users, applications, and systems.
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.
Learning Objects Reusability Effectiveness Metric (LOREM
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.
Synthesis Array Topology Metrics in Location Characterization
Shanmugha Sundaram, GA
2015-08-01
Towards addressing some of the fundamental mysteries in physics at the micro- and macro-cosm level, that form the Key Science Projects (KSPs) for the Square Kilometer Array (SKA; such as Probing the Dark Ages and the Epoch of Reionization in the course of an Evolving Universe; Galaxy Evolution, Cosmology, and Dark Energy; and the Origin and evolution of Cosmic Magnetism) a suitable interfacing of these goals has to be achieved with its optimally designed array configuration, by means of a critical evaluation of the radio imagingcapabilities and metrics. Of the two forerunner sites, viz. Australia and South Africa, where pioneering advancements to state-of-the-art in synthesis array radio astronomy instrumentation are being attempted in the form of pathfinders to the SKA, for its eventual deployment, a diversity of site-dependent topology and design metrics exists. Here, the particular discussion involves those KSPs that relate to galactic morphology and evolution, and explores their suitability as a scientific research goal from the prespective of the location-driven instrument design specification. Relative merits and adaptability with regard to either site shall be presented from invoking well-founded and established array-design and optimization principles designed into a customized software tool.
Metrics correlation and analysis service (MCAS)
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)
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.
Rainbow metric from quantum gravity
Assaniousssi, Mehdi; Lewandowski, Jerzy
2014-01-01
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 space-time. Under general assumptions, we discover that the quantum space-time on which the field propagates can be replaced by a classical space-time, 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 behavior of high-energy particles on quantum space-time relies only on the assumption that the quantum space-time is described by a wave-function $\\Psi_o$ in a Hilbert space $\\mathcal{H}_G$.
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
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.
Squared Metric Facility Location Problem
Fernandes, Cristina G; Miyazawa, Flávio K; Pedrosa, Lehilton L C
2011-01-01
Jain et al. proposed two well-known algorithms for the Metric Facility Location Problem (MFLP), that achieve approximation ratios of 1.861 and 1.61. Mahdian et al. combined the latter algorithm with scaling and greedy augmentation techniques, obtaining a 1.52-approximation for the MFLP. We consider a generalization of the Squared Euclidean Facility Location Problem, when the distance function is a squared metric, which we call Squared Metric Facility Location Problem (SMFLP). We show that the algorithms of Jain et al. and of Mahdian et al., when applied to this variant of the facility location, achieve approximation ratios of 2.87, 2.43, and 2.17, respectively. It is shown that, for the SMFLP, there is no 2.04-approximation algorithm, assuming P $\
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.
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.
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
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.
Kerr-Schild--Kundt Metrics are Universal
Gurses, Metin; Tekin, Bayram
2016-01-01
Universal metrics are the metrics that solve generic gravity theories which defined by covariant field equations built on the powers of the contractions and the covariant derivatives of the Riemann tensor. Here, we show that the Kerr-Schild--Kundt class metrics are universal extending the rather scarce family of universal metrics in the literature. Besides being interesting on their own, these metrics can provide consistent background for quantum field theory at extremely high energies.
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...
S-curvature of isotropic Berwald metrics
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.
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.
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.
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
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.
Bartholdi, Laurent; Smale, Nat; Smale, Steve; Baker, Anthony W
2009-01-01
Hodge theory is a beautiful synthesis of geometry, topology, and analysis, which has been developed in the setting of Riemannian manifolds. On the other hand, spaces of images, which are important in the mathematical foundations of vision and pattern recognition, do not fit this framework. This motivates us to develop a version of Hodge theory on metric spaces with a probability measure. We believe that this constitutes a step towards understanding the geometry of vision. The appendix by Anthony Baker provides a separable, compact metric space with infinite dimensional \\alpha-scale homology.
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.
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...
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...
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...
Hofer's metrics and boundary depth
Usher, Michael
2011-01-01
We show that if (M,\\omega) is a closed symplectic manifold which admits a nontrivial Hamiltonian vector field all of whose contractible closed orbits are constant, then Hofer's metric on the group of Hamiltonian diffeomorphisms of (M,\\omega) has infinite diameter, and indeed admits infinite-dimensional quasi-isometrically embedded normed vector spaces. A similar conclusion applies to Hofer's metric on various spaces of Lagrangian submanifolds, including those Hamiltonian-isotopic to the diagonal in M x M when M satisfies the above dynamical condition. To prove this, we use the properties of a Floer-theoretic quantity called the boundary depth, which measures the nontriviality of the boundary operator on the Floer complex in a way that encodes robust symplectic-topological information.
On metrically complete Bruhat-Tits buildings
Martin, Benjamin; Schillewaert, Jeroen; Steinke, Günter F.; Struyve, Koen
2011-01-01
Metrical completeness for Bruhat-Tits buildings is a natural and useful condition. In this paper we determine which Bruhat-Tits buildings are metrically complete up to certain cases involving infinite-dimensionality and residue characteristic two.
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...
Horan, Patrick; Frew, Andrew
2007-01-01
The priority of the research is thus to establish which criteria are important for destination websites and to determine a mechanism for their measurement. These criteria are divided into both macro- and micro- level metrics which each combine to provide information that is actionable from a business’ perspective. This work lays the foundation for the anticipated outcome of this research, a robust methodology for measuring the effectiveness of destination websites coupled with a suite of acti...
Metric reconstruction from Weyl scalars
The Kerr geometry has remained an elusive world in which to explore physics and delve into the more esoteric implications of general relativity. Following the discovery, by Kerr in 1963, of the metric for a rotating black hole, the most major advance has been an understanding of its Weyl curvature perturbations based on Teukolsky's discovery of separable wave equations some ten years later. In the current research climate, where experiments across the globe are preparing for the first detection of gravitational waves, a more complete understanding than concerns just the Weyl curvature is now called for. To understand precisely how comparatively small masses move in response to the gravitational waves they emit, a formalism has been developed based on a description of the whole spacetime metric perturbation in the neighbourhood of the emission region. Presently, such a description is not available for the Kerr geometry. While there does exist a prescription for obtaining metric perturbations once curvature perturbations are known, it has become apparent that there are gaps in that formalism which are still waiting to be filled. The most serious gaps include gauge inflexibility, the inability to include sources-which are essential when the emitting masses are considered-and the failure to describe the l = 0 and 1 perturbation properties. Among these latter properties of the perturbed spacetime, arising from a point mass in orbit, are the perturbed mass and axial component of angular momentum, as well as the very elusive Carter constant for non-axial angular momentum. A status report is given on recent work which begins to repair these deficiencies in our current incomplete description of Kerr metric perturbations
Multi-Metric Sustainability Analysis
Cowlin, S.; Heimiller, D.; Macknick, J.; Mann, M.; Pless, J.; Munoz, D.
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.
Developing a quality assurance metric
Love, Steve; Scoble, Rosa
2006-01-01
Abstract There are a variety of techniques that lecturers can use to get feedback on their teaching - for example, module feedback and coursework results. However, a question arises about how reliable and valid are the content that goes into these quality assurance metrics. The aim of this article is to present a new approach for collecting and analysing qualitative feedback from students that could be used...
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...
Almost contact metric 3-submersions
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.
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
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
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.
Obtención de polvos cerámicos de BNKT-KNN por el método Pechini
Yasnó, J. P.
2013-10-01
Full Text Available Pechini method was used in order to obtain fine ceramic and single-phase powders for a lead-free ferroelectric system 0,97[(Bi1/2Na1/21-x(Bi1/2K1/2xTiO3]-0,03[(Na1/2K1/2NbO3]or BNKT-KNN (x = 0.00, 0.18, 0.21, 0.24, 0.27. This method allowed obtaining powders with 100 % perovskite phase, which was confirmed by X-ray diffraction, for this particular system in all the studied stoichiometries using temperature as low as 600 ºC. The effects on the bonds present in the structure due to variation of the stoichiometry, Na-K, were determined using infrared spectroscopy, FT-IR. Irregular nanoparticles were observed by scanning electron microscopy.El método Pechini fue utilizado para obtener polvos cerámicos finos y monofásicos del sistema ferroeléctrico libre de plomo 0,97[(Bi1/2Na1/21-x(Bi1/2K1/2xTiO3]-0,03[(Na1/2K1/2NbO3] ó BNKT-KNN (x = 0.00, 0.18, 0.21, 0.24, 0.27. Este método permitió la obtención de polvos con 100 % de fase perovskita, para el sistema de interés en todas las estequiometrias estudiadas, a una temperatura tan baja como 600 ºC, lo que fue confirmado por difracción de rayos X. Por medio de espectroscopia infrarroja, FT-IR, se pudo determinar cómo afecta la variación de la estequiometria, Na-K, los enlaces presentes en la estructura. Mediante microscopia electrónica de barrido se observaron partículas nanométricas irregulares.
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.
Toward an efficient objective metric based on perceptual criteria
Quintard, Ludovic; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine
2008-01-01
Quality assessment is a very challenging problem and will still as is since it is difficult to define universal tools. So, subjective assessment is one adapted way but it is tedious, time consuming and needs normalized room. Objective metrics can be with reference, with reduced reference and with no-reference. This paper presents a study carried out for the development of a no-reference objective metric dedicated to the quality evaluation of display devices. Initially, a subjective study has been devoted to this problem by asking a representative panel (15 male and 15 female; 10 young adults, 10 adults and 10 seniors) to answer questions regarding their perception of several criteria for quality assessment. These quality factors were hue, saturation, contrast and texture. This aims to define the importance of perceptual criteria in the human judgment of quality. Following the study, the factors that impact the quality evaluation of display devices have been proposed. The development of a no-reference objective metric has been performed by using statistical tools allowing to separate the important axes. This no-reference metric based on perceptual criteria by integrating some specificities of the human visual system (HVS) has a high correlation with the subjective data.
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.
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
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.
Product Operations Status Summary Metrics
Takagi, Atsuya; Toole, Nicholas
2010-01-01
The Product Operations Status Summary Metrics (POSSUM) computer program provides a readable view into the state of the Phoenix Operations Product Generation Subsystem (OPGS) data pipeline. POSSUM provides a user interface that can search the data store, collect product metadata, and display the results in an easily-readable layout. It was designed with flexibility in mind for support in future missions. Flexibility over various data store hierarchies is provided through the disk-searching facilities of Marsviewer. This is a proven program that has been in operational use since the first day of the Phoenix mission.
Anabalón, Andrés; Batista, Carlos
2016-03-01
In four dimensions, the most general metric admitting two commuting Killing vectors and a rank-two Killing tensor can be parametrized by ten arbitrary functions of a single variable. We show that picking a special vierbein, reducing the system to eight functions, implies the existence of two geodesic and share-free, null congruences, generated by two principal null directions of the Weyl tensor. Thus, if the spacetime is an Einstein manifold, the Goldberg-Sachs theorem implies it is Petrov type D, and by explicit construction, is in the Carter class. Hence, our analysis provides a straightforward connection between the most general integrable structure and the Carter family of spacetimes.
Anabalon, Andres
2016-01-01
In four dimensions, the most general metric admitting two Killing vectors and a rank-two Killing tensor can be parameterized by ten arbitrary functions of a single variable. We show that picking a special vierbien, reducing the system to eight functions, implies the existence of two geodesic and share-free, null congruences, generated by two principal null directions of the Weyl tensor. Thus, if the spacetime is an Einstein manifold, the Goldberg-Sachs theorem implies it is Petrov type D, and by explicit construction, is in the Carter class. Hence, our analysis provide an straightforward connection between the most general integrable structure and the Carter family of spacetimes.
This is a corrected and essentially extended version of the unpublished manuscript by Y Nutku and M Sheftel which contains new results. It is proposed to be published in honour of Y Nutku’s memory. All corrections and new results in sections 1, 2 and 4 are due to M Sheftel. We present new anti-self-dual exact solutions of the Einstein field equations with Euclidean and neutral (ultra-hyperbolic) signatures that admit only one rotational Killing vector. Such solutions of the Einstein field equations are determined by non-invariant solutions of Boyer–Finley (BF) equation. For the case of Euclidean signature such a solution of the BF equation was first constructed by Calderbank and Tod. Two years later, Martina, Sheftel and Winternitz applied the method of group foliation to the BF equation and reproduced the Calderbank–Tod solution together with new solutions for the neutral signature. In the case of Euclidean signature we obtain new metrics which asymptotically locally look like a flat space and have a non-removable singular point at the origin. In the case of ultra-hyperbolic signature there exist three inequivalent forms of metric. Only one of these can be obtained by analytic continuation from the Calderbank–Tod solution whereas the other two are new. (paper)
Taxonomy for Information Privacy Metrics
Rasika Dayarathna
2011-10-01
Full Text Available A comprehensive privacy framework is essential for the progress of the information privacy field. Some practical implications of a comprehensive framework are laying foundation for building information privacy metrics and having fruitful discussions. Taxonomy is an essential step in building a framework. This research study attempts to build taxonomy for the information privacy domain based on empirical data. The classical grounded theory approach introduced by Glaser was applied and incidents reported by the International Association of Privacy Professionals (IAPP are used for building the taxonomy. These incidents include privacy related current research works, data breaches, personal views, interviews, and technological innovations. TAMZAnalyzer, an open source qualitative data analysis tool, was used in coding, keeping memos, sorting, and creating categories. The taxonomy is presented in seven themes and several categories including legal, technical, and ethical aspects. The findings of this study helps practitioners understand and discuss the subjects and academia work toward building a comprehensive framework and metrics for the information privacy domain
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.
The metric space of geodesic laminations on a surface: I
Zhu, Xiaodong; Bonahon, Francis
2003-01-01
We consider the space of geodesic laminations on a surface, endowed with the Hausdorff metric d_H and with a variation of this metric called the d_log metric. We compute and/or estimate the Hausdorff dimensions of these two metrics. We also relate these two metrics to another metric which is combinatorially defined in terms of train tracks.
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...
A Brief Overview Of Software Testing Metrics
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.
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.
Color Ratios and Chromatic Adaptation
Finlayson, Graham D.; Süsstrunk, Sabine
2002-01-01
In this paper, the performance of chromatic adaptation transforms based on stable color ratios is investigated.It was found that for three different sets of reflectance data, their performance was not statistically different from CMCCAT2000,when applying the chromatic adaptation transforms to Lam’s corresponding color data set and using a perceptual error metric of CIE Delta E94.The sensors with the best color ratio stability are much sharper and more de-correlated than the CMCCAT2000 sensors...
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...
Evaluating the value of web metrics
Riihimäki, Tommi
2014-01-01
Objectives of the Study: The unique measurability of websites allows the collection of detailed information about the behavior and characteristics of website visitors. This thesis examines the value of different web metrics based on the behavior of website visitors. The objective is to develop and test a method for identifying key metrics that are the most valuable for site developers to follow. The key web metrics are expected to contain the most useful and relevant information about the...
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 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.
Radiation-dominated area metric cosmology
Schuller, F.; Wohlfarth, M.
2007-01-01
We provide further crucial support for a refined, area metric structure of spacetime. On the basis of 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 ...
Improved characterization of the Kerr metric
The condition of asymptotic flatness is removed from Simon's characterization of the Kerr metric by vanishing of the complexified Bach tensor. The solution of the stationary vacuum equations of relativity is given for a vanishing Simon tensor. One class of metrics consists of three Ehlersrotated Levi-Civita metrics, which have conformally flat three-spaces. The second class contains Hoffmann's planefronted standing wave solutions, and the third includes the three-parameter Kerr-NUT space-time. (author)
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...
SOFTWARE METRICS VALIDATION METHODOLOGIES IN SOFTWARE ENGINEERING
K.P. Srinivasan; T. Devi
2014-01-01
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...
Generalized tolerance sensitivity and DEA metric sensitivity
Luka Neralić; Richard E. Wendell
2015-01-01
This paper considers the relationship between Tolerance sensitivity analysis in optimization and metric sensitivity analysis in Data Envelopment Analysis (DEA). Herein, we extend the results on the generalized Tolerance framework proposed by Wendell and Chen and show how this framework includes DEA metric sensitivity as a special case. Further, we note how recent results in Tolerance sensitivity suggest some possible extensions of the results in DEA metric sensitivity.
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....
Inertia Manipulation through Metric Patching
Waite, D
2001-01-01
This paper will present the exact solution for the stress-energy tensor of a spherical matter shell of finite thickness that will patch together different metrics at the boundaries of the shell. The choice of vacuum field solutions for the shell exterior and hollow interior that we make will allow us to manipulate the inertial state of an object within the shell. The choice will cause it to be in a state of acceleration with the shell relative to an external observer for an indefinite time. The stress-energy tensor's solution results in zero ship frame energy requirements, and only finite stress requirements, and we show how any WEC violation can be avoided.
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
About the possibility of a generalized metric
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
Structure of stationary and axisymmetric metrics
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
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 ...
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.
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
Using Genetic Algorithms for Building Metrics of Collaborative Systems
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
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.
Ricci flow and the metric completion of the space of Kahler metrics
Clarke, Brian; Rubinstein, Yanir A.
2011-01-01
We consider the space of Kahler metrics as a Riemannian submanifold of the space of Riemannian metrics, and study the associated submanifold geometry. In particular, we show that the intrinsic and extrinsic distance functions are equivalent. We also determine the metric completion of the space of Kahler metrics, making contact with recent generalizations of the Calabi-Yau Theorem due to Dinew, Guedj-Zeriahi, and Kolodziej. As an application, we obtain a new analytic stability criterion for th...
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.
Invariant metric for nonlinear symplectic maps
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.
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.
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...
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.
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.
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.
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.
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.
Metrics for Automotive Merchandising, Petroleum Marketing.
Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.
Designed to meet the job-related metric measurement needs of students in automotive merchandising and petroleum marketing classes, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know…
Pravda, V.; Pravdova, A.
2002-01-01
Physical interpretation of some stationary and non-stationary regions of the spinning C-metric is presented. They represent different spacetime regions of a uniformly accelerated Kerr black hole. Stability of geodesics corresponding to equilibrium points in a general stationary spacetime with an additional symmetry is also studied and results are then applied to the spinning C-metric.
Smart Grid Status and Metrics Report Appendices
Balducci, Patrick J.; Antonopoulos, Chrissi A.; Clements, Samuel L.; Gorrissen, Willy J.; Kirkham, Harold; Ruiz, Kathleen A.; Smith, David L.; Weimar, Mark R.; Gardner, Chris; Varney, Jeff
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.
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...
On homogeneous Einstein (α , β) -metrics
Yan, Zaili; Deng, Shaoqiang
2016-05-01
In this paper, we study homogeneous Einstein (α , β) -metrics. First, we deduce a formula for Ricci curvature of a homogeneous (α , β) -metric. Based on this formula, we obtain a sufficient and necessary condition for a compact homogeneous (α , β) -metric to be Einstein and with vanishing S-curvature. Moreover, we prove that any homogeneous Ricci flat (α , β) space with vanishing S-curvature must be a Minkowski space. Finally, we consider left invariant Einstein (α , β) -metrics on Lie groups with negative Ricci constant. Under some appropriate conditions, we show that the underlying Lie groups must be two step solvable. We also present a more convenient sufficient and necessary condition for the metric to be Einstein in this special case.
FABASOFT BEST PRACTICES AND TEST METRICS MODEL
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.
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.
Load Balancing Metric with Diversity for Energy Efficient Routing in Wireless Sensor Networks
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...
Better algorithms for unfair metrical task systems and applications
Fiat, Amos; Mendel, Manor
2004-01-01
Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain improved randomized online algorithms for metrical task systems on arbitrary metric spaces.
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
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.
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
Characterising risk - aggregated metrics: radiation and noise
The characterisation of risk is an important phase in the risk assessment - risk management process. From the multitude of risk attributes a few have to be selected to obtain a risk characteristic or profile that is useful for risk management decisions and implementation of protective measures. One way to reduce the number of attributes is aggregation. In the field of radiation protection such an aggregated metric is firmly established: effective dose. For protection against environmental noise the Health Council of the Netherlands recently proposed a set of aggregated metrics for noise annoyance and sleep disturbance. The presentation will discuss similarities and differences between these two metrics and practical limitations. The effective dose has proven its usefulness in designing radiation protection measures, which are related to the level of risk associated with the radiation practice in question, given that implicit judgements on radiation induced health effects are accepted. However, as the metric does not take into account the nature of radiation practice, it is less useful in policy discussions on the benefits and harm of radiation practices. With respect to the noise exposure metric, only one effect is targeted (annoyance), and the differences between sources are explicitly taken into account. This should make the metric useful in policy discussions with respect to physical planning and siting problems. The metric proposed has only significance on a population level, and can not be used as a predictor for individual risk. (author)
A New Metrics for Hierarchical Clustering
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
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
SAPHIRE 8 Quality Assurance Software Metrics Report
Kurt G. Vedros
2011-08-01
The purpose of this review of software metrics is to examine the quality of the metrics gathered in the 2010 IV&V and to set an outline for results of updated metrics runs to be performed. We find from the review that the maintenance of accepted quality standards presented in the SAPHIRE 8 initial Independent Verification and Validation (IV&V) of April, 2010 is most easily achieved by continuing to utilize the tools used in that effort while adding a metric of bug tracking and resolution. Recommendations from the final IV&V were to continue periodic measurable metrics such as McCabe's complexity measure to ensure quality is maintained. The four software tools used to measure quality in the IV&V were CodeHealer, Coverage Validator, Memory Validator, Performance Validator, and Thread Validator. These are evaluated based on their capabilities. We attempted to run their latest revisions with the newer Delphi 2010 based SAPHIRE 8 code that has been developed and was successful with all of the Validator series of tools on small tests. Another recommendation from the IV&V was to incorporate a bug tracking and resolution metric. To improve our capability of producing this metric, we integrated our current web reporting system with the SpiraTest test management software purchased earlier this year to track requirements traceability.
Application-adaptive resource scheduling in a computational grid
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.
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.
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.
An observation on Asanov's Unicorn metrics
Vincze, Csaba
2016-01-01
Finsleroid-Finsler metrics form an important class of singular (y-local) Finslerian metrics. They were introduced by G. S. Asanov in 2006. As a special case Asanov produced examples of Landsberg spaces of dimension at least three that are not of Berwald type. These are called Unicorns [5]. The existence of regular (y - global) Landsberg metrics that are not of Berwald type is an open problem up to this day. In this paper we prove that Asanov's Unicorns belong to the class of generalized Berwa...
Convergence of Finslerian metrics under Ricci flow
Yar Ahmadi, Mohamad; Bidabad, Behroz
2016-04-01
In this work, convergence of evolving Finslerian metrics first in a general flow next under Finslerian Ricci flow is studied. More intuitively it is proved that a family of Finslerian metrics $g(t)$ which are solutions to the Finslerian Ricci flow converge in $C^{\\infty}$ to a smooth limit Finslerian metric as $ t $ approaches the finite time $ T $. As a consequence of this result one can show that in a compact Finsler manifold the curvature tensor along Ricci flow blows up in short time.
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
Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.
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.
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.
A metric and frameworks for resilience analysis of engineered and infrastructure systems
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
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.
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)....
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...
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.
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.
Evaluating Web Accessibility Metrics for Jordanian Universities
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.
Clean Cities Annual Metrics Report 2009 (Revised)
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...
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.
Using Activity Metrics for DEVS Simulation Profiling
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.
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.
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...
L(2) Cohomology of the Bergman metric.
Donnelly, H; Fefferman, C
1983-05-01
The L(2) cohomology of the Bergman metric is infinite dimensional in the middle degree and vanishes for all other degrees. Asymptotic expansions are given for the Schwartz kernels of the corresponding projections onto harmonic forms. PMID:16593319
L2 Cohomology of the Bergman metric
Donnelly, Harold; Fefferman, Charles
1983-01-01
The L2 cohomology of the Bergman metric is infinite dimensional in the middle degree and vanishes for all other degrees. Asymptotic expansions are given for the Schwartz kernels of the corresponding projections onto harmonic forms. PMID:16593319
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.
Integrated Metrics for Improving the Life Cycle Approach to Assessing Product System Sustainability
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.
GRC GSFC TDRSS Waveform Metrics Report
Mortensen, Dale J.
2013-01-01
The report presents software metrics and porting metrics for the GGT Waveform. The porting was from a ground-based COTS SDR, the SDR-3000, to the CoNNeCT JPL SDR. The report does not address any of the Operating Environment (OE) software development, nor the original TDRSS waveform development at GSFC for the COTS SDR. With regard to STRS, the report presents compliance data and lessons learned.
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...
OSMAN:a novel Arabic readability metric
El-Haj, Mahmoud; Rayson, Paul Edward
2016-01-01
We present OSMAN (Open Source Metric for Measuring Arabic Narratives) - a novel open source Arabic readability metric and tool. It allows researchers to calculate readability for Arabic text with and without diacritics. OSMAN is a modified version of the conventional readability formulas such as Flesch and Fog. In our work we introduce a novel approach towards counting short, long and stress syllables in Arabic which is essential for judging readability of Arabic narratives. We also introduce...
Analysis of Inconsistencies in Object Oriented Metrics
Ahmed M. Salem; Qureshi, Abrar A.
2011-01-01
Software Metrics have been proposed for procedural and object oriented paradigms to measure various attributes like complexity, cohesion, software quality, and productivity. Among all of these, “Complexity” and “Cohesion” are considered to be the most important attributes. As object oriented analysis and design appears to be at the forefront of software engineering technologies, many different object-oriented complexity and cohesion metrics have been developed. The aim of the paper is to comp...
Finite Metric Spaces of Strictly Negative Type
Hjorth, Poul; Lisonek, P.; Markvorsen, Steen; Thomassen, Carsten
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...... by Kelly, we conjecture that all finite subspaces of hyperbolic spaces are hypermetric and regular, and hence of strictly negative type. (C) 1998 Elsevier Science Inc....
Environmental Metrics for Community Health Improvement
Jakubowski, Benjamin; Frumkin, Howard
2010-01-01
Environmental factors greatly affect human health. Accordingly, environmental metrics are a key part of the community health information base. We review environmental metrics relevant to community health, including measurements of contaminants in environmental media, such as air, water, and food; measurements of contaminants in people (biomonitoring); measurements of features of the built environment that affect health; and measurements of "upstream" environmental conditions relevant to healt...
Multipole solutions in metric-affine gravity
Socorro, J; Macías, A; Mielke, E W; Socorro, José; Lämmerzahl, Claus; Macías, Alfredo; Mielke, Eckehard W.
1998-01-01
Above Planck energies, the spacetime might become non--Riemannian, as it is known fron string theory and inflation. Then geometries arise in which nonmetricity and torsion appear as field strengths, side by side with curvature. By gauging the affine group, a metric affine gauge theory emerges as dynamical framework. Here, by using the harmonic map ansatz, a new class of multipole like solutions in the metric affine gravity theory (MAG) is obtained.
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...
An information theoretic approach for privacy metrics
Michele Bezzi
2010-01-01
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 ...
Fubini Theorem for pseudo-Riemannian metrics
Bolsinov, Alexey V.; Kiosak, Volodymyr; Matveev, Vladimir S.
2008-01-01
We generalize the following classical result of Fubini for pseudo-Riemannian metrics: if three essentially different metrics on $M^{n\\ge 3}$ share the same unparametrized geodesics, and two of them (say, $g$ and $\\bar g$) are strictly nonproportional (i.e., the minimal polynomial of $g^{i\\alpha} \\bar g_{\\alpha j}$ coincides with the characteristic polynomial) at least at one point, then they have constant curvature.
Effective dimension in some general metric spaces
Mayordomo, Elvira
2014-01-01
We introduce the concept of effective dimension for a general metric space. Effective dimension was defined by Lutz in (Lutz 2003) for Cantor space and has also been extended to Euclidean space. Our extension to other metric spaces is based on a supergale characterization of Hausdorff dimension. We present here the concept of constructive dimension and its characterization in terms of Kolmogorov complexity. Further research directions are indicated.
A Laplacian on Metric Measure Spaces
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...
Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set
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.
Ricci flow and the metric completion of the space of Kahler metrics
Clarke, Brian
2011-01-01
We consider the space of Kahler metrics as a Riemannian submanifold of the space of Riemannian metrics, and study the associated submanifold geometry. In particular, we show that the intrinsic and extrinsic distance functions are equivalent. We also determine the metric completion of the space of Kahler metrics, making contact with recent generalizations of the Calabi-Yau Theorem due to Dinew, Guedj-Zeriahi, and Kolodziej. As an application, we obtain a new analytic stability criterion for the existence of a Kahler-Einstein metric on a Fano manifold in terms of the Ricci flow and the distance function. We also prove that the Kahler-Ricci flow converges as soon as it converges in the metric sense.
Metrics for Offline Evaluation of Prognostic Performance
Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai
2010-01-01
Prognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.
Positive Semidefinite Metric Learning with Boosting
Shen, Chunhua; 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 observation that any positive semidefinite matrix can be decomposed into a linear positive combination of trace-one rank-one matrices. \\BoostMetric thus uses rank-one positive semidefinite matrices as weak learners within an efficient and scalable boosting-based learning process. The resulting method is easy to implement, does not require tuning, and can accommodate various types of constraints. Experiments on various datasets show that the proposed algorithm compares favorably to those state-of-the-art methods in terms of classi...
Metric of Rotating Charged Spherical Mass in Vacuum for Vector Graviton Metric Theory of Gravitation
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.
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
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
Cleanroom Energy Efficiency: Metrics and Benchmarks
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.
SOFTWARE METRICS VALIDATION METHODOLOGIES IN SOFTWARE ENGINEERING
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].
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.
Codes in W*-Metric Spaces: Theory and Examples
Bumgardner, Christopher J.
2011-01-01
We introduce a "W*"-metric space, which is a particular approach to non-commutative metric spaces where a "quantum metric" is defined on a von Neumann algebra. We generalize the notion of a quantum code and quantum error correction to the setting of finite dimensional "W*"-metric spaces, which includes codes and error correction for classical…
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.
Demonstration of the Symmetry Properties of Gravitational Metric Fields
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.
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...
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...
New type of fixed point theorems in generalized metric spaces
Hojjat Afshari; Hossein Piri
2015-01-01
In this paper, we prove some new type of fixed point theorems in generalized complete metric spaces. The results presented in this paper mainly improve the corresponding results announced by Wardowski [D. Wardowski, Fixed point theory of a new type of contractive mappings in complete metric spaces, Fixed Point Theory Appl. 2012 (2012), Article ID 94] from metric spaces to generalized metric spaces.
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
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.
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.
Pragmatic quality metrics for evolutionary software development models
Royce, Walker
1990-01-01
Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.
Enhancing the quality metric of protein microarray image
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.
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
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)
Enhanced Accident Tolerant LWR Fuels: Metrics Development
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.
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...
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...
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 ...
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.
Information metric and Euclidean Janus correspondence
Dongsu Bak
2016-05-01
Full Text Available 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 has a dual description in the Euclidean version of the Janus time-dependent black hole geometry.
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.
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...
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...
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
Beyond Benchmarking: Value-Adding Metrics
Fitz-enz, Jac
2007-01-01
HR metrics has grown up a bit over the past two decades, moving away from simple benchmarking practices and toward a more inclusive approach to measuring institutional performance and progress. In this article, the acknowledged "father" of human capital performance benchmarking provides an overview of several aspects of today's HR metrics…
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?
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.
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…
Remarks on bootstrap percolation in metric networks
We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes depending on the graph size N. Large metric graphs are ignited by the occurrence of critical nuclei, which initially occupy an infinitesimal fraction, f* → 0, of the graph and then explode throughout a finite fraction. Smaller metric graphs are effectively random in the sense that their ignition requires the initial ignition of a finite, unlocalized fraction of the graph, f* > 0. The crossover between the two regimes is at a size N* which scales exponentially with the connectivity range λ like N* ∼ exp λd. The neuronal cultures are finite metric graphs of size N ≅ 105 - 106, which, for the parameters of the experiment, is effectively random since N *. This explains the seeming contradiction in the observed finite f* in these cultures. Finally, we discuss the dynamics of the firing front
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
Outsourced similarity search on metric data assets
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...
Strong Ideal Convergence in Probabilistic Metric Spaces
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.
Description of the Sandia Validation Metrics Project
This report describes the underlying principles and goals of the Sandia ASCI Verification and Validation Program Validation Metrics Project. It also gives a technical description of two case studies, one in structural dynamics and the other in thermomechanics, that serve to focus the technical work of the project in Fiscal Year 2001
Colliding waves in metric-affine gravity
García, A; Macías, A; Mielke, E W; Socorro, J; García, Alberto; Lämmerzahl, Claus; Macías, Alfredo; Mielke, Eckehard W.; Socorro, José
1998-01-01
We generalize the formulation of the colliding gravitational waves to metric-affine theories and present an example of such kind of exact solutions. The plane waves are equipped with five symmetries and the resulting geometry after the collision possesses two spacelike Killing vectors.
Clean Cities 2011 Annual Metrics Report
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.
Clean Cities 2010 Annual Metrics Report
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.
Calabi–Yau metrics and string compactification
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.
Pravda, Vojtěch; Pravdová, Alena
New Jersey: World Scientific, 2002, s. 247-262. ISBN 981-238-093-0 R&D Projects: GA ČR GA202/00/P031; GA ČR GA202/00/P030 Keywords : spinning C-metric * exact solutions of Einsteinďs equations Subject RIV: BA - General Mathematics
Metrical musings on Littlewood and friends
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...
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.
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.
Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report
Cornhill, Dennis; Bharadwaj, Raj; Mylaraswamy, Dinkar
2013-01-01
This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.
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.
Staša Stropnik; Jana Kodrič
2013-01-01
Adaptive skills are defined as a collection of conceptual, social and practical skills that are learned by people in order to function in their everyday lives. They include an individual's ability to adapt to and manage her or his surroundings to effectively function and meet social or community expectations. Good adaptive skills promote individual's independence in different environments, whereas poorly developed adaptive skills are connected to individual's dependency and with g...
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...
Adaptive resolution refinement for high-fidelity continuum parameterizations
Anderson, J.W.; Khamayseh, A. [Los Alamos National Lab., NM (United States); Jean, B.A. [Mississippi State Univ., Starkville, MS (United States)
1996-10-01
This paper describes an algorithm the adaptively samples a parametric continuum so that a fidelity metric is satisfied. Using the divide-and-conquer strategy of adaptive sampling eliminates the guesswork of traditional uniform parameterization techniques. The space and time complexity of parameterization are increased in a controllable manner so that a desired fidelity is obtained.
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
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.
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.
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.
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 $k=n-2$.
Data Complexity Metrics for XML Web Services
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.
Metrics for measuring distances in configuration spaces
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
A Taxonomy of Metrics for Hosted Databases
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.
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
Metric for Early Measurement of Software Complexity
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.
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.
Structural Properties of Hard Metric TSP Inputs
Mömke, Tobias
The metric traveling salesman problem is one of the most prominent APX-complete optimization problems. An important particularity of this problem is that there is a large gap between the known upper bound and lower bound on the approximability (assuming P ≠ NP). In fact, despite more than 30 years of research, no one could find a better approximation algorithm than the 1.5-approximation provided by Christofides. The situation is similar for a related problem, the metric Hamiltonian path problem, where the start and the end of the path are prespecified: the best approximation ratio up to date is 5/3 by an algorithm presented by Hoogeveen almost 20 years ago.
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...
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
Metric-Aware Secure Service Orchestration
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.
Ideal Based Cyber Security Technical Metrics for Control Systems
W. F. Boyer; M. A. McQueen
2007-10-01
Much of the world's critical infrastructure is at risk from attack through electronic networks connected to control systems. Security metrics are important because they provide the basis for management decisions that affect the protection of the infrastructure. A cyber security technical metric is the security relevant output from an explicit mathematical model that makes use of objective measurements of a technical object. A specific set of technical security metrics are proposed for use by the operators of control systems. Our proposed metrics are based on seven security ideals associated with seven corresponding abstract dimensions of security. We have defined at least one metric for each of the seven ideals. Each metric is a measure of how nearly the associated ideal has been achieved. These seven ideals provide a useful structure for further metrics development. A case study shows how the proposed metrics can be applied to an operational control system.
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
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
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...
Almost Contact Metric Structures Induced by $G_2$ Structures
Özdemir, Nülifer; Solgun, Mehmet; Aktay, Şirin
2016-01-01
We study almost contact metric structures induced by 2-fold vector cross products on manifolds with $G_2$ structures. We get some results on possible classes of almost contact metric structures. Finally we give examples.
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...
Boundary behavior of the Bergman metric
Chen, Bo-Yong
2002-01-01
Let $\\Omega$ be a bounded pseudoconvex domain in ${\\bf C}^n$. We give sufficient conditions for the Bergman metric to go to infinity uniformly at some boundary point, which is stated by the existence of a Hölder continuous plurisubharmonic peak function at this point or the verification of property $(P)$ (in the sense of Coman) which is characterized by the pluricomplex Green function.
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.
Economic metrics for wind energy projects
Wagner Sousa de Oliveira, Antonio Jorge Fernandes, Joaquim Jose Borges Gouveia
2011-01-01
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 involv...
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 ...
Structural complexity metrics for UML class diagrams
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.
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...
Validation of a Quality Management Metric
Grossman, Mary Alice.
2000-01-01
The quality of software management in a development program is a major factor in determining the success of a program. The four main areas where a software program manager can affect the outcome of a program are requirements management, estimation/planning management, people management, and risk management. In this thesis a quality management metric (QMM) was used to measure the performance of ten software managers on Department of Defense (DoD) software development programs. Informal verific...
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.
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.
Riemann surface with almost positive definite metric
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.
A Metrics Approach for Collaborative Systems
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
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.
(m,q)-isimetries on metric spaces
Bermúdez, T.; Martinón, A.; Müller, Vladimír
2014-01-01
Roč. 72, č. 2 (2014), s. 313-329. ISSN 0379-4024 R&D Projects: GA AV ČR IAA100190903 Institutional support: RVO:67985840 Keywords : m-isometry * Mazur-ulam theorem * metric space Subject RIV: BA - General Mathematics Impact factor: 0.550, year: 2014 http://www.mathjournals.org/jot/2014-072-002/2014-072-002-002.html
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...
Smart Grid Status and Metrics Report
Balducci, Patrick J.; Weimar, Mark R.; Kirkham, Harold
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.
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 ...
The Planck Vacuum and the Schwarzschild Metrics
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.
Thermodynamic Metrics and Black Hole Physics
Åman, Jan; Pidokrajt, Narit
2015-01-01
We give a brief survey of thermodynamic metrics, in particular the Hessian of the entropy function, and how they apply to black hole thermodynamics. We then provide a detailed discussion of the Gibbs surface of Kerr black holes. In particular we analyze its global properties, and extend it to take the entropy of the inner horizon into account. A brief discussion of Kerr-Newman black holes is included.
Evaluation Metrics for Biostatistical and Epidemiological Collaborations
Rubio, Doris McGartland; del Junco, Deborah J.; Bhore, Rafia; Lindsell, Christopher J.; Oster, Robert A.; Wittkowski, Knut M.; Welty, Leah J.; Li, Yi-Ju; DeMets, Dave
2011-01-01
Increasing demands for evidence-based medicine and for the translation of biomedical research into individual and public health benefit have been accompanied by the proliferation of special units that offer expertise in biostatistics, epidemiology, and research design (BERD) within academic health centers. Objective metrics that can be used to evaluate, track, and improve the performance of these BERD units are critical to their successful establishment and sustainable future. To develop a se...
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...
Discrete Affine Minimal Surfaces with Indefinite Metric
Craizer, Marcos; Anciaux, Henri; Lewiner, Thomas
2008-01-01
Inspired by the Weierstrass representation of smooth affine minimal surfaces with indefinite metric, we propose a constructive process producing a large class of discrete surfaces that we call discrete affine minimal surfaces. We show that they are critical points of an affine area functional defined on the space of quadrangular discrete surfaces. The construction makes use of asymptotic coordinates and allows defining the discrete analogs of some differential geometric objects, such as the n...
Models, Metrics, and Measurement in Developmental Psychology
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.
An information theoretic approach for privacy metrics
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...
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...
Dynamic Density: An Air Traffic Management Metric
Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.
1998-01-01
The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.
Metric optimized gating for fetal cardiac MRI.
Jansz, Michael S; Seed, Mike; van Amerom, Joshua F P; Wong, Derek; Grosse-Wortmann, Lars; Yoo, Shi-Joon; Macgowan, Christopher K
2010-11-01
Phase-contrast magnetic resonance imaging can be used to complement echocardiography for the evaluation of the fetal heart. Cardiac imaging typically requires gating with peripheral hardware; however, a gating signal is not readily available in utero. No successful application of existing technologies to human fetal phase-contrast magnetic resonance imaging has been reported to date in the literature. The purpose of this work is to develop a technique for phase-contrast magnetic resonance imaging of the fetal heart that does not require measurement of a gating signal. Metric optimized gating involves acquiring data without gating and retrospectively determining the proper reconstruction by optimizing an image metric. The effects of incorrect gating on phase contrast images were investigated, and the time-entropy of the series of images was found to provide a good measure of the level of corruption. The technique was validated with a pulsatile flow phantom, experiments with adult volunteers, and in vivo application in the fetal population. Images and flow curves from these measurements are presented. Additionally, numerical simulations were used to investigate the degree to which heart rate variability affects the reconstruction process. Metric optimized gating enables imaging with conventional phase-contrast magnetic resonance imaging sequences in the absence of a gating signal, permitting flow measurements in the great vessels in utero. PMID:20632406
Hessian potential for Fefferman-Graham metric
Matsueda, Hiroaki
2015-01-01
The Fefferman-Graham metric is frequently used for derivation of the first law of the entanglement thermodynamics. On ther other hand, the entanglement thermodynamics is well formulated by the Hessian geometry. The aim of this work is to relate them with each other by finding the corresponding Hessian potential. We find that the deformation of the bulk Hessian potential for the pure AdS spacetime behaves as a source potential of the boundary Fisher metric, and the deformation coincides with the Fefferman-Graham metric. A peculiar feature different from related works is that we need not to use the Ryu-Takayanagi formula for the above derivation. The canonical parameter space in the Hessian geometry is a kind of the model parameter space, rather than the real classical spacetime in the usual setup of the AdS/CFT correspondence. However, the underlying mathematical structure is the same as that of the AdS/CFT correspondence. This suggests the presence of more global class of holographic transformation.
An Improved Metric Learning Approach for Degraded Face Recognition
2014-01-01
To solve the matching problem of the elements in different data collections, an improved coupled metric learning approach is proposed. First, we improved the supervised locality preserving projection algorithm and added the within-class and between-class information of the improved algorithm to coupled metric learning, so a novel coupled metric learning method is proposed. Furthermore, we extended this algorithm to nonlinear space, and the kernel coupled metric learning method based on superv...
Evaluation of Cost Estimation Metrics: Towards a Unified Terminology
M. Alsmadi, Izzat; S. Nuser, Maryam
2013-01-01
Cost overrun of software projects is major cause of their failures. In order to facilitate accurate software cost estimation, there are several metrics, tools and datasets. In this paper, we evaluate and compare different metrics and datasets in terms of similarities and differences of involved software attributes. These metrics forecast project cost estimations based on different software attributes. Some of these metrics are public and standard while others are only employed in a particular...
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 ...
Reproducibility of Graph Metrics in fMRI Networks
Telesford, Qawi K.; Simpson, Sean L.; Mozolic, Jennifer L.
2010-01-01
The reliability of graph metrics calculated in network analysis is essential to the interpretation of complex network organization. These graph metrics are used to deduce the small-world properties in networks. In this study, we investigated the test-retest reliability of graph metrics from functional magnetic resonance imaging (fMRI) data collected for two runs in 45 healthy older adults. Graph metrics were calculated on data for both runs and compared using intraclass correlation coefficie...
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 ...
On projectively equivalent metrics near points of bifurcation
Matveev, Vladimir S.
2008-01-01
Let Riemannian metrics $g$ and $\\bar g$ on a connected manifold $M^n$ have the same geodesics (considered as unparameterized curves). Suppose the eigenvalues of one metric with respect to the other are all different at a point. Then, by the famous Levi-Civita's Theorem, the metrics have a certain standard form near the point. Our main result is a generalization of Levi-Civita's Theorem for the points where the eigenvalues of one metric with respect to the other bifurcate.
Inner Metric Geometry of Complex Algebraic Surfaces with Isolated Singularities
Birbrair, Lev; Fernandes, Alexandre
2007-01-01
We produce examples of complex algebraic surfaces with isolated singularities such that these singularities are not metrically conic, i.e. the germs of the surfaces near singular points are not bi-Lipschitz equivalent, with respect to the inner metric, to cones. The technique used to prove the nonexistence of the metric conic structure is related to a development of Metric Homology. The class of the examples is rather large and it includes some surfaces of Brieskorn.
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.
Adaptive Sampling in Hierarchical Simulation
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.
Performance Comparison of QOS Metrics for a Distributed Pricing Scheme
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
Fixed Point Theorems in Quaternion-Valued Metric Spaces
2014-01-01
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.
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...
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...
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....
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...
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...
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...
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...
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...
Robustness of climate metrics under climate policy ambiguity
Highlights: • We assess the economic impacts of using different climate metrics. • The setting is cost-efficient scenarios for three interpretations of the 2C target. • With each target setting, the optimal metric is different. • Therefore policy ambiguity prevents the selection of an optimal metric. • Robust metric values that perform well with multiple policy targets however exist. -- Abstract: A wide array of alternatives has been proposed as the common metrics with which to compare the climate impacts of different emission types. Different physical and economic metrics and their parameterizations give diverse weights between e.g. CH4 and CO2, and fixing the metric from one perspective makes it sub-optimal from another. As the aims of global climate policy involve some degree of ambiguity, it is not possible to determine a metric that would be optimal and consistent with all policy aims. This paper evaluates the cost implications of using predetermined metrics in cost-efficient mitigation scenarios. Three formulations of the 2 °C target, including both deterministic and stochastic approaches, shared a wide range of metric values for CH4 with which the mitigation costs are only slightly above the cost-optimal levels. Therefore, although ambiguity in current policy might prevent us from selecting an optimal metric, it can be possible to select robust metric values that perform well with multiple policy targets
GENERAL RELATIVITY AND METRICS OF INHOMOGENEOUS ROTATING UNIVERSE
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
Term Based Comparison Metrics for Controlled and Uncontrolled Indexing Languages
Good, B. M.; Tennis, J. T.
2009-01-01
Introduction: We define a collection of metrics for describing and comparing sets of terms in controlled and uncontrolled indexing languages and then show how these metrics can be used to characterize a set of languages spanning folksonomies, ontologies and thesauri. Method: Metrics for term set characterization and comparison were identified and…
Graev metrics on free products and HNN extensions
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…
Two special metrics with R14-type holonomy
Ghanam, R.; Thompson, G.
2001-06-01
Two spacetime metrics are constructed that provide examples that were conjectured to exist in a recent paper by Hall and Lonie. The first metric is an Einstein space that has a null recurrent vector field. The second metric is conformally flat and also has a null recurrent vector field.
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…
Fixed Point Theorems in Quaternion-Valued Metric Spaces
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.
Spherically Symmetric Solution in Bi-metric theory of Gravity
E, Anoop Narayanan P; Suresh, P. K.
2014-01-01
The possibility of spherically symmetric solutions in bi-metric theory of gravity is examined. It is shown that two possible black hole type solutions exists in the model. Spherically symmetric solution of general theory of relativity is recovered in the absence of the second metric. The result is compared with other bi-metric models as well as general theory of relativity.
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.
FIXED POINT RESULTS ON METRIC-TYPE SPACES
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.
The Geometry of r-adaptive meshes generated using Optimal Transport Methods
C. J. Budd; Russell, R. D.; Walsh, E.
2014-01-01
The principles of mesh equidistribution and alignment play a fundamental role in the design of adaptive methods, and a metric tensor M and mesh metric are useful theoretical tools for understanding a methods level of mesh alignment, or anisotropy. We consider a mesh redistribution method based on the Monge-Ampere equation, which combines equidistribution of a given scalar density function with optimal transport. It does not involve explicit use of a metric tensor M, although such a tensor mus...
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...
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.
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
Staša Stropnik
2013-02-01
Full Text Available Adaptive skills are defined as a collection of conceptual, social and practical skills that are learned by people in order to function in their everyday lives. They include an individual's ability to adapt to and manage her or his surroundings to effectively function and meet social or community expectations. Good adaptive skills promote individual's independence in different environments, whereas poorly developed adaptive skills are connected to individual's dependency and with greater need for control and help with everyday tasks. Assessment of adaptive skills is often connected to assessment of intellectual disability, due to the reason that the diagnosis of intellectual disability includes lower levels of achievements on standardized tests of intellectual abilities as well as important deficits in adaptive skills. Assessment of adaptive behavior is a part of standard assessment battery with children and adults with different problems, disorders or disabilities that affect their everyday functioning. This contribution also presents psychometric tools most regularly used for assessment of adaptive skills and characteristics of adaptive skills with individual clinical groups.
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...
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.
THE ROLE OF ARTICLE LEVEL METRICS IN SCIENTIFIC PUBLISHING
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.
An Improved Metric Learning Approach for Degraded Face Recognition
Guofeng Zou
2014-01-01
Full Text Available To solve the matching problem of the elements in different data collections, an improved coupled metric learning approach is proposed. First, we improved the supervised locality preserving projection algorithm and added the within-class and between-class information of the improved algorithm to coupled metric learning, so a novel coupled metric learning method is proposed. Furthermore, we extended this algorithm to nonlinear space, and the kernel coupled metric learning method based on supervised locality preserving projection is proposed. In kernel coupled metric learning approach, two elements of different collections are mapped to the unified high dimensional feature space by kernel function, and then generalized metric learning is performed in this space. Experiments based on Yale and CAS-PEAL-R1 face databases demonstrate that the proposed kernel coupled approach performs better in low-resolution and fuzzy face recognition and can reduce the computing time; it is an effective metric method.
Balanced metrics for vector bundles and polarised manifolds
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...
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...
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.
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
Energy Metrics for State Government Buildings
Michael, Trevor
Measuring true progress towards energy conservation goals requires the accurate reporting and accounting of energy consumption. An accurate energy metrics framework is also a critical element for verifiable Greenhouse Gas Inventories. Energy conservation in government can reduce expenditures on energy costs leaving more funds available for public services. In addition to monetary savings, conserving energy can help to promote energy security, air quality, and a reduction of carbon footprint. With energy consumption/GHG inventories recently produced at the Federal level, state and local governments are beginning to also produce their own energy metrics systems. In recent years, many states have passed laws and executive orders which require their agencies to reduce energy consumption. In June 2008, SC state government established a law to achieve a 20% energy usage reduction in state buildings by 2020. This study examines case studies from other states who have established similar goals to uncover the methods used to establish an energy metrics system. Direct energy consumption in state government primarily comes from buildings and mobile sources. This study will focus exclusively on measuring energy consumption in state buildings. The case studies reveal that many states including SC are having issues gathering the data needed to accurately measure energy consumption across all state buildings. Common problems found include a lack of enforcement and incentives that encourage state agencies to participate in any reporting system. The case studies are aimed at finding the leverage used to gather the needed data. The various approaches at coercing participation will hopefully reveal methods that SC can use to establish the accurate metrics system needed to measure progress towards its 20% by 2020 energy reduction goal. Among the strongest incentives found in the case studies is the potential for monetary savings through energy efficiency. Framing energy conservation
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.
Metric propositional neighborhood logics on natural numbers
Bresolin, Davide; Della Monica, Dario; Goranko, Valentin;
2013-01-01
is decidable in double exponential time and expressively complete with respect to a well-defined sub-fragment of the two-variable fragment FO2[N,=,<,s] of first-order logic for linear orders with successor function, interpreted over natural numbers. Moreover, we show that MPNL can be extended in a...... Metric Propositional Neighborhood Logic (MPNL) over natural numbers. MPNL features two modalities referring, respectively, to an interval that is “met by” the current one and to an interval that “meets” the current one, plus an infinite set of length constraints, regarded as atomic propositions, to...
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.
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
Adaptive and application dependant runtime guided hardware reconfiguration for the IBM POWER7
Prat Robles, David
2014-01-01
The aim of this project is to develop adaptive resource management systems for the im- provement of the power-performance metrics associated with the current and future IBM POWER-series microprocessors.
WTR: A Reputation Metric for Distributed Hash Tables Based on a Risk and Credibility Factor
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.
Defining a Standard Metric for Electricity Savings
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.
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.
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...
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...
Network Community Detection on Metric Space
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.
Automatic classification of Deep Web sources based on KNN algorithm%基于K-近邻算法的Deep Web数据源的自动分类
张智; 顾韵华
2011-01-01
To meet the need of Deep Web query, an algorithm for classification of Deep Web sources based on KNN is put forward. The algorithm extracts the form features from Web pages, and makes the form features vector normal. Then the algorithm classifies Deep Web pages by computing distance. The experimental results show that the algorithm has improved in precision and recall.%针对Deep Web的查询需求,提出了一种基于K-近邻算法的Deep Web数据源的自动分类方法.该算法在对Deep Web网页进行表单特征提取及规范化的基础上,基于距离对Deep Web网页所属的目标主题进行判定.实验结果表明:基于K-近邻分类算法可以较有效地进行DeepWeb数据源的自动分类,并得到较高的查全率和查准率.
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
Long-term energy planning with uncertain environmental performance metrics
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
Measurable Control System Security through Ideal Driven Technical Metrics
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
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.
Møller Larsen, Marcus; Lyngsie, Jacob
We investigate why some exchange relationships terminate prematurely. We argue that investments in informal governance structures induce premature termination in relationships already governed by formal contracts. The formalized adaptive behavior of formal governance structures and the flexible and...... reciprocal adaptation of informal governance structure create ambiguity in situations of contingencies, which, subsequently, increases the likelihood of premature relationship termination. Using a large sample of exchange relationships in the global service provider industry, we find support for a hypothesis...
Andersen, Torben Juul
2015-01-01
This article provides an overview of theoretical contributions that have influenced the discourse around strategic adaptation including contingency perspectives, strategic fit reasoning, decision structure, information processing, corporate entrepreneurship, and strategy process. The related...... concepts of strategic renewal, dynamic managerial capabilities, dynamic capabilities, and strategic response capabilities are discussed and contextualized against strategic responsiveness. The insights derived from this article are used to outline the contours of a dynamic process of strategic adaptation...
A software quality model and metrics for risk assessment
Hyatt, L.; Rosenberg, L.
1996-01-01
A software quality model and its associated attributes are defined and used as the model for the basis for a discussion on risk. Specific quality goals and attributes are selected based on their importance to a software development project and their ability to be quantified. Risks that can be determined by the model's metrics are identified. A core set of metrics relating to the software development process and its products is defined. Measurements for each metric and their usability and applicability are discussed.
Metrics for Evaluating Dialogue Strategies in a Spoken Language System
Danieli, Morena; Gerbino, Elisabetta
1996-01-01
In this paper, we describe a set of metrics for the evaluation of different dialogue management strategies in an implemented real-time spoken language system. The set of metrics we propose offers useful insights in evaluating how particular choices in the dialogue management can affect the overall quality of the man-machine dialogue. The evaluation makes use of established metrics: the transaction success, the contextual appropriateness of system answers, the calculation of normal and correct...
Report on metric study tour to Republic of South Africa
Laner, F. J.
1978-01-01
The modernized metric system, known universally as the International System of Units (abbreviated SI under the French name) was renamed in 1960 by the world body on standards. A map shows 98 percent of the world using or moving toward adoption of SI units. Only the countries of Burma, Liberia, Brunei, and Southern Yemen are nonmetric. The author describes a two-week session in Pretoria and Johannesburg on metrication, followed by additional meetings on metrication in Rhodesia. (MCW)