Relevant bibliographies by topics / Metric estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Metric estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Metric estimation"

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Díaz, Álvaro, Javier González-Bayon, and Pablo Sánchez. "Security Estimation in Wireless Sensor Network Simulator." Journal of Circuits, Systems and Computers 25, no. 07 (April 22, 2016): 1650067. http://dx.doi.org/10.1142/s0218126616500675.

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Sensor nodes are low-power and low-cost devices with the requirement of a long autonomous lifetime. Therefore, the nodes have to use the available power carefully and avoid expensive computations or radio transmissions. In addition, as some wireless sensor networks (WSNs) process sensitive data, selecting a security protocol is vital. Cryptographic methods used in WSNs should fulfill the constraints of sensor nodes and should be evaluated for their security and power consumption. WSN engineers use several metrics to obtain estimations prior to network deployment. These metrics are usually related to power and execution time estimation. However, security is a feature that cannot be estimated and it is either “active” or “inactive”, with no possibility of introducing intermediate security levels. This lack of flexibility is a disadvantage in real deployments where different operation modes with different security and power specifications are often needed. This paper proposes including a new security estimation metric in a previously proposed framework for WSN simulation and embedded software (SW) performance analysis. This metric is called Security Estimation Metric (SEM) and it provides information about the security encryption used in WSN transmissions. Results show that the metric improves flexibility, granularity and execution time compared to other cryptographic tests.
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COSTAGLIOLA, G., F. FERRUCCI, G. TORTORA, and G. VITIELLO. "A METRIC FOR THE SIZE ESTIMATION OF OBJECT-ORIENTED GRAPHICAL USER INTERFACES." International Journal of Software Engineering and Knowledge Engineering 10, no. 05 (October 2000): 581–603. http://dx.doi.org/10.1142/s0218194000000304.

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In order to achieve quality products with reliable cost and effort estimations, one of the main tasks for planning software project development is size estimation. This is especially true when dealing with interactive applications which represent critical components in a software project. In the paper, we address the problem of the size estimation of interactive graphical applications developed using the object-oriented methodology. In particular, we define and validate a metric, the Class Point metric, for estimating the size of object-oriented GUIs. The method is based on the idea of quantifying classes in a program analogous to function counting performed by the function point metric. Theoretical validation has proven the consistency of the Class Point metric as size measure. Empirical validation provides evidence that the Class Point metric is a useful measure for OO software size.
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Lee, Jae Young, Martin Röösli, and Martina S. Ragettli. "Estimation of Heat-Attributable Mortality Using the Cross-Validated Best Temperature Metric in Switzerland and South Korea." International Journal of Environmental Research and Public Health 18, no. 12 (June 13, 2021): 6413. http://dx.doi.org/10.3390/ijerph18126413.

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This study presents a novel method for estimating the heat-attributable fractions (HAF) based on the cross-validated best temperature metric. We analyzed the association of eight temperature metrics (mean, maximum, minimum temperature, maximum temperature during daytime, minimum temperature during nighttime, and mean, maximum, and minimum apparent temperature) with mortality and performed the cross-validation method to select the best model in selected cities of Switzerland and South Korea from May to September of 1995–2015. It was observed that HAF estimated using different metrics varied by 2.69–4.09% in eight cities of Switzerland and by 0.61–0.90% in six cities of South Korea. Based on the cross-validation method, mean temperature was estimated to be the best metric, and it revealed that the HAF of Switzerland and South Korea were 3.29% and 0.72%, respectively. Furthermore, estimates of HAF were improved by selecting the best city-specific model for each city, that is, 3.34% for Switzerland and 0.78% for South Korea. To the best of our knowledge, this study is the first to observe the uncertainty of HAF estimation originated from the selection of temperature metric and to present the HAF estimation based on the cross-validation method.
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Schober, R., and W. H. Gerstacker. "Metric for noncoherent sequence estimation." Electronics Letters 35, no. 25 (1999): 2178. http://dx.doi.org/10.1049/el:19991489.

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Corl, Vickie. "Developing Classroom Science Skills: Metric Estimation Estimating Metric Units: Upper Elementary through High School." Science Activities: Classroom Projects and Curriculum Ideas 27, no. 2 (July 1990): 23–24. http://dx.doi.org/10.1080/00368121.1990.9956720.

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Kim, Jungho, Sungwon Kang, Jongsun Ahn, and Seonah Lee. "EMSA: Extensibility Metric for Software Architecture." International Journal of Software Engineering and Knowledge Engineering 28, no. 03 (March 2018): 371–405. http://dx.doi.org/10.1142/s0218194018500134.

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Software extensibility, the capability of adding new functions to a software system, is established based on software architecture. Therefore, developers need to evaluate the capability when designing software architecture. To support the evaluation, researchers have proposed metrics based on quality models or scenarios. However, those metrics are vague or subjective, depending on specific systems and evaluators. We propose the extensibility metric for software architecture (EMSA), which represents the degree of extensibility of a software system based on its architecture. To reduce the subjectivity of the metric, we first identify a typical task of adding new functions to a software system. Second, we define the metrics based on the characteristics of software architecture and its changes and finally combine them into a single metric. The originality of EMSA comes from defining metrics based on software architecture and extensibility tasks and integrating them into one. Furthermore, we made an effort to translate the degree into effort estimation expressed as person-hours. To evaluate EMSA, we conducted two types of user studies, obtaining measurements in both a laboratory and a real-world project. The results show that the EMSA estimation is reasonably accurate [6.6% MMRE and 100% PRED(25%)], even in a real-world project (93.2% accuracy and 8.5% standard deviation).
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BHARKAD, SANGITA D., and MANESH KOKARE. "PERFORMANCE EVALUATION OF DISTANCE METRICS: APPLICATION TO FINGERPRINT RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 25, no. 06 (September 2011): 777–806. http://dx.doi.org/10.1142/s0218001411009007.

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Distance metric is widely used in similarity estimation which plays a key role in fingerprint recognition. In this work we propose the detailed comparison of 29 distinct distance metrics. Features of fingerprint images are extracted using Fast Fourier Transform (FFT). Recognition rate, receiver operating curve (ROC), time and space complexity parameters are used for evaluation of each distance metric. To consolidate our conclusion we used the standard fingerprint database available at Bologna University and FVC2000 databases. After evaluation of 29 distinct distance metrics we found Sorgel distance metric performs best. Genuine acceptance rate (GAR) of Sorgel distance metric is observed to be ~5% higher than traditional Euclidean distance metric at low false acceptance rate (FAR). Sorgel distance gives good GAR at low FAR with moderate computational complexity.
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Najadat, Hassan, Izzat Alsmadi, and Yazan Shboul. "Predicting Software Projects Cost Estimation Based on Mining Historical Data." ISRN Software Engineering 2012 (April 10, 2012): 1–8. http://dx.doi.org/10.5402/2012/823437.

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In this research, a hybrid cost estimation model is proposed to produce a realistic prediction model that takes into consideration software project, product, process, and environmental elements. A cost estimation dataset is built from a large number of open source projects. Those projects are divided into three domains: communication, finance, and game projects. Several data mining techniques are used to classify software projects in terms of their development complexity. Data mining techniques are also used to study association between different software attributes and their relation to cost estimation. Results showed that finance metrics are usually the most complex in terms of code size and some other complexity metrics. Results showed also that games applications have higher values of the SLOCmath, coupling, cyclomatic complexity, and MCDC metrics. Information gain is used in order to evaluate the ability of object-oriented metrics to predict software complexity. MCDC metric is shown to be the first metric in deciding a software project complexity. A software project effort equation is created based on clustering and based on all software projects’ attributes. According to the software metrics weights values developed in this project, we can notice that MCDC, LOC, and cyclomatic complexity of the traditional metrics are still the dominant metrics that affect our classification process, while number of children and depth of inheritance are the dominant from the object-oriented metrics as a second level.
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Wurfel, J. D., M. Padilla, and N. M. Grzywacz. "Metric estimation of visual-deformation motions." Journal of Vision 5, no. 8 (March 16, 2010): 328. http://dx.doi.org/10.1167/5.8.328.

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Pons-Moll, Gerard, Jonathan Taylor, Jamie Shotton, Aaron Hertzmann, and Andrew Fitzgibbon. "Metric Regression Forests for Correspondence Estimation." International Journal of Computer Vision 113, no. 3 (April 11, 2015): 163–75. http://dx.doi.org/10.1007/s11263-015-0818-9.

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Dissertations / Theses on the topic "Metric estimation"

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O'Loan, Caleb J. "Topics in estimation of quantum channels." Thesis, University of St Andrews, 2010. http://hdl.handle.net/10023/869.

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A quantum channel is a mapping which sends density matrices to density matrices. The estimation of quantum channels is of great importance to the field of quantum information. In this thesis two topics related to estimation of quantum channels are investigated. The first of these is the upper bound of Sarovar and Milburn (2006) on the Fisher information obtainable by measuring the output of a channel. Two questions raised by Sarovar and Milburn about their bound are answered. A Riemannian metric on the space of quantum states is introduced, related to the construction of the Sarovar and Milburn bound. Its properties are characterized. The second topic investigated is the estimation of unitary channels. The situation is considered in which an experimenter has several non-identical unitary channels that have the same parameter. It is shown that it is possible to improve estimation using the channels together, analogous to the case of identical unitary channels. Also, a new method of phase estimation is given based on a method sketched by Kitaev (1996). Unlike other phase estimation procedures which perform similarly, this procedure requires only very basic experimental resources.
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Kazzazi, Seyedeh Mandan. "Dental metric standards for sex estimation in archaeological populations from Iran." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31067.

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Sex estimation of skeletal remains is one of the major components of forensic identification of unknown individuals. Teeth are a potential source of information on sex and are often recovered in archaeological or forensic contexts due to their post-mortem longevity. Currently there is limited data on dental sexual dimorphism of archaeological populations from Iran. This dissertation represents the first study to provide a dental sex estimation method for Iron Age populations. The current study was conducted on the skeletal remains of 143 adults from two Iron Age populations in close temporal and geographic proximity in the Solduz Valley (West Azerbaijan Province of Iran). 2D and 3D cervical mesiodistal and buccolingual and root volume measurements of maxillary and mandibular teeth were used to investigate the degree of sexual dimorphism in permanent dentition and to assess their applicability in sex estimation. In total 1327, 457, and 480 anterior and posterior teeth were used to collect 2D cervical, 3D cervical, and root volume measurements respectively. 2D cervical measurements were taken using Hillson-Fitzgerald dental calliper and 3D measurements were collected using CT images provided by Open Research Scan Archive (ORSA) - Penn Museum. 3D models of the teeth were created using manual segmentation in the Amira 6.01 software package. Since tooth density largely differs from crown to apex, root segmentation required two threshold levels: the segmentation of the root from the jaw and the segmentation of the crown from the root. Thresholds used for root segmentation were calculated using the half maximum height protocol of Spoor et al. (1993) for each skull, and thresholds used for crown segmentation were set visually for each tooth separately. Data was analysed using discriminant function analysis and posterior probabilities were calculated for all produced formulae where sex was previously assessed from morphological features of pelvis and skull. Bootstrapping was used to account for small sample sizes in the analysis. Statistical analysis was carried out using SPSS 23. The percentage of sexual dimorphism was also used to quantify the amount of sexual dimorphism in the sample. The results showed that incisors and canines were the most sexually dimorphic teeth, providing percentages of correct sex classification between 80% and 100% depending on the measurement used. Root volume measurement was shown to be the most sexually dimorphic variable providing an accuracy of over 90% in all functions. The present study provided the first dental metric standards for sex estimation using odontometric data in Iranian archaeological populations. Dental measurements, particularly root volume measurements, were found to be of value for sex assessment and the method presented here could be a useful tool for establishing accurate demographic data from skeletal remains of the Iron Age from Iran.
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Tabulo, Moti M. "Radio resource management and metric estimation for multi-carrier CDMA systems." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/13065.

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This thesis investigates the management of radio resources in the physical layer (PHY and MAC layers of multi-carrier CDMA (MC-CDMA)) systems and how the estimation of metric sin the various layers may be used in performing a cross layer management of resources to provide increased QoS whilst making optimal usage of the radio resource. At the PHY layer, the grouping and subcarrier allocation problem for a grouped MC-CDMA system is formulated as an integer linear programming problem. Two algorithms are proposed to solve this problem, namely a Branch and Bound based algorithm and a mixed probabilistic-greedy Local Search algorithm. The Local Search algorithm is found to offer increased QoS (in terms of BER) for more users at a lower complexity than any of the other algorithms. At the MAC layer, a new multi-rate model - multi-group MC-CDMA (MG-MC-CDMA) - is introduced and the performance of power-control and multi-group allocation algorithms in the MG-MC-CDMA system examined. A weighted fair queuing scheduler that takes advantage of the particular features of the MG-MC-CDMA system is proposed. A capacity model, incorporating an interference analysis and that takes into account the nature of the traffic types carried in the system, is outlined. In addition to MAC layer metrics characterising the traffic in the system, the capacity model has, as some of its required metrics, PHY layer parameters such as the ratio of inter-cell interference to total received power and information of whether or not a mobile is in a cell’s edge region. New techniques are proposed to estimate these metrics. The final contribution of the thesis is the use of the proposed dynamic capacity estimation formwork to develop new radio resource management algorithms that work across the PHY and MAC layers to deliver enhanced QoS.
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Strobel, Matthias. "Estimation of minimum mean squared error with variable metric from censored observations." [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-35333.

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Engström, Isak. "Automated Gait Analysis : Using Deep Metric Learning." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178139.

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Sectors of security, safety, and defence require methods for identifying people on the individual level. Automation of these tasks has the potential of outperforming manual labor, as well as relieving workloads. The ever-extending surveillance camera networks, advances in human pose estimation from monocular cameras, together with the progress of deep learning techniques, pave the way for automated walking gait analysis as an identification method. This thesis investigates the use of 2D kinematic pose sequences to represent gait, monocularly extracted from a limited dataset containing walking individuals captured from five camera views. The sequential information of the gait is captured using recurrent neural networks. Techniques in deep metric learning are applied to evaluate two network models, with contrasting output dimensionalities, against deep-metric-, and non-deep-metric-based embedding spaces. The results indicate that the gait representation, network designs, and network learning structure show promise when identifying individuals, scaling particularly well to unseen individuals. However, with the limited dataset, the network models performed best when the dataset included the labels from both the individuals and the camera views simultaneously, contrary to when the data only contained the labels from the individuals without the information of the camera views. For further investigations, an extension of the data would be required to evaluate the accuracy and effectiveness of these methods, for the re-identification task of each individual.

Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

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Winden, Matthew Wayne. "INTEGRATING STATED PREFERENCE CHOICE ANALYSIS AND MULTI-METRIC INDICATORS IN ENVIRONMENTAL VALUATION." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343325594.

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Schenkel, Flávio Schramm. "Studies on effects of parental selection on estimation of genetic parameters and breeding values of metric traits." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ35812.pdf.

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Khodabandeloo, Babak, Dyan Melvin, and Hongki Jo. "Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties." MDPI AG, 2017. http://hdl.handle.net/10150/626477.

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Direct measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well.
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Rojas, Christian Andres. "Demand Estimation with Differentiated Products: An Application to Price Competition in the U.S. Brewing Industry." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28916.

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A large part of the empirical work on differentiated products markets has focused on demand estimation and the pricing behavior of firms. These two themes are key inputs in important applications such as the merging of two firms or the introduction of new products. The validity of inferences, therefore, depends on accurate demand estimates and sound assumptions about the pricing behavior of firms. This dissertation makes a contribution to this literature in two ways. First, it adds to previous techniques of estimating demand for differentiated products. Second, it extends previous analyses of pricing behavior to models of price leadership that, while important, have received limited attention. The investigation focuses on the U.S. brewing industry, where price leadership appears to be an important type of firm behavior. The analysis is conducted in two stages. In the first stage, the recent Distance Metric (DM) method devised by Pinkse, Slade and Brett is used to estimate the demand for 64 brands of beer in 58 major metropolitan areas of the United States. This study adds to previous applications of the DM method (Pinkse and Slade; Slade 2004) by employing a demand specification that is more flexible and also by estimating advertising substitution coefficients for numerous beer brands. In the second stage, different pricing models are compared and ranked by exploiting the exogenous change in the federal excise tax of 1991. Demand estimates of the first stage are used to compute the implied marginal costs for the different models of pricing behavior prior to the tax increase. Then, the tax increase is added to the these pre-tax increase marginal costs, and equilibrium prices for all brands are simulated for each model of pricing behavior. These "predicted" prices are then compared to actual prices for model assessment. Results indicate that Bertrand-Nash predicts the pricing behavior of firms more closely than other models, although Stackelberg leadership yields results that are not substanitally different from the Bertrand-Nash model. Nevertheless, Bertrand-Nash tends to under-predict prices of more price-elastic brands and to over-predict prices of less price- elastic brands. An implication of this result is that Anheuser-Busch could exert more market power by increasing the price of its highly inelastic brands, especially Budweiser. Overall, actual price movements as a result of the tax increase tend to be more similar across brands than predicted by any of the models considered. While this pattern is not inconsistent with leadership behavior, leadership models considered in this dissertation do not conform with this pattern.
Ph. D.
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Paditz, Ludwig. "On the error-bound in the nonuniform version of Esseen's inequality in the Lp-metric." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-112888.

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The aim of this paper is to investigate the known nonuniform version of Esseen's inequality in the Lp-metric, to get a numerical bound for the appearing constant L. For a long time the results given by several authors constate the impossibility of a nonuniform estimation in the most interesting case δ=1, because the effect L=L(δ)=O(1/(1-δ)), δ->1-0, was observed, where 2+δ, 0<δ<1, is the order of the assumed moments of the considered independent random variables X_k, k=1,2,...,n. Again making use of the method of conjugated distributions, we improve the well-known technique to show in the most interesting case δ=1 the finiteness of the absolute constant L and to prove L=L(1)=<127,74*7,31^(1/p), p>1. In the case 0<δ<1 we only give the analytical structure of L but omit numerical calculations. Finally an example on normal approximation of sums of l_2-valued random elements demonstrates the application of the nonuniform mean central limit bounds obtained here
Das Anliegen dieses Artikels besteht in der Untersuchung einer bekannten Variante der Esseen'schen Ungleichung in Form einer ungleichmäßigen Fehlerabschätzung in der Lp-Metrik mit dem Ziel, eine numerische Abschätzung für die auftretende absolute Konstante L zu erhalten. Längere Zeit erweckten die Ergebnisse, die von verschiedenen Autoren angegeben wurden, den Eindruck, dass die ungleichmäßige Fehlerabschätzung im interessantesten Fall δ=1 nicht möglich wäre, weil auf Grund der geführten Beweisschritte der Einfluss von δ auf L in der Form L=L(δ)=O(1/(1-δ)), δ->1-0, beobachtet wurde, wobei 2+δ, 0<δ<1, die Ordnung der vorausgesetzten Momente der betrachteten unabhängigen Zufallsgrößen X_k, k=1,2,...,n, angibt. Erneut wird die Methode der konjugierten Verteilungen angewendet und die gut bekannte Beweistechnik verbessert, um im interessantesten Fall δ=1 die Endlichkeit der absoluten Konstanten L nachzuweisen und um zu zeigen, dass L=L(1)=<127,74*7,31^(1/p), p>1, gilt. Im Fall 0<δ<1 wird nur die analytische Struktur von L herausgearbeitet, jedoch ohne numerische Berechnungen. Schließlich wird mit einem Beispiel zur Normalapproximation von Summen l_2-wertigen Zufallselementen die Anwendung der gewichteten Fehlerabschätzung im globalen zentralen Grenzwertsatz demonstriert
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Books on the topic "Metric estimation"

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Shoemaker, Robert W. Metric for me!: A layperson's guide to the metric system for everyday use with exercises, problems, and estimations. South Beloit, Ill: Blackhawk Metric Supply, 1993.

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W, Shoemaker Robert. Metric for me!: A layperson's guide to the metric system for everyday use with exercises, problems, and estimations. 2nd ed. South Beloit, Ill: Blackhawk Metric Supply Inc., 1998.

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Vanderhoof, Catherine, ed. Math Tests: No Problem! Application. New York, USA 1994: Scholastic Inc., 1994.

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Howard, Chandler, ed. Metric estimating seminar workbook. Kingston, MA: Means, 1992.

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Limit Theorems For Nonlinear Cointegrating Regression. Singapore, Hong Kong: WPSC, 2015.

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Chen, Min, J. Michael Dunn, Amos Golan, and Aman Ullah, eds. Advances in Info-Metrics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190636685.001.0001.

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Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In a recent book on the Foundations of Info-Metrics, Golan (OUP, 2018) provides the theoretical underpinning of info-metrics and the necessary tools and building blocks for using that framework. This volume complements Golan’s book and expands on the series of studies on the classical maximum entropy and Bayesian methods published in the different proceedings started with the seminal collection of Levine and Tribus (1979) and continuing annually. The objective of this volume is to expand the study of info-metrics, and information processing, across the sciences and to further explore the basis of information-theoretic inference and its mathematical and philosophical foundations. This volume is inherently interdisciplinary and applications oriented. It contains some of the recent developments in the field, as well as many new cross-disciplinary case studies and examples. The emphasis here is on the interrelationship between information and inference where we view the word ‘inference’ in its most general meaning – capturing all types of problem solving. That includes model building, theory creation, estimation, prediction, and decision making. The volume contains nineteen chapters in seven parts. Although chapters in each part are related, each chapter is self-contained; it provides the necessary tools for using the info-metrics framework for solving the problem confronted in that chapter. This volume is designed to be accessible for researchers, graduate students, and practitioners across the disciplines, requiring only some basic quantitative skills. The multidisciplinary nature and applications provide a hands-on experience for the reader.
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Allison, Diana. Estimating and Costing for Interior Designers. 2nd ed. Bloomsbury Publishing Inc, 2021. http://dx.doi.org/10.5040/9781501361081.

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Math is an essential component of the interior design profession. Estimating and Costing for Interior Designers, Second Edition, teaches readers a logical process for calculating materials and estimating the costs of installed products based on their math calculations. Fully updated and revised, this book utilizes step-by-step examples and worksheets to simplify the math used in the interior design field. Sample problems and exercises take the calculations of quantities needed one step further to actually applying material and labor costs, in order to discover the installed costs of the specified products. Exercises are provided in introductory, intermediate, and advanced levels for all types of interior designers. Clear sections cover wall and ceiling treatments, window treatments, soft fabrications, upholstery, flooring, and cabinetry and countertops, making this book applicable to both commercial and residential design projects. New to This Edition -Key pedagogical features including: learning objectives, key terms, chapter summaries, imperial and metric units, professional tips, and glossary. -Student STUDIO materials including: calculation worksheets, schedules/cost worksheets, practice examples, and flashcards. -Robust Instructor Resources including: a revised instructor’s guide, test questions, additional practice exercises and answers, PowerPoints lecture slides, and Excel worksheets.
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Hildebrand, Maria, and Ulf Ekelund. The assessment of physical activity. Edited by Neil Armstrong and Willem van Mechelen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198757672.003.0021.

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Physical activity (PA) is a complex human behaviour that comprises several dimensions, including intensity, frequency, duration, type/mode, and domain. PA outcomes can be divided into two main categories: the estimation of energy expenditure, and other quantifying metrics of PA. Subjective methods, including questionnaires and diaries, are often easy to use, cost-effective and are able to assess type of PA and to rank PA levels. However, they are prone to several limitations and are not able to provide accurate estimates of PA, energy expenditure, or intensity. Objective methods, including accelerometers and heart rate monitors, provide a reasonably accurate quantification of intensity, frequency, duration, and PA energy expenditure. When choosing a method for assessing PA several factors need to be considered, including validity, reliability, accuracy, and responsiveness, as well as the purpose of the study, the population being studied, and the outcome of interest.
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Book chapters on the topic "Metric estimation"

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Le Cam, L. "Metric dimension and statistical estimation." In CRM Proceedings and Lecture Notes, 303–11. Providence, Rhode Island: American Mathematical Society, 1997. http://dx.doi.org/10.1090/crmp/011/14.

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Sommer, Stefan, Alexis Arnaudon, Line Kuhnel, and Sarang Joshi. "Bridge Simulation and Metric Estimation on Landmark Manifolds." In Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 79–91. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67675-3_8.

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Zheng, Wenzhao, Jiwen Lu, and Jie Zhou. "Structural Deep Metric Learning for Room Layout Estimation." In Computer Vision – ECCV 2020, 735–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58523-5_43.

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Jensen, Mathias Højgaard, Sarang Joshi, and Stefan Sommer. "Bridge Simulation and Metric Estimation on Lie Groups." In Lecture Notes in Computer Science, 430–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80209-7_47.

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Zolfaghari, Mohammadreza, Morteza Ghareh Gozlou, and Mohammad Taghi Manzuri Shalmani. "Multiple Metric Learning for Graph Based Human Pose Estimation." In Neural Information Processing, 200–208. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42051-1_26.

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Xiao, Bo, Xiaokang Yang, Hongyuan Zha, Yi Xu, and Thomas S. Huang. "Metric Learning for Regression Problems and Human Age Estimation." In Advances in Multimedia Information Processing - PCM 2009, 88–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10467-1_7.

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Pan, Leting. "Human Age Estimation by Metric Learning for Regression Problems." In Lecture Notes in Computer Science, 455–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03641-5_34.

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Okarma, Krzysztof, and Przemysław Mazurek. "GPGPU Based Estimation of the Combined Video Quality Metric." In Advances in Intelligent and Soft Computing, 285–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23154-4_32.

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Long, Yangjing. "Retracted: Human Age Estimation by Metric Learning for Regression Problems." In Computer Analysis of Images and Patterns, 74–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_9.

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Long, Yangjing. "Erratum to: Human Age Estimation by Metric Learning for Regression Problems." In Computer Analysis of Images and Patterns, E2. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_152.

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Conference papers on the topic "Metric estimation"

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Pandey, Amit. "Stall estimation metric: An architectural metric for estimating software complexity." In 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2016. http://dx.doi.org/10.1109/icrito.2016.7784987.

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Sedighi Maman, Zahra, Amir Baghdadi, Fadel Megahed, and Lora Cavuoto. "Monitoring and Change Point Estimation of Normal (In-Control) and Fatigued (Out-of-Control) State in Workers." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60487.

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This paper presents a fused metric for the assessment of physical workload that can improve fatigue detection using a statistical visualization approach. The goal for considering this combined metric is to concisely reduce the number of variables acquired from multiple sensors. The sensor system gathers data from a heart rate monitor and accelerometers placed at different locations on the body including trunk, wrist, hip and ankle. Two common manufacturing tasks of manual material handling and small parts assembly were tested. Statistical process control was used to monitor the metrics for the workload state of the human body. A cumulative sum (CUSUM) statistical analysis was applied to each of the single metrics and the combined metric of heart rate reserve and acceleration (HRR*ACC). The sensor data were transformed to linear profiles by using the CUSUM plot, which can be monitored by profile monitoring techniques. A significant variation between the lifting replications was observed for the combined metric in comparison to the single metrics, which is an important factor in selecting a fused metric. The results show that the proposed approach can improve the ability to detect different states (i.e., fatigue vs. non-fatigued) in the human body.
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Simon, Donald L. "Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-43744.

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This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.
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Pons-Moll, Gerard, Jonathan Taylor, Jamie Shotton, Aaron Hertzmann, and Andrew Fitzgibbon. "Metric Regression Forests for Human Pose Estimation." In British Machine Vision Conference 2013. British Machine Vision Association, 2013. http://dx.doi.org/10.5244/c.27.4.

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Lee, Mong-Shu, and Kuan-Chih Chiu. "Objective smoothness metric for just noticeable blur estimation." In 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2016. http://dx.doi.org/10.1109/cisp-bmei.2016.7852800.

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Jang, Mingyu, Yoonji Kim, Geunbae Kim, Dongweon Yoon, and Cheol-sun Park. "Blind Estimation of Interleaving Parameter Using Soft Metric." In 2020 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2020. http://dx.doi.org/10.1109/ictc49870.2020.9289374.

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Tran, Duc A., and Thuy T. Do. "Power-of-Metric Embedding for Network Dissimilarity Estimation." In 2018 IEEE International Conference on Communications (ICC 2018). IEEE, 2018. http://dx.doi.org/10.1109/icc.2018.8422286.

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Ye, Qingqing, Haibo Hu, Man Ho Au, Xiaofeng Meng, and Xiaokui Xiao. "Towards Locally Differentially Private Generic Graph Metric Estimation." In 2020 IEEE 36th International Conference on Data Engineering (ICDE). IEEE, 2020. http://dx.doi.org/10.1109/icde48307.2020.00204.

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Foster, Chad R. "Test Uncertainty and Failure Mode Discovery." In ASME 2014 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icef2014-5421.

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An uncertainty metric is used to prioritize testing for initial product development. Similar metrics are used in signal processing, cryptography, and digital communication. The greatest benefit of this metric is to maximize testing value to discover failures. A major drawback is a reduction in the accuracy of launch reliability estimates. A preferred approach uses two separate testing processes, the first will increase the initial issue discovery using the uncertainty metric while the second increases the accuracy of the reliability estimation. Engine development data is presented to highlight the application of this metric for both engine and vehicle testing.
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Sun, Zeyu, and Sei-ichiro Kamata. "Second-Order Estimation Based Attention Network for Metric Learning." In 2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR). IEEE, 2020. http://dx.doi.org/10.1109/icievicivpr48672.2020.9306560.

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Reports on the topic "Metric estimation"

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Traina, Caetano, Traina Jr., Faloutsos Agma J., and Christos. Distance Exponent: A New Concept for Selectivity Estimation in Metric Trees. Fort Belvoir, VA: Defense Technical Information Center, March 1999. http://dx.doi.org/10.21236/ada363780.

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Banks, H. T., and W. C. Thompson. Least Squares Estimation of Probability Measures in the Prohorov Metric Framework. Fort Belvoir, VA: Defense Technical Information Center, November 2012. http://dx.doi.org/10.21236/ada573681.

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Downing, W. Logan, Howell Li, William T. Morgan, Cassandra McKee, and Darcy M. Bullock. Using Probe Data Analytics for Assessing Freeway Speed Reductions during Rain Events. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317350.

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Rain impacts roadways such as wet pavement, standing water, decreased visibility, and wind gusts and can lead to hazardous driving conditions. This study investigates the use of high fidelity Doppler data at 1 km spatial and 2-minute temporal resolution in combination with commercial probe speed data on freeways. Segment-based space-mean speeds were used and drops in speeds during rainfall events of 5.5 mm/hour or greater over a one-month period on a section of four to six-lane interstate were assessed. Speed reductions were evaluated as a time series over a 1-hour window with the rain data. Three interpolation methods for estimating rainfall rates were tested and seven metrics were developed for the analysis. The study found sharp drops in speed of more than 40 mph occurred at estimated rainfall rates of 30 mm/hour or greater, but the drops did not become more severe beyond this threshold. The average time of first detected rainfall to impacting speeds was 17 minutes. The bilinear method detected the greatest number of events during the 1-month period, with the most conservative rate of predicted rainfall. The range of rainfall intensities were estimated between 7.5 to 106 mm/hour for the 39 events. This range was much greater than the heavy rainfall categorization at 16 mm/hour in previous studies reported in the literature. The bilinear interpolation method for Doppler data is recommended because it detected the greatest number of events and had the longest rain duration and lowest estimated maximum rainfall out of three methods tested, suggesting the method balanced awareness of the weather conditions around the roadway with isolated, localized rain intensities.
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