WorldWideScience

Sample records for metric based rules

  1. On ruled surface in 3-dimensional almost contact metric manifold

    Science.gov (United States)

    Karacan, Murat Kemal; Yuksel, Nural; Ikiz, Hasibe

    In this paper, we study ruled surface in 3-dimensional almost contact metric manifolds by using surface theory defined by Gök [Surfaces theory in contact geometry, PhD thesis (2010)]. We also studied the theory of curves using cross product defined by Camcı. In this study, we obtain the distribution parameters of the ruled surface and then some results and theorems are presented with special cases. Moreover, some relationships among asymptotic curve and striction line of the base curve of the ruled surface have been found.

  2. Recommended metric for tracking visibility progress in the Regional Haze Rule.

    Science.gov (United States)

    Gantt, Brett; Beaver, Melinda; Timin, Brian; Lorang, Phil

    2018-05-01

    For many national parks and wilderness areas with special air quality protections (Class I areas) in the western United States (U.S.), wildfire smoke and dust events can have a large impact on visibility. The U.S. Environmental Protection Agency's (EPA) 1999 Regional Haze Rule used the 20% haziest days to track visibility changes over time even if they are dominated by smoke or dust. Visibility on the 20% haziest days has remained constant or degraded over the last 16 yr at some Class I areas despite widespread emission reductions from anthropogenic sources. To better track visibility changes specifically associated with anthropogenic pollution sources rather than natural sources, the EPA has revised the Regional Haze Rule to track visibility on the 20% most anthropogenically impaired (hereafter, most impaired) days rather than the haziest days. To support the implementation of this revised requirement, the EPA has proposed (but not finalized) a recommended metric for characterizing the anthropogenic and natural portions of the daily extinction budget at each site. This metric selects the 20% most impaired days based on these portions using a "delta deciview" approach to quantify the deciview scale impact of anthropogenic light extinction. Using this metric, sulfate and nitrate make up the majority of the anthropogenic extinction in 2015 on these days, with natural extinction largely made up of organic carbon mass in the eastern U.S. and a combination of organic carbon mass, dust components, and sea salt in the western U.S. For sites in the western U.S., the seasonality of days selected as the 20% most impaired is different than the seasonality of the 20% haziest days, with many more winter and spring days selected. Applying this new metric to the 2000-2015 period across sites representing Class I areas results in substantial changes in the calculated visibility trend for the northern Rockies and southwest U.S., but little change for the eastern U.S. Changing the

  3. A rule-based software test data generator

    Science.gov (United States)

    Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

    1991-01-01

    Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

  4. Standardized reporting of functioning information on ICF-based common metrics.

    Science.gov (United States)

    Prodinger, Birgit; Tennant, Alan; Stucki, Gerold

    2018-02-01

    In clinical practice and research a variety of clinical data collection tools are used to collect information on people's functioning for clinical practice and research and national health information systems. Reporting on ICF-based common metrics enables standardized documentation of functioning information in national health information systems. The objective of this methodological note on applying the ICF in rehabilitation is to demonstrate how to report functioning information collected with a data collection tool on ICF-based common metrics. We first specify the requirements for the standardized reporting of functioning information. Secondly, we introduce the methods needed for transforming functioning data to ICF-based common metrics. Finally, we provide an example. The requirements for standardized reporting are as follows: 1) having a common conceptual framework to enable content comparability between any health information; and 2) a measurement framework so that scores between two or more clinical data collection tools can be directly compared. The methods needed to achieve these requirements are the ICF Linking Rules and the Rasch measurement model. Using data collected incorporating the 36-item Short Form Health Survey (SF-36), the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), and the Stroke Impact Scale 3.0 (SIS 3.0), the application of the standardized reporting based on common metrics is demonstrated. A subset of items from the three tools linked to common chapters of the ICF (d4 Mobility, d5 Self-care and d6 Domestic life), were entered as "super items" into the Rasch model. Good fit was achieved with no residual local dependency and a unidimensional metric. A transformation table allows for comparison between scales, and between a scale and the reporting common metric. Being able to report functioning information collected with commonly used clinical data collection tools with ICF-based common metrics enables clinicians

  5. Value-based metrics and Internet-based enterprises

    Science.gov (United States)

    Gupta, Krishan M.

    2001-10-01

    Within the last few years, a host of value-based metrics like EVA, MVA, TBR, CFORI, and TSR have evolved. This paper attempts to analyze the validity and applicability of EVA and Balanced Scorecard for Internet based organizations. Despite the collapse of the dot-com model, the firms engaged in e- commerce continue to struggle to find new ways to account for customer-base, technology, employees, knowledge, etc, as part of the value of the firm. While some metrics, like the Balance Scorecard are geared towards internal use, others like EVA are for external use. Value-based metrics are used for performing internal audits as well as comparing firms against one another; and can also be effectively utilized by individuals outside the firm looking to determine if the firm is creating value for its stakeholders.

  6. A Rule Based Approach to ISS Interior Volume Control and Layout

    Science.gov (United States)

    Peacock, Brian; Maida, Jim; Fitts, David; Dory, Jonathan

    2001-01-01

    Traditional human factors design involves the development of human factors requirements based on a desire to accommodate a certain percentage of the intended user population. As the product is developed human factors evaluation involves comparison between the resulting design and the specifications. Sometimes performance metrics are involved that allow leniency in the design requirements given that the human performance result is satisfactory. Clearly such approaches may work but they give rise to uncertainty and negotiation. An alternative approach is to adopt human factors design rules that articulate a range of each design continuum over which there are varying outcome expectations and interactions with other variables, including time. These rules are based on a consensus of human factors specialists, designers, managers and customers. The International Space Station faces exactly this challenge in interior volume control, which is based on anthropometric, performance and subjective preference criteria. This paper describes the traditional approach and then proposes a rule-based alternative. The proposed rules involve spatial, temporal and importance dimensions. If successful this rule-based concept could be applied to many traditional human factors design variables and could lead to a more effective and efficient contribution of human factors input to the design process.

  7. Energy-Based Metrics for Arthroscopic Skills Assessment.

    Science.gov (United States)

    Poursartip, Behnaz; LeBel, Marie-Eve; McCracken, Laura C; Escoto, Abelardo; Patel, Rajni V; Naish, Michael D; Trejos, Ana Luisa

    2017-08-05

    Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency.

  8. MESUR: USAGE-BASED METRICS OF SCHOLARLY IMPACT

    Energy Technology Data Exchange (ETDEWEB)

    BOLLEN, JOHAN [Los Alamos National Laboratory; RODRIGUEZ, MARKO A. [Los Alamos National Laboratory; VAN DE SOMPEL, HERBERT [Los Alamos National Laboratory

    2007-01-30

    The evaluation of scholarly communication items is now largely a matter of expert opinion or metrics derived from citation data. Both approaches can fail to take into account the myriad of factors that shape scholarly impact. Usage data has emerged as a promising complement to existing methods o fassessment but the formal groundwork to reliably and validly apply usage-based metrics of schlolarly impact is lacking. The Andrew W. Mellon Foundation funded MESUR project constitutes a systematic effort to define, validate and cross-validate a range of usage-based metrics of schlolarly impact by creating a semantic model of the scholarly communication process. The constructed model will serve as the basis of a creating a large-scale semantic network that seamlessly relates citation, bibliographic and usage data from a variety of sources. A subsequent program that uses the established semantic network as a reference data set will determine the characteristics and semantics of a variety of usage-based metrics of schlolarly impact. This paper outlines the architecture and methodology adopted by the MESUR project and its future direction.

  9. Advanced spatial metrics analysis in cellular automata land use and cover change modeling

    International Nuclear Information System (INIS)

    Zamyatin, Alexander; Cabral, Pedro

    2011-01-01

    This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.

  10. Evaluation of Vehicle-Based Crash Severity Metrics.

    Science.gov (United States)

    Tsoi, Ada H; Gabler, Hampton C

    2015-01-01

    Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes. The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000-2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2-) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy. The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric

  11. Retrospective group fusion similarity search based on eROCE evaluation metric.

    Science.gov (United States)

    Avram, Sorin I; Crisan, Luminita; Bora, Alina; Pacureanu, Liliana M; Avram, Stefana; Kurunczi, Ludovic

    2013-03-01

    In this study, a simple evaluation metric, denoted as eROCE was proposed to measure the early enrichment of predictive methods. We demonstrated the superior robustness of eROCE compared to other known metrics throughout several active to inactive ratios ranging from 1:10 to 1:1000. Group fusion similarity search was investigated by varying 16 similarity coefficients, five molecular representations (binary and non-binary) and two group fusion rules using two reference structure set sizes. We used a dataset of 3478 actives and 43,938 inactive molecules and the enrichment was analyzed by means of eROCE. This retrospective study provides optimal similarity search parameters in the case of ALDH1A1 inhibitors. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Evaluating hydrological model performance using information theory-based metrics

    Science.gov (United States)

    The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...

  13. Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2013-01-01

    Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  14. Attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm.

    Science.gov (United States)

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

    In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  15. Rule-Based Event Processing and Reaction Rules

    Science.gov (United States)

    Paschke, Adrian; Kozlenkov, Alexander

    Reaction rules and event processing technologies play a key role in making business and IT / Internet infrastructures more agile and active. While event processing is concerned with detecting events from large event clouds or streams in almost real-time, reaction rules are concerned with the invocation of actions in response to events and actionable situations. They state the conditions under which actions must be taken. In the last decades various reaction rule and event processing approaches have been developed, which for the most part have been advanced separately. In this paper we survey reaction rule approaches and rule-based event processing systems and languages.

  16. Ideal Based Cyber Security Technical Metrics for Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    W. F. Boyer; M. A. McQueen

    2007-10-01

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

  17. Operator-based metric for nuclear operations automation assessment

    Energy Technology Data Exchange (ETDEWEB)

    Zacharias, G.L.; Miao, A.X.; Kalkan, A. [Charles River Analytics Inc., Cambridge, MA (United States)] [and others

    1995-04-01

    Continuing advances in real-time computational capabilities will support enhanced levels of smart automation and AI-based decision-aiding systems in the nuclear power plant (NPP) control room of the future. To support development of these aids, we describe in this paper a research tool, and more specifically, a quantitative metric, to assess the impact of proposed automation/aiding concepts in a manner that can account for a number of interlinked factors in the control room environment. In particular, we describe a cognitive operator/plant model that serves as a framework for integrating the operator`s information-processing capabilities with his procedural knowledge, to provide insight as to how situations are assessed by the operator, decisions made, procedures executed, and communications conducted. Our focus is on the situation assessment (SA) behavior of the operator, the development of a quantitative metric reflecting overall operator awareness, and the use of this metric in evaluating automation/aiding options. We describe the results of a model-based simulation of a selected emergency scenario, and metric-based evaluation of a range of contemplated NPP control room automation/aiding options. The results demonstrate the feasibility of model-based analysis of contemplated control room enhancements, and highlight the need for empirical validation.

  18. Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

    Science.gov (United States)

    Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

    Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.

  19. The Death of Socrates: Managerialism, Metrics and Bureaucratisation in Universities

    Science.gov (United States)

    Orr, Yancey; Orr, Raymond

    2016-01-01

    Neoliberalism exults the ability of unregulated markets to optimise human relations. Yet, as David Graeber has recently illustrated, it is paradoxically built on rigorous systems of rules, metrics and managers. The potential transition to a market-based tuition and research-funding model for higher education in Australia has, not surprisingly,…

  20. Designing Industrial Networks Using Ecological Food Web Metrics.

    Science.gov (United States)

    Layton, Astrid; Bras, Bert; Weissburg, Marc

    2016-10-18

    Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

  1. Comparison of luminance based metrics in different lighting conditions

    DEFF Research Database (Denmark)

    Wienold, J.; Kuhn, T.E.; Christoffersen, J.

    In this study, we evaluate established and newly developed metrics for predicting glare using data from three different research studies. The evaluation covers two different targets: 1. How well the user’s perception of glare magnitude correlates to the prediction of the glare metrics? 2. How well...... do the glare metrics describe the subjects’ disturbance by glare? We applied Spearman correlations, logistic regressions and an accuracy evaluation, based on an ROC-analysis. The results show that five of the twelve investigated metrics are failing at least one of the statistical tests. The other...... seven metrics CGI, modified DGI, DGP, Ev, average Luminance of the image Lavg, UGP and UGR are passing all statistical tests. DGP, CGI, DGI_mod and UGP have largest AUC and might be slightly more robust. The accuracy of the predictions of afore mentioned seven metrics for the disturbance by glare lies...

  2. Metrics for assessing retailers based on consumer perception

    Directory of Open Access Journals (Sweden)

    Klimin Anastasii

    2017-01-01

    Full Text Available The article suggests a new look at trading platforms, which is called “metrics.” Metrics are a way to look at the point of sale in a large part from the buyer’s side. The buyer enters the store and make buying decision based on those factors that the seller often does not consider, or considers in part, because “does not see” them, since he is not a buyer. The article proposes the classification of retailers, metrics and a methodology for their determination, presents the results of an audit of retailers in St. Petersburg on the proposed methodology.

  3. A Metrical Theory of Stress and Destressing in English and Dutch

    NARCIS (Netherlands)

    Kager, R.W.J.

    1989-01-01

    The topic of this study is word stress, more specifically the relation between rules of stress and destressing within the framework of metrical phonology. Our claims will be largely based on in-depth analyses of two word stress systems: those of English and Dutch. We intend to offer a

  4. Gamut Volume Index: a color preference metric based on meta-analysis and optimized colour samples.

    Science.gov (United States)

    Liu, Qiang; Huang, Zheng; Xiao, Kaida; Pointer, Michael R; Westland, Stephen; Luo, M Ronnier

    2017-07-10

    A novel metric named Gamut Volume Index (GVI) is proposed for evaluating the colour preference of lighting. This metric is based on the absolute gamut volume of optimized colour samples. The optimal colour set of the proposed metric was obtained by optimizing the weighted average correlation between the metric predictions and the subjective ratings for 8 psychophysical studies. The performance of 20 typical colour metrics was also investigated, which included colour difference based metrics, gamut based metrics, memory based metrics as well as combined metrics. It was found that the proposed GVI outperformed the existing counterparts, especially for the conditions where correlated colour temperatures differed.

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

    DEFF Research Database (Denmark)

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

    2018-01-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  7. PSQM-based RR and NR video quality metrics

    Science.gov (United States)

    Lu, Zhongkang; Lin, Weisi; Ong, Eeping; Yang, Xiaokang; Yao, Susu

    2003-06-01

    This paper presents a new and general concept, PQSM (Perceptual Quality Significance Map), to be used in measuring the visual distortion. It makes use of the selectivity characteristic of HVS (Human Visual System) that it pays more attention to certain area/regions of visual signal due to one or more of the following factors: salient features in image/video, cues from domain knowledge, and association of other media (e.g., speech or audio). PQSM is an array whose elements represent the relative perceptual-quality significance levels for the corresponding area/regions for images or video. Due to its generality, PQSM can be incorporated into any visual distortion metrics: to improve effectiveness or/and efficiency of perceptual metrics; or even to enhance a PSNR-based metric. A three-stage PQSM estimation method is also proposed in this paper, with an implementation of motion, texture, luminance, skin-color and face mapping. Experimental results show the scheme can improve the performance of current image/video distortion metrics.

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

    Directory of Open Access Journals (Sweden)

    Welington M da Silva

    2012-01-01

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

  9. Quality Evaluation in Wireless Imaging Using Feature-Based Objective Metrics

    OpenAIRE

    Engelke, Ulrich; Zepernick, Hans-Jürgen

    2007-01-01

    This paper addresses the evaluation of image quality in the context of wireless systems using feature-based objective metrics. The considered metrics comprise of a weighted combination of feature values that are used to quantify the extend by which the related artifacts are present in a processed image. In view of imaging applications in mobile radio and wireless communication systems, reduced-reference objective quality metrics are investigated for quantifying user-perceived quality. The exa...

  10. Analysis of Subjects' Vulnerability in a Touch Screen Game Using Behavioral Metrics.

    Science.gov (United States)

    Parsinejad, Payam; Sipahi, Rifat

    2017-12-01

    In this article, we report results on an experimental study conducted with volunteer subjects playing a touch-screen game with two unique difficulty levels. Subjects have knowledge about the rules of both game levels, but only sufficient playing experience with the easy level of the game, making them vulnerable with the difficult level. Several behavioral metrics associated with subjects' playing the game are studied in order to assess subjects' mental-workload changes induced by their vulnerability. Specifically, these metrics are calculated based on subjects' finger kinematics and decision making times, which are then compared with baseline metrics, namely, performance metrics pertaining to how well the game is played and a physiological metric called pnn50 extracted from heart rate measurements. In balanced experiments and supported by comparisons with baseline metrics, it is found that some of the studied behavioral metrics have the potential to be used to infer subjects' mental workload changes through different levels of the game. These metrics, which are decoupled from task specifics, relate to subjects' ability to develop strategies to play the game, and hence have the advantage of offering insight into subjects' task-load and vulnerability assessment across various experimental settings.

  11. Methodological approaches based on business rules

    Directory of Open Access Journals (Sweden)

    Anca Ioana ANDREESCU

    2008-01-01

    Full Text Available Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize the rules and move them outside the application. This paper analyzes and evaluates three well-known business rules approaches. It also outlines some critical factors that have to be taken into account in the decision to introduce business rules facilities in a software system. Based on the concept of explicit manipulation of business rules in a software system, the need for a general approach based on business rules is discussed.

  12. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  13. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

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

    Directory of Open Access Journals (Sweden)

    George S. Eskander Ekladious

    2017-11-01

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

  15. Using Rule-Based Computer Programming to Unify Communication Rules Research.

    Science.gov (United States)

    Sanford, David L.; Roach, J. W.

    This paper proposes the use of a rule-based computer programming language as a standard for the expression of rules, arguing that the adoption of a standard would enable researchers to communicate about rules in a consistent and significant way. Focusing on the formal equivalence of artificial intelligence (AI) programming to different types of…

  16. Evaluative Usage-Based Metrics for the Selection of E-Journals.

    Science.gov (United States)

    Hahn, Karla L.; Faulkner, Lila A.

    2002-01-01

    Explores electronic journal usage statistics and develops three metrics and three benchmarks based on those metrics. Topics include earlier work that assessed the value of print journals and was modified for the electronic format; the evaluation of potential purchases; and implications for standards development, including the need for content…

  17. Moral empiricism and the bias for act-based rules.

    Science.gov (United States)

    Ayars, Alisabeth; Nichols, Shaun

    2017-10-01

    Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the

  18. A C++ Class for Rule-Base Objects

    Directory of Open Access Journals (Sweden)

    William J. Grenney

    1992-01-01

    Full Text Available A C++ class, called Tripod, was created as a tool to assist with the development of rule-base decision support systems. The Tripod class contains data structures for the rule-base and member functions for operating on the data. The rule-base is defined by three ASCII files. These files are translated by a preprocessor into a single file that is located when a rule-base object is instantiated. The Tripod class was tested as part of a proto-type decision support system (DSS for winter highway maintenance in the Intermountain West. The DSS is composed of two principal modules: the main program, called the wrapper, and a Tripod rule-base object. The wrapper is a procedural module that interfaces with remote sensors and an external meterological database. The rule-base contains the logic for advising an inexperienced user and for assisting with the decision making process.

  19. Connection Setup Signaling Scheme with Flooding-Based Path Searching for Diverse-Metric Network

    Science.gov (United States)

    Kikuta, Ko; Ishii, Daisuke; Okamoto, Satoru; Oki, Eiji; Yamanaka, Naoaki

    Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

  20. Determination of a Screening Metric for High Diversity DNA Libraries.

    Science.gov (United States)

    Guido, Nicholas J; Handerson, Steven; Joseph, Elaine M; Leake, Devin; Kung, Li A

    2016-01-01

    The fields of antibody engineering, enzyme optimization and pathway construction rely increasingly on screening complex variant DNA libraries. These highly diverse libraries allow researchers to sample a maximized sequence space; and therefore, more rapidly identify proteins with significantly improved activity. The current state of the art in synthetic biology allows for libraries with billions of variants, pushing the limits of researchers' ability to qualify libraries for screening by measuring the traditional quality metrics of fidelity and diversity of variants. Instead, when screening variant libraries, researchers typically use a generic, and often insufficient, oversampling rate based on a common rule-of-thumb. We have developed methods to calculate a library-specific oversampling metric, based on fidelity, diversity, and representation of variants, which informs researchers, prior to screening the library, of the amount of oversampling required to ensure that the desired fraction of variant molecules will be sampled. To derive this oversampling metric, we developed a novel alignment tool to efficiently measure frequency counts of individual nucleotide variant positions using next-generation sequencing data. Next, we apply a method based on the "coupon collector" probability theory to construct a curve of upper bound estimates of the sampling size required for any desired variant coverage. The calculated oversampling metric will guide researchers to maximize their efficiency in using highly variant libraries.

  1. Determination of a Screening Metric for High Diversity DNA Libraries.

    Directory of Open Access Journals (Sweden)

    Nicholas J Guido

    Full Text Available The fields of antibody engineering, enzyme optimization and pathway construction rely increasingly on screening complex variant DNA libraries. These highly diverse libraries allow researchers to sample a maximized sequence space; and therefore, more rapidly identify proteins with significantly improved activity. The current state of the art in synthetic biology allows for libraries with billions of variants, pushing the limits of researchers' ability to qualify libraries for screening by measuring the traditional quality metrics of fidelity and diversity of variants. Instead, when screening variant libraries, researchers typically use a generic, and often insufficient, oversampling rate based on a common rule-of-thumb. We have developed methods to calculate a library-specific oversampling metric, based on fidelity, diversity, and representation of variants, which informs researchers, prior to screening the library, of the amount of oversampling required to ensure that the desired fraction of variant molecules will be sampled. To derive this oversampling metric, we developed a novel alignment tool to efficiently measure frequency counts of individual nucleotide variant positions using next-generation sequencing data. Next, we apply a method based on the "coupon collector" probability theory to construct a curve of upper bound estimates of the sampling size required for any desired variant coverage. The calculated oversampling metric will guide researchers to maximize their efficiency in using highly variant libraries.

  2. A Constructivist Approach to Rule Bases

    NARCIS (Netherlands)

    Sileno, G.; Boer, A.; van Engers, T.; Loiseau, S.; Filipe, J.; Duval, B.; van den Herik, J.

    2015-01-01

    The paper presents a set of algorithms for the conversion of rule bases between priority-based and constraint-based representations. Inspired by research in precedential reasoning in law, such algorithms can be used for the analysis of a rule base, and for the study of the impact of the introduction

  3. Integrated Case Based and Rule Based Reasoning for Decision Support

    OpenAIRE

    Eshete, Azeb Bekele

    2009-01-01

    This project is a continuation of my specialization project which was focused on studying theoretical concepts related to case based reasoning method, rule based reasoning method and integration of them. The integration of rule-based and case-based reasoning methods has shown a substantial improvement with regards to performance over the individual methods. Verdande Technology As wants to try integrating the rule based reasoning method with an existing case based system. This project focu...

  4. GPS Device Testing Based on User Performance Metrics

    Science.gov (United States)

    2015-10-02

    1. Rationale for a Test Program Based on User Performance Metrics ; 2. Roberson and Associates Test Program ; 3. Status of, and Revisions to, the Roberson and Associates Test Program ; 4. Comparison of Roberson and DOT/Volpe Programs

  5. Monitor-Based Statistical Model Checking for Weighted Metric Temporal Logic

    DEFF Research Database (Denmark)

    Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand

    2012-01-01

    We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction with desi......We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction...

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

    Science.gov (United States)

    Ni, Zhuang; Liu, Kui; Kang, Guixia

    2018-04-01

    Distance metric learning algorithm has been widely applied to medical diagnosis and exhibited its strengths in classification problems. The k-nearest neighbour (KNN) is an efficient method which treats each feature equally. The large margin nearest neighbour classification (LMNN) improves the accuracy of KNN by learning a global distance metric, which did not consider the locality of data distributions. In this paper, we propose a new distance metric algorithm adopting cosine metric and LMNN named COS-SUBLMNN which takes more care about local feature of data to overcome the shortage of LMNN and improve the classification accuracy. The proposed methodology is verified on CVDs patient vector derived from real-world medical data. The Experimental results show that our method provides higher accuracy than KNN and LMNN did, which demonstrates the effectiveness of the Risk predictive model of CVDs based on COS-SUBLMNN.

  7. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  8. A step-indexed Kripke model of hidden state via recursive properties on recursively defined metric spaces

    DEFF Research Database (Denmark)

    Birkedal, Lars; Schwinghammer, Jan; Støvring, Kristian

    2010-01-01

    for Chargu´eraud and Pottier’s type and capability system including frame and anti-frame rules, based on the operational semantics and step-indexed heap relations. The worlds are constructed as a recursively defined predicate on a recursively defined metric space, which provides a considerably simpler...

  9. Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography–Based Metrics

    Energy Technology Data Exchange (ETDEWEB)

    Niedzielski, Joshua S., E-mail: jsniedzielski@mdanderson.org [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Yang, Jinzhong [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Stingo, Francesco [Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Martel, Mary K.; Mohan, Radhe [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Gomez, Daniel R. [Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Briere, Tina M. [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Liao, Zhongxing [Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Court, Laurence E. [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States)

    2016-02-01

    Purpose: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy. Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method was validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis. Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively. Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced

  10. Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography–Based Metrics

    International Nuclear Information System (INIS)

    Niedzielski, Joshua S.; Yang, Jinzhong; Stingo, Francesco; Martel, Mary K.; Mohan, Radhe; Gomez, Daniel R.; Briere, Tina M.; Liao, Zhongxing; Court, Laurence E.

    2016-01-01

    Purpose: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy. Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method was validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis. Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively. Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced

  11. Concordance-based Kendall's Correlation for Computationally-Light vs. Computationally-Heavy Centrality Metrics: Lower Bound for Correlation

    Directory of Open Access Journals (Sweden)

    Natarajan Meghanathan

    2017-01-01

    Full Text Available We identify three different levels of correlation (pair-wise relative ordering, network-wide ranking and linear regression that could be assessed between a computationally-light centrality metric and a computationally-heavy centrality metric for real-world networks. The Kendall's concordance-based correlation measure could be used to quantitatively assess how well we could consider the relative ordering of two vertices vi and vj with respect to a computationally-light centrality metric as the relative ordering of the same two vertices with respect to a computationally-heavy centrality metric. We hypothesize that the pair-wise relative ordering (concordance-based assessment of the correlation between centrality metrics is the most strictest of all the three levels of correlation and claim that the Kendall's concordance-based correlation coefficient will be lower than the correlation coefficient observed with the more relaxed levels of correlation measures (linear regression-based Pearson's product-moment correlation coefficient and the network wide ranking-based Spearman's correlation coefficient. We validate our hypothesis by evaluating the three correlation coefficients between two sets of centrality metrics: the computationally-light degree and local clustering coefficient complement-based degree centrality metrics and the computationally-heavy eigenvector centrality, betweenness centrality and closeness centrality metrics for a diverse collection of 50 real-world networks.

  12. Fusion set selection with surrogate metric in multi-atlas based image segmentation

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2016-01-01

    Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation. (paper)

  13. Dynamic Rule Encryption for Mobile Payment

    Directory of Open Access Journals (Sweden)

    Emir Husni

    2017-01-01

    Full Text Available The trend of financial transactions by using a mobile phone or mobile payment increases. By using the mobile payment service, users can save money on mobile phone (handset and separate from the pulse. For protecting users, mobile payment service providers must complete the mobile payment service with the transaction security. One way to provide transaction security is to utilize a secure mobile payment application. This research provides a safety feature used for an Android-based mobile payment application. This security feature is making encryption rules dynamically named Dynamic Rule Encryption (DRE. DRE has the ability to protect data by means of encrypting data with dynamic rules, and DRE also has a token function for an authentication. DRE token raised with dynamic time-based rules. Here, the time is used as a reference with the order of the day in the year (day of the year. The processes of the DRE’s encryption, decryption, and the DRE’s functionality as the token are discussed in this paper. Here, the Hamming distance metric is employed for having maximum differences between plaintext and ciphertext.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-10-15

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

  15. A Step-Indexed Kripke Model of Hidden State via Recursive Properties on Recursively Defined Metric Spaces

    DEFF Research Database (Denmark)

    Schwinghammer, Jan; Birkedal, Lars; Støvring, Kristian

    2011-01-01

    ´eraud and Pottier’s type and capability system including both frame and anti-frame rules. The model is a possible worlds model based on the operational semantics and step-indexed heap relations, and the worlds are constructed as a recursively defined predicate on a recursively defined metric space. We also extend...

  16. Towards Video Quality Metrics Based on Colour Fractal Geometry

    Directory of Open Access Journals (Sweden)

    Richard Noël

    2010-01-01

    Full Text Available Vision is a complex process that integrates multiple aspects of an image: spatial frequencies, topology and colour. Unfortunately, so far, all these elements were independently took into consideration for the development of image and video quality metrics, therefore we propose an approach that blends together all of them. Our approach allows for the analysis of the complexity of colour images in the RGB colour space, based on the probabilistic algorithm for calculating the fractal dimension and lacunarity. Given that all the existing fractal approaches are defined only for gray-scale images, we extend them to the colour domain. We show how these two colour fractal features capture the multiple aspects that characterize the degradation of the video signal, based on the hypothesis that the quality degradation perceived by the user is directly proportional to the modification of the fractal complexity. We claim that the two colour fractal measures can objectively assess the quality of the video signal and they can be used as metrics for the user-perceived video quality degradation and we validated them through experimental results obtained for an MPEG-4 video streaming application; finally, the results are compared against the ones given by unanimously-accepted metrics and subjective tests.

  17. Turbulence Hazard Metric Based on Peak Accelerations for Jetliner Passengers

    Science.gov (United States)

    Stewart, Eric C.

    2005-01-01

    Calculations are made of the approximate hazard due to peak normal accelerations of an airplane flying through a simulated vertical wind field associated with a convective frontal system. The calculations are based on a hazard metric developed from a systematic application of a generic math model to 1-cosine discrete gusts of various amplitudes and gust lengths. The math model simulates the three degree-of- freedom longitudinal rigid body motion to vertical gusts and includes (1) fuselage flexibility, (2) the lag in the downwash from the wing to the tail, (3) gradual lift effects, (4) a simplified autopilot, and (5) motion of an unrestrained passenger in the rear cabin. Airplane and passenger response contours are calculated for a matrix of gust amplitudes and gust lengths. The airplane response contours are used to develop an approximate hazard metric of peak normal accelerations as a function of gust amplitude and gust length. The hazard metric is then applied to a two-dimensional simulated vertical wind field of a convective frontal system. The variations of the hazard metric with gust length and airplane heading are demonstrated.

  18. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    OpenAIRE

    Aminifar, Sadegh; bin Marzuki, Arjuna

    2013-01-01

    Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal...

  19. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  20. Grading the Metrics: Performance-Based Funding in the Florida State University System

    Science.gov (United States)

    Cornelius, Luke M.; Cavanaugh, Terence W.

    2016-01-01

    A policy analysis of Florida's 10-factor Performance-Based Funding system for state universities. The focus of the article is on the system of performance metrics developed by the state Board of Governors and their impact on institutions and their missions. The paper also discusses problems and issues with the metrics, their ongoing evolution, and…

  1. Individuality evaluation for paper based artifact-metrics using transmitted light image

    Science.gov (United States)

    Yamakoshi, Manabu; Tanaka, Junichi; Furuie, Makoto; Hirabayashi, Masashi; Matsumoto, Tsutomu

    2008-02-01

    Artifact-metrics is an automated method of authenticating artifacts based on a measurable intrinsic characteristic. Intrinsic characters, such as microscopic random-patterns made during the manufacturing process, are very difficult to copy. A transmitted light image of the distribution can be used for artifact-metrics, since the fiber distribution of paper is random. Little is known about the individuality of the transmitted light image although it is an important requirement for intrinsic characteristic artifact-metrics. Measuring individuality requires that the intrinsic characteristic of each artifact significantly differs, so having sufficient individuality can make an artifact-metric system highly resistant to brute force attack. Here we investigate the influence of paper category, matching size of sample, and image-resolution on the individuality of a transmitted light image of paper through a matching test using those images. More concretely, we evaluate FMR/FNMR curves by calculating similarity scores with matches using correlation coefficients between pairs of scanner input images, and the individuality of paper by way of estimated EER with probabilistic measure through a matching method based on line segments, which can localize the influence of rotation gaps of a sample in the case of large matching size. As a result, we found that the transmitted light image of paper has a sufficient individuality.

  2. Rule-Based and Case-Based Reasoning in Housing Prices

    OpenAIRE

    Gabrielle Gayer; Itzhak Gilboa; Offer Lieberman

    2004-01-01

    People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the case-based model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We ...

  3. Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising.

    Science.gov (United States)

    Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery

    2017-01-01

    The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.

  4. Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising

    Directory of Open Access Journals (Sweden)

    Jaime Guixeres

    2017-10-01

    Full Text Available The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking. Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy and estimate the number of online views (mean error of 0.199. The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.

  5. Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising

    Science.gov (United States)

    Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M.; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery

    2017-01-01

    The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube. PMID:29163251

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

    Directory of Open Access Journals (Sweden)

    BHURTAH-SEEWOOSUNGKUR, I.

    2016-05-01

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

  7. Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2014-08-01

    Full Text Available Emergence is a common phenomenon, and it is also a general and important concept in complex dynamic systems like artificial societies. Usually, artificial societies are used for assisting in resolving several complex social issues (e.g., emergency management, intelligent transportation system with the aid of computer science. The levels of an emergence may have an effect on decisions making, and the occurrence and degree of an emergence are generally perceived by human observers. However, due to the ambiguity and inaccuracy of human observers, to propose a quantitative method to measure emergences in artificial societies is a meaningful and challenging task. This article mainly concentrates upon three kinds of emergences in artificial societies, including emergence of attribution, emergence of behavior, and emergence of structure. Based on information entropy, three metrics have been proposed to measure emergences in a quantitative way. Meanwhile, the correctness of these metrics has been verified through three case studies (the spread of an infectious influenza, a dynamic microblog network, and a flock of birds with several experimental simulations on the Netlogo platform. These experimental results confirm that these metrics increase with the rising degree of emergences. In addition, this article also has discussed the limitations and extended applications of these metrics.

  8. Synchronization of multi-agent systems with metric-topological interactions.

    Science.gov (United States)

    Wang, Lin; Chen, Guanrong

    2016-09-01

    A hybrid multi-agent systems model integrating the advantages of both metric interaction and topological interaction rules, called the metric-topological model, is developed. This model describes planar motions of mobile agents, where each agent can interact with all the agents within a circle of a constant radius, and can furthermore interact with some distant agents to reach a pre-assigned number of neighbors, if needed. Some sufficient conditions imposed only on system parameters and agent initial states are presented, which ensure achieving synchronization of the whole group of agents. It reveals the intrinsic relationships among the interaction range, the speed, the initial heading, and the density of the group. Moreover, robustness against variations of interaction range, density, and speed are investigated by comparing the motion patterns and performances of the hybrid metric-topological interaction model with the conventional metric-only and topological-only interaction models. Practically in all cases, the hybrid metric-topological interaction model has the best performance in the sense of achieving highest frequency of synchronization, fastest convergent rate, and smallest heading difference.

  9. Risk-based rules for crane safety systems

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, Stian [Section for Control Systems, DNV Maritime, 1322 Hovik (Norway)], E-mail: Stian.Ruud@dnv.com; Mikkelsen, Age [Section for Lifting Appliances, DNV Maritime, 1322 Hovik (Norway)], E-mail: Age.Mikkelsen@dnv.com

    2008-09-15

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented.

  10. Risk-based rules for crane safety systems

    International Nuclear Information System (INIS)

    Ruud, Stian; Mikkelsen, Age

    2008-01-01

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented

  11. Derivative-Based Trapezoid Rule for the Riemann-Stieltjes Integral

    Directory of Open Access Journals (Sweden)

    Weijing Zhao

    2014-01-01

    Full Text Available The derivative-based trapezoid rule for the Riemann-Stieltjes integral is presented which uses 2 derivative values at the endpoints. This kind of quadrature rule obtains an increase of two orders of precision over the trapezoid rule for the Riemann-Stieltjes integral and the error term is investigated. At last, the rationality of the generalization of derivative-based trapezoid rule for Riemann-Stieltjes integral is demonstrated.

  12. Rule-based energy management strategies for hybrid vehicles

    NARCIS (Netherlands)

    Hofman, T.; Druten, van R.M.; Serrarens, A.F.A.; Steinbuch, M.

    2007-01-01

    Int. J. of Electric and Hybrid Vehicles (IJEHV), The highest control layer of a (hybrid) vehicular drive train is termed the Energy Management Strategy (EMS). In this paper an overview of different control methods is given and a new rule-based EMS is introduced based on the combination of Rule-Based

  13. Alternatives to accuracy and bias metrics based on percentage errors for radiation belt modeling applications

    Energy Technology Data Exchange (ETDEWEB)

    Morley, Steven Karl [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-07-01

    This report reviews existing literature describing forecast accuracy metrics, concentrating on those based on relative errors and percentage errors. We then review how the most common of these metrics, the mean absolute percentage error (MAPE), has been applied in recent radiation belt modeling literature. Finally, we describe metrics based on the ratios of predicted to observed values (the accuracy ratio) that address the drawbacks inherent in using MAPE. Specifically, we define and recommend the median log accuracy ratio as a measure of bias and the median symmetric accuracy as a measure of accuracy.

  14. Assessment and improvement of radiation oncology trainee contouring ability utilizing consensus-based penalty metrics

    International Nuclear Information System (INIS)

    Hallock, Abhirami; Read, Nancy; D'Souza, David

    2012-01-01

    The objective of this study was to develop and assess the feasibility of utilizing consensus-based penalty metrics for the purpose of critical structure and organ at risk (OAR) contouring quality assurance and improvement. A Delphi study was conducted to obtain consensus on contouring penalty metrics to assess trainee-generated OAR contours. Voxel-based penalty metric equations were used to score regions of discordance between trainee and expert contour sets. The utility of these penalty metric scores for objective feedback on contouring quality was assessed by using cases prepared for weekly radiation oncology radiation oncology trainee treatment planning rounds. In two Delphi rounds, six radiation oncology specialists reached agreement on clinical importance/impact and organ radiosensitivity as the two primary criteria for the creation of the Critical Structure Inter-comparison of Segmentation (CriSIS) penalty functions. Linear/quadratic penalty scoring functions (for over- and under-contouring) with one of four levels of severity (none, low, moderate and high) were assigned for each of 20 OARs in order to generate a CriSIS score when new OAR contours are compared with reference/expert standards. Six cases (central nervous system, head and neck, gastrointestinal, genitourinary, gynaecological and thoracic) then were used to validate 18 OAR metrics through comparison of trainee and expert contour sets using the consensus derived CriSIS functions. For 14 OARs, there was an improvement in CriSIS score post-educational intervention. The use of consensus-based contouring penalty metrics to provide quantitative information for contouring improvement is feasible.

  15. Research on Fault Diagnosis Method Based on Rule Base Neural Network

    Directory of Open Access Journals (Sweden)

    Zheng Ni

    2017-01-01

    Full Text Available The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

  16. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    Directory of Open Access Journals (Sweden)

    Sadegh Aminifar

    2013-01-01

    Full Text Available Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal and vertical rule bases method has a great roll in easing of extracting the optimum control surface by using too lesser rules than traditional fuzzy systems. This research involves with control of a system with high nonlinearity and in difficulty to model it with classical methods. As a case study for testing proposed method in real condition, the designed controller is applied to steaming room with uncertain data and variable parameters. A comparison between PID and traditional fuzzy counterpart and our proposed system shows that our proposed system outperforms PID and traditional fuzzy systems in point of view of number of valve switching and better surface following. The evaluations have done both with model simulation and DSP implementation.

  17. An XML-Based Manipulation and Query Language for Rule-Based Information

    Science.gov (United States)

    Mansour, Essam; Höpfner, Hagen

    Rules are utilized to assist in the monitoring process that is required in activities, such as disease management and customer relationship management. These rules are specified according to the application best practices. Most of research efforts emphasize on the specification and execution of these rules. Few research efforts focus on managing these rules as one object that has a management life-cycle. This paper presents our manipulation and query language that is developed to facilitate the maintenance of this object during its life-cycle and to query the information contained in this object. This language is based on an XML-based model. Furthermore, we evaluate the model and language using a prototype system applied to a clinical case study.

  18. Fuzzy rule-based model for hydropower reservoirs operation

    Energy Technology Data Exchange (ETDEWEB)

    Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2011-02-15

    Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

  19. An updated nuclear criticality slide rule

    International Nuclear Information System (INIS)

    Hopper, C.M.; Broadhead, B.L.

    1998-04-01

    This Volume 2 contains the functional version of the updated nuclear criticality slide rule (more accurately, sliding graphs) that is referenced in An Updated Nuclear Criticality Slide Rule: Technical Basis, NUREG/CR-6504, Vol. 1 (ORNL/TM-13322/V1). This functional slide rule provides a readily usable open-quotes in-handclose quotes method for estimating pertinent nuclear criticality accident information from sliding graphs, thereby permitting (1) the rapid estimation of pertinent criticality accident information without laborious or sophisticated calculations in a nuclear criticality emergency situation, (2) the appraisal of potential fission yields and external personnel radiation exposures for facility safety analyses, and (3) a technical basis for emergency preparedness and training programs at nonreactor nuclear facilities. The slide rule permits the estimation of neutron and gamma dose rates and integrated doses based upon estimated fission yields, distance from the fission source, and time-after criticality accidents for five different critical systems. Another sliding graph permits the estimation of critical solution fission yields based upon fissile material concentration, critical vessel geometry, and solution addition rate. Another graph provides neutron and gamma dose-reduction factors for water, steel, and concrete. Graphs from historic documents are provided as references for estimating critical parameters of various fissile material systems. Conversion factors for various English and metric units are provided for quick reference

  20. Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning

    Science.gov (United States)

    Khosyi'ah, S.; Irfan, M.; Maylawati, D. S.; Mukhlas, O. S.

    2018-01-01

    Along with the development of human civilization in Indonesia, the changes and reform of Islamic inheritance law so as to conform to the conditions and culture cannot be denied. The distribution of inheritance in Indonesia can be done automatically by storing the rule of Islamic inheritance law in the expert system. In this study, we analyze the knowledge of experts in Islamic inheritance in Indonesia and represent it in the form of rules using rule-based Forward Chaining (FC) and Davis-Putman-Logemann-Loveland (DPLL) algorithms. By hybridizing FC and DPLL algorithms, the rules of Islamic inheritance law in Indonesia are clearly defined and measured. The rules were conceptually validated by some experts in Islamic laws and informatics. The results revealed that generally all rules were ready for use in an expert system.

  1. Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

    Science.gov (United States)

    Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

    2010-01-01

    Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

  2. METRIC context unit architecture

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, R.O.

    1988-01-01

    METRIC is an architecture for a simple but powerful Reduced Instruction Set Computer (RISC). Its speed comes from the simultaneous processing of several instruction streams, with instructions from the various streams being dispatched into METRIC's execution pipeline as they become available for execution. The pipeline is thus kept full, with a mix of instructions for several contexts in execution at the same time. True parallel programming is supported within a single execution unit, the METRIC Context Unit. METRIC's architecture provides for expansion through the addition of multiple Context Units and of specialized Functional Units. The architecture thus spans a range of size and performance from a single-chip microcomputer up through large and powerful multiprocessors. This research concentrates on the specification of the METRIC Context Unit at the architectural level. Performance tradeoffs made during METRIC's design are discussed, and projections of METRIC's performance are made based on simulation studies.

  3. Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials

    Science.gov (United States)

    An, Ming-Wen; Mandrekar, Sumithra J.; Branda, Megan E.; Hillman, Shauna L.; Adjei, Alex A.; Pitot, Henry; Goldberg, Richard M.; Sargent, Daniel J.

    2011-01-01

    Purpose The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Experimental Design Individual patient data from three North Central Cancer Treatment Group trials (N0026, n=117; N9741, n=1109; N9841, n=332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response (TriTR: Response vs. Stable vs. Progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12-, 16- and 24-weeks post baseline. Model discrimination was evaluated using the concordance (c) index. Results The overall best response rates for the three trials were 26%, 45%, and 25% respectively. While nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the c-indices for the traditional response metrics ranged from 0.59-0.65; for the continuous metrics from 0.60-0.66 and for the TriTR metrics from 0.64-0.69. The c-indices for TriTR at 12-weeks were comparable to those at 16- and 24-weeks. Conclusions Continuous tumor-measurement-based metrics provided no predictive improvement over traditional response based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future Phase II trials. PMID:21880789

  4. Proposed Performance-Based Metrics for the Future Funding of Graduate Medical Education: Starting the Conversation.

    Science.gov (United States)

    Caverzagie, Kelly J; Lane, Susan W; Sharma, Niraj; Donnelly, John; Jaeger, Jeffrey R; Laird-Fick, Heather; Moriarty, John P; Moyer, Darilyn V; Wallach, Sara L; Wardrop, Richard M; Steinmann, Alwin F

    2017-12-12

    Graduate medical education (GME) in the United States is financed by contributions from both federal and state entities that total over $15 billion annually. Within institutions, these funds are distributed with limited transparency to achieve ill-defined outcomes. To address this, the Institute of Medicine convened a committee on the governance and financing of GME to recommend finance reform that would promote a physician training system that meets society's current and future needs. The resulting report provided several recommendations regarding the oversight and mechanisms of GME funding, including implementation of performance-based GME payments, but did not provide specific details about the content and development of metrics for these payments. To initiate a national conversation about performance-based GME funding, the authors asked: What should GME be held accountable for in exchange for public funding? In answer to this question, the authors propose 17 potential performance-based metrics for GME funding that could inform future funding decisions. Eight of the metrics are described as exemplars to add context and to help readers obtain a deeper understanding of the inherent complexities of performance-based GME funding. The authors also describe considerations and precautions for metric implementation.

  5. Cloud-based Computing and Applications of New Snow Metrics for Societal Benefit

    Science.gov (United States)

    Nolin, A. W.; Sproles, E. A.; Crumley, R. L.; Wilson, A.; Mar, E.; van de Kerk, M.; Prugh, L.

    2017-12-01

    Seasonal and interannual variability in snow cover affects socio-environmental systems including water resources, forest ecology, freshwater and terrestrial habitat, and winter recreation. We have developed two new seasonal snow metrics: snow cover frequency (SCF) and snow disappearance date (SDD). These metrics are calculated at 500-m resolution using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data (MOD10A1). SCF is the number of times snow is observed in a pixel over the user-defined observation period. SDD is the last date of observed snow in a water year. These pixel-level metrics are calculated rapidly and globally in the Google Earth Engine cloud-based environment. SCF and SDD can be interactively visualized in a map-based interface, allowing users to explore spatial and temporal snowcover patterns from 2000-present. These metrics are especially valuable in regions where snow data are sparse or non-existent. We have used these metrics in several ongoing projects. When SCF was linked with a simple hydrologic model in the La Laguna watershed in northern Chile, it successfully predicted summer low flows with a Nash-Sutcliffe value of 0.86. SCF has also been used to help explain changes in Dall sheep populations in Alaska where sheep populations are negatively impacted by late snow cover and low snowline elevation during the spring lambing season. In forest management, SCF and SDD appear to be valuable predictors of post-wildfire vegetation growth. We see a positive relationship between winter SCF and subsequent summer greening for several years post-fire. For western US winter recreation, we are exploring trends in SDD and SCF for regions where snow sports are economically important. In a world with declining snowpacks and increasing uncertainty, these metrics extend across elevations and fill data gaps to provide valuable information for decision-making. SCF and SDD are being produced so that anyone with Internet access and a Google

  6. Connecting clinical and actuarial prediction with rule-based methods.

    Science.gov (United States)

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  7. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł

    2010-01-01

    We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. © 2010 Springer-Verlag.

  8. Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

    Science.gov (United States)

    2011-01-01

    predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity. Conclusions Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time. PMID:22173204

  9. Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining.

    Science.gov (United States)

    Toti, Giulia; Vilalta, Ricardo; Lindner, Peggy; Lefer, Barry; Macias, Charles; Price, Daniel

    2016-11-01

    Traditional studies on effects of outdoor pollution on asthma have been criticized for questionable statistical validity and inefficacy in exploring the effects of multiple air pollutants, alone and in combination. Association rule mining (ARM), a method easily interpretable and suitable for the analysis of the effects of multiple exposures, could be of use, but the traditional interest metrics of support and confidence need to be substituted with metrics that focus on risk variations caused by different exposures. We present an ARM-based methodology that produces rules associated with relevant odds ratios and limits the number of final rules even at very low support levels (0.5%), thanks to post-pruning criteria that limit rule redundancy and control for statistical significance. The methodology has been applied to a case-crossover study to explore the effects of multiple air pollutants on risk of asthma in pediatric subjects. We identified 27 rules with interesting odds ratio among more than 10,000 having the required support. The only rule including only one chemical is exposure to ozone on the previous day of the reported asthma attack (OR=1.14). 26 combinatory rules highlight the limitations of air quality policies based on single pollutant thresholds and suggest that exposure to mixtures of chemicals is more harmful, with odds ratio as high as 1.54 (associated with the combination day0 SO 2 , day0 NO, day0 NO 2 , day1 PM). The proposed method can be used to analyze risk variations caused by single and multiple exposures. The method is reliable and requires fewer assumptions on the data than parametric approaches. Rules including more than one pollutant highlight interactions that deserve further investigation, while helping to limit the search field. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Metrics for Polyphonic Sound Event Detection

    Directory of Open Access Journals (Sweden)

    Annamaria Mesaros

    2016-05-01

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

  11. The dynamics of metric-affine gravity

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  12. Utility of ck metrics in predicting size of board-based software games

    International Nuclear Information System (INIS)

    Sabhat, N.; Azam, F.; Malik, A.A.

    2017-01-01

    Software size is one of the most important inputs of many software cost and effort estimation models. Early estimation of software plays an important role at the time of project inception. An accurate estimate of software size is, therefore, crucial for planning, managing, and controlling software development projects dealing with the development of software games. However, software size is unavailable during early phase of software development. This research determines the utility of CK (Chidamber and Kemerer) metrics, a well-known suite of object-oriented metrics, in estimating the size of software applications using the information from its UML (Unified Modeling Language) class diagram. This work focuses on a small subset dealing with board-based software games. Almost sixty games written using an object-oriented programming language are downloaded from open source repositories, analyzed and used to calibrate a regression-based size estimation model. Forward stepwise MLR (Multiple Linear Regression) is used for model fitting. The model thus obtained is assessed using a variety of accuracy measures such as MMRE (Mean Magnitude of Relative Error), Prediction of x(PRED(x)), MdMRE (Median of Relative Error) and validated using K-fold cross validation. The accuracy of this model is also compared with an existing model tailored for size estimation of board games. Based on a small subset of desktop games developed in various object-oriented languages, we obtained a model using CK metrics and forward stepwise multiple linear regression with reasonable estimation accuracy as indicated by the value of the coefficient of determination (R2 = 0.756).Comparison results indicate that the existing size estimation model outperforms the model derived using CK metrics in terms of accuracy of prediction. (author)

  13. Online Dispatching Rules For Vehicle-Based Internal Transport Systems

    NARCIS (Netherlands)

    T. Le-Anh (Tuan); M.B.M. de Koster (René)

    2004-01-01

    textabstractOn-line vehicles dispatching rules are widely used in many facilities such as warehouses to control vehicles' movements. Single-attribute dispatching rules, which dispatch vehicles based on only one parameter, are used commonly. However, multi-attribute dispatching rules prove to be

  14. Anisotropic interaction rules in circular motions of pigeon flocks: An empirical study based on sparse Bayesian learning

    Science.gov (United States)

    Chen, Duxin; Xu, Bowen; Zhu, Tao; Zhou, Tao; Zhang, Hai-Tao

    2017-08-01

    Coordination shall be deemed to the result of interindividual interaction among natural gregarious animal groups. However, revealing the underlying interaction rules and decision-making strategies governing highly coordinated motion in bird flocks is still a long-standing challenge. Based on analysis of high spatial-temporal resolution GPS data of three pigeon flocks, we extract the hidden interaction principle by using a newly emerging machine learning method, namely the sparse Bayesian learning. It is observed that the interaction probability has an inflection point at pairwise distance of 3-4 m closer than the average maximum interindividual distance, after which it decays strictly with rising pairwise metric distances. Significantly, the density of spatial neighbor distribution is strongly anisotropic, with an evident lack of interactions along individual velocity. Thus, it is found that in small-sized bird flocks, individuals reciprocally cooperate with a variational number of neighbors in metric space and tend to interact with closer time-varying neighbors, rather than interacting with a fixed number of topological ones. Finally, extensive numerical investigation is conducted to verify both the revealed interaction and decision-making principle during circular flights of pigeon flocks.

  15. WellnessRules: A Web 3.0 Case Study in RuleML-Based Prolog-N3 Profile Interoperation

    Science.gov (United States)

    Boley, Harold; Osmun, Taylor Michael; Craig, Benjamin Larry

    An interoperation study, WellnessRules, is described, where rules about wellness opportunities are created by participants in rule languages such as Prolog and N3, and translated within a wellness community using RuleML/XML. The wellness rules are centered around participants, as profiles, encoding knowledge about their activities conditional on the season, the time-of-day, the weather, etc. This distributed knowledge base extends FOAF profiles with a vocabulary and rules about wellness group networking. The communication between participants is organized through Rule Responder, permitting wellness-profile translation and distributed querying across engines. WellnessRules interoperates between rules and queries in the relational (Datalog) paradigm of the pure-Prolog subset of POSL and in the frame (F-logic) paradigm of N3. An evaluation of Rule Responder instantiated for WellnessRules revealed acceptable Web response times.

  16. Personalization of Rule-based Web Services.

    Science.gov (United States)

    Choi, Okkyung; Han, Sang Yong

    2008-04-04

    Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters', service providers' and users' preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work.

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

    Science.gov (United States)

    Good, B. M.; Tennis, J. T.

    2009-01-01

    Introduction: We define a collection of metrics for describing and comparing sets of terms in controlled and uncontrolled indexing languages and then show how these metrics can be used to characterize a set of languages spanning folksonomies, ontologies and thesauri. Method: Metrics for term set characterization and comparison were identified and…

  18. Adapting observationally based metrics of biogeophysical feedbacks from land cover/land use change to climate modeling

    International Nuclear Information System (INIS)

    Chen, Liang; Dirmeyer, Paul A

    2016-01-01

    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)

  19. A metric and topological analysis of determinism in the crude oil spot market

    International Nuclear Information System (INIS)

    Barkoulas, John T.; Chakraborty, Atreya; Ouandlous, Arav

    2012-01-01

    We test whether the spot price of crude oil is determined by stochastic rules or exhibits deterministic endogenous fluctuations. In our analysis, we employ both metric (correlation dimension and Lyapunov exponents) and topological (recurrence plots) diagnostic tools for chaotic dynamics. We find that the underlying system for crude oil spot prices (i) is of high dimensionality (no stabilization of the correlation dimension), (ii) does not exhibit sensitive dependence on initial conditions, and (iii) is not characterized by the recurrence property. Thus, the empirical evidence suggests that stochastic rather than deterministic rules are present in the system dynamics of the crude oil spot market. Recurrent plot analysis indicates that volatility clustering is an adequate, but not complete, explanation of the morphology of oil spot prices. - Highlights: ► We test whether the spot price of crude oil exhibits deterministic chaos. ► We employ both metric and topological diagnostic tools for chaos. ► Stochastic rules appear to govern the temporal evolution of oil prices. ► Volatility clustering explains the morphology of oil prices largely, but not entirely.

  20. Constructing rule-based models using the belief functions framework

    NARCIS (Netherlands)

    Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

    2012-01-01

    Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

  1. A Fuzzy Rule-based Controller For Automotive Vehicle Guidance

    OpenAIRE

    Hessburg, Thomas; Tomizuka, Masayoshi

    1991-01-01

    A fuzzy rule-based controller is applied to lateral guidance of a vehicle for an automated highway system. The fuzzy rules, based on human drivers' experiences, are developed to track the center of a lane in the presence of external disturbances and over a range of vehicle operating conditions.

  2. A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output.

    Science.gov (United States)

    Stevanovic, Stefan; Pervan, Boris

    2018-01-19

    We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator's estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered.

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

    NARCIS (Netherlands)

    Strickert, M.; Schneider, P.; Keilwagen, J.; Villmann, T.; Biehl, M.; Hammer, B.

    2008-01-01

    Supervised attribute relevance detection using cross-comparisons (SARDUX), a recently proposed method for data-driven metric learning, is extended from dimension-weighted Minkowski distances to metrics induced by a data transformation matrix Ω for modeling mutual attribute dependence. Given class

  4. Comparison of SOAP and REST Based Web Services Using Software Evaluation Metrics

    Directory of Open Access Journals (Sweden)

    Tihomirovs Juris

    2016-12-01

    Full Text Available The usage of Web services has recently increased. Therefore, it is important to select right type of Web services at the project design stage. The most common implementations are based on SOAP (Simple Object Access Protocol and REST (Representational State Transfer Protocol styles. Maintainability of REST and SOAP Web services has become an important issue as popularity of Web services is increasing. Choice of the right approach is not an easy decision since it is influenced by development requirements and maintenance considerations. In the present research, we present the comparison of SOAP and REST based Web services using software evaluation metrics. To achieve this aim, a systematic literature review will be made to compare REST and SOAP Web services in terms of the software evaluation metrics.

  5. Application of Metric-based Software Reliability Analysis to Example Software

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Smidts, Carol

    2008-07-01

    The software reliability of TELLERFAST ATM software is analyzed by using two metric-based software reliability analysis methods, a state transition diagram-based method and a test coverage-based method. The procedures for the software reliability analysis by using the two methods and the analysis results are provided in this report. It is found that the two methods have a relation of complementary cooperation, and therefore further researches on combining the two methods to reflect the benefit of the complementary cooperative effect to the software reliability analysis are recommended

  6. Combination Rules for Morse-Based van der Waals Force Fields.

    Science.gov (United States)

    Yang, Li; Sun, Lei; Deng, Wei-Qiao

    2018-02-15

    In traditional force fields (FFs), van der Waals interactions have been usually described by the Lennard-Jones potentials. Conventional combination rules for the parameters of van der Waals (VDW) cross-termed interactions were developed for the Lennard-Jones based FFs. Here, we report that the Morse potentials were a better function to describe VDW interactions calculated by highly precise quantum mechanics methods. A new set of combination rules was developed for Morse-based FFs, in which VDW interactions were described by Morse potentials. The new set of combination rules has been verified by comparing the second virial coefficients of 11 noble gas mixtures. For all of the mixed binaries considered in this work, the combination rules work very well and are superior to all three other existing sets of combination rules reported in the literature. We further used the Morse-based FF by using the combination rules to simulate the adsorption isotherms of CH 4 at 298 K in four covalent-organic frameworks (COFs). The overall agreement is great, which supports the further applications of this new set of combination rules in more realistic simulation systems.

  7. Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

    Science.gov (United States)

    Opitz, Bertram; Hofmann, Juliane

    2015-03-01

    A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Measuring reliability under epistemic uncertainty: Review on non-probabilistic reliability metrics

    Directory of Open Access Journals (Sweden)

    Kang Rui

    2016-06-01

    Full Text Available In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence-theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis-based reliability metrics, possibility-theory-based reliability metrics (posbist reliability and uncertainty-theory-based reliability metrics (belief reliability. It is pointed out that a qualified reliability metric that is able to consider the effect of epistemic uncertainty needs to (1 compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2 satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.

  9. Numerical Calabi-Yau metrics

    International Nuclear Information System (INIS)

    Douglas, Michael R.; Karp, Robert L.; Lukic, Sergio; Reinbacher, Rene

    2008-01-01

    We develop numerical methods for approximating Ricci flat metrics on Calabi-Yau hypersurfaces in projective spaces. Our approach is based on finding balanced metrics and builds on recent theoretical work by Donaldson. We illustrate our methods in detail for a one parameter family of quintics. We also suggest several ways to extend our results

  10. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    Science.gov (United States)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  11. An investigation of care-based vs. rule-based morality in frontotemporal dementia, Alzheimer's disease, and healthy controls.

    Science.gov (United States)

    Carr, Andrew R; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S; Mather, Michelle; Jimenez, Elvira E; Thompson, Paul; Mendez, Mario F

    2015-11-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer's disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. Published by Elsevier Ltd.

  12. An Embedded Rule-Based Diagnostic Expert System in Ada

    Science.gov (United States)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  13. Designing Fuzzy Rule Based Expert System for Cyber Security

    OpenAIRE

    Goztepe, Kerim

    2016-01-01

    The state of cyber security has begun to attract more attention and interest outside the community of computer security experts. Cyber security is not a single problem, but rather a group of highly different problems involving different sets of threats. Fuzzy Rule based system for cyber security is a system consists of a rule depository and a mechanism for accessing and running the rules. The depository is usually constructed with a collection of related rule sets. The aim of this study is to...

  14. Questionable validity of the catheter-associated urinary tract infection metric used for value-based purchasing.

    Science.gov (United States)

    Calderon, Lindsay E; Kavanagh, Kevin T; Rice, Mara K

    2015-10-01

    Catheter-associated urinary tract infections (CAUTIs) occur in 290,000 US hospital patients annually, with an estimated cost of $290 million. Two different measurement systems are being used to track the US health care system's performance in lowering the rate of CAUTIs. Since 2010, the Agency for Healthcare Research and Quality (AHRQ) metric has shown a 28.2% decrease in CAUTI, whereas the Centers for Disease Control and Prevention metric has shown a 3%-6% increase in CAUTI since 2009. Differences in data acquisition and the definition of the denominator may explain this discrepancy. The AHRQ metric analyzes chart-audited data and reflects both catheter use and care. The Centers for Disease Control and Prevention metric analyzes self-reported data and primarily reflects catheter care. Because analysis of the AHRQ metric showed a progressive change in performance over time and the scientific literature supports the importance of catheter use in the prevention of CAUTI, it is suggested that risk-adjusted catheter-use data be incorporated into metrics that are used for determining facility performance and for value-based purchasing initiatives. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

  15. Knowledge base rule partitioning design for CLIPS

    Science.gov (United States)

    Mainardi, Joseph D.; Szatkowski, G. P.

    1990-01-01

    This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

  16. Resilience-based performance metrics for water resources management under uncertainty

    Science.gov (United States)

    Roach, Tom; Kapelan, Zoran; Ledbetter, Ralph

    2018-06-01

    This paper aims to develop new, resilience type metrics for long-term water resources management under uncertain climate change and population growth. Resilience is defined here as the ability of a water resources management system to 'bounce back', i.e. absorb and then recover from a water deficit event, restoring the normal system operation. Ten alternative metrics are proposed and analysed addressing a range of different resilience aspects including duration, magnitude, frequency and volume of related water deficit events. The metrics were analysed on a real-world case study of the Bristol Water supply system in the UK and compared with current practice. The analyses included an examination of metrics' sensitivity and correlation, as well as a detailed examination into the behaviour of metrics during water deficit periods. The results obtained suggest that multiple metrics which cover different aspects of resilience should be used simultaneously when assessing the resilience of a water resources management system, leading to a more complete understanding of resilience compared with current practice approaches. It was also observed that calculating the total duration of a water deficit period provided a clearer and more consistent indication of system performance compared to splitting the deficit periods into the time to reach and time to recover from the worst deficit events.

  17. Evidence-based Metrics Toolkit for Measuring Safety and Efficiency in Human-Automation Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — APRIL 2016 NOTE: Principal Investigator moved to Rice University in mid-2015. Project continues at Rice with the same title (Evidence-based Metrics Toolkit for...

  18. Resilience Metrics for the Electric Power System: A Performance-Based Approach.

    Energy Technology Data Exchange (ETDEWEB)

    Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Castillo, Andrea R [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Silva-Monroy, Cesar Augusto [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    Grid resilience is a concept related to a power system's ability to continue operating and delivering power even in the event that low probability, high-consequence disruptions such as hurricanes, earthquakes, and cyber-attacks occur. Grid resilience objectives focus on managing and, ideally, minimizing potential consequences that occur as a result of these disruptions. Currently, no formal grid resilience definitions, metrics, or analysis methods have been universally accepted. This document describes an effort to develop and describe grid resilience metrics and analysis methods. The metrics and methods described herein extend upon the Resilience Analysis Process (RAP) developed by Watson et al. for the 2015 Quadrennial Energy Review. The extension allows for both outputs from system models and for historical data to serve as the basis for creating grid resilience metrics and informing grid resilience planning and response decision-making. This document describes the grid resilience metrics and analysis methods. Demonstration of the metrics and methods is shown through a set of illustrative use cases.

  19. SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

    International Nuclear Information System (INIS)

    Zhao, T; Ruan, D

    2015-01-01

    Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject to random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be

  20. COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

    Full Text Available Security is one of the major challenges in open network. There are so many types of attacks which follow fixed patterns or frequently change their patterns. It is difficult to find the malicious attack which does not have any fixed patterns. The Distributed Denial of Service (DDoS attacks like Botnets are used to slow down the system performance. To address such problems Collaborative Network Security Management System (CNSMS is proposed along with the association mining rule. CNSMS system is consists of collaborative Unified Threat Management (UTM, cloud based security centre and traffic prober. The traffic prober captures the internet traffic and given to the collaborative UTM. Traffic is analysed by the Collaborative UTM, to determine whether it contains any malicious attack or not. If any security event occurs, it will reports to the cloud based security centre. The security centre generates security rules based on association mining rule and distributes to the network. The cloud based security centre is used to store the huge amount of tragic, their logs and the security rule generated. The feedback is evaluated and the invalid rules are eliminated to improve the system efficiency.

  1. Rule-Based Storytelling Text-to-Speech (TTS Synthesis

    Directory of Open Access Journals (Sweden)

    Ramli Izzad

    2016-01-01

    Full Text Available In recent years, various real life applications such as talking books, gadgets and humanoid robots have drawn the attention to pursue research in the area of expressive speech synthesis. Speech synthesis is widely used in various applications. However, there is a growing need for an expressive speech synthesis especially for communication and robotic. In this paper, global and local rule are developed to convert neutral to storytelling style speech for the Malay language. In order to generate rules, modification of prosodic parameters such as pitch, intensity, duration, tempo and pauses are considered. Modification of prosodic parameters is examined by performing prosodic analysis on a story collected from an experienced female and male storyteller. The global and local rule is applied in sentence level and synthesized using HNM. Subjective tests are conducted to evaluate the synthesized storytelling speech quality of both rules based on naturalness, intelligibility, and similarity to the original storytelling speech. The results showed that global rule give a better result than local rule

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

    Science.gov (United States)

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

    2010-03-01

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

  3. Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

    Science.gov (United States)

    Nakamura, Katsuhiko; Hoshina, Akemi

    This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

  4. Comparison of Highly Resolved Model-Based Exposure Metrics for Traffic-Related Air Pollutants to Support Environmental Health Studies

    Directory of Open Access Journals (Sweden)

    Shih Ying Chang

    2015-12-01

    Full Text Available Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NOx, PM2.5, and elemental carbon (EC during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK, ambient on-road concentration from the Research LINE source dispersion model (R-LINE, a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93% and individual level (average bias between −10% to 95%. For pollutants with significant contribution from on-road emission (EC and NOx, the on-road based indoor metric performs the best at the population level (error less than 52%. At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%. For PM2.5, due to the relatively low contribution from on-road emission (7%, STOK-based indoor metric performs the best at both population (error below 40% and individual level (error below 25%. The results of the study will help future epidemiology studies to select appropriate exposure metric and reduce potential bias in exposure characterization.

  5. Guidelines for visualizing and annotating rule-based models†

    Science.gov (United States)

    Chylek, Lily A.; Hu, Bin; Blinov, Michael L.; Emonet, Thierry; Faeder, James R.; Goldstein, Byron; Gutenkunst, Ryan N.; Haugh, Jason M.; Lipniacki, Tomasz; Posner, Richard G.; Yang, Jin; Hlavacek, William S.

    2011-01-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models. PMID:21647530

  6. Guidelines for visualizing and annotating rule-based models.

    Science.gov (United States)

    Chylek, Lily A; Hu, Bin; Blinov, Michael L; Emonet, Thierry; Faeder, James R; Goldstein, Byron; Gutenkunst, Ryan N; Haugh, Jason M; Lipniacki, Tomasz; Posner, Richard G; Yang, Jin; Hlavacek, William S

    2011-10-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

  7. An Investigation of Care-Based vs. Rule-Based Morality in Frontotemporal Dementia, Alzheimer’s Disease, and Healthy Controls

    Science.gov (United States)

    Carr, Andrew R.; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S.; Mather, Michelle; Jimenez, Elvira E.; Thompson, Paul; Mendez, Mario F.

    2015-01-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer’s disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. PMID:26432341

  8. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan; Lau, Cheryl; Mü ller, Pascal; Wonka, Peter; Pauly, Mark

    2017-01-01

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  9. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan

    2017-05-24

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  10. Rule based deterioration identification and management system

    International Nuclear Information System (INIS)

    Kataoka, S.; Pavinich, W.; Lapides, M.

    1993-01-01

    Under the sponsorship of IHI and EPRI, a rule-based screening system has been developed that can be used by utility engineers to determine which deterioration mechanisms are acting on specific LWR components, and to evaluate the efficacy of an age-related deterioration management program. The screening system was developed using the rule-based shell, NEXPERT, which provides traceability to the data sources used in the logic development. The system addresses all the deterioration mechanisms of specific metals encountered in either BWRs or PWRs. Deterioration mechanisms are listed with reasons why they may occur during the design life of LWRs, considering the plant environment, manufacturing process, service history, material chemical composition, etc. of components in a specific location of a LWR. To eliminate the evaluation of inactive deterioration quickly, a tier structure is applied to the rules. The reasons why deterioration will occur are extracted automatically by backward chaining. To reduce the amount of user input, plant environmental data are stored in files as default environmental data. (author)

  11. Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode.

    Science.gov (United States)

    Scheib, Jean P P; Stoll, Sarah; Thürmer, J Lukas; Randerath, Jennifer

    2018-01-01

    The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous

  12. Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

    Science.gov (United States)

    Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

    2018-03-28

    To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

  13. On Information Metrics for Spatial Coding.

    Science.gov (United States)

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

    2018-04-01

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

  14. Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

    Science.gov (United States)

    Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

    2017-07-28

    New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

  15. Diversity of Rule-based Approaches: Classic Systems and Recent Applications

    Directory of Open Access Journals (Sweden)

    Grzegorz J. Nalepa

    2016-11-01

    Full Text Available Rules are a common symbolic model of knowledge. Rule-based systems share roots in cognitive science and artificial intelligence. In the former, they are mostly used in cognitive architectures; in the latter, they are developed in several domains including knowledge engineering and machine learning. This paper aims to give an overview of these issues with the focus on the current research perspective of artificial intelligence. Moreover, in this setting we discuss our results in the design of rule-based systems and their applications in context-aware and business intelligence systems.

  16. A rule-based automatic sleep staging method.

    Science.gov (United States)

    Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

    2012-03-30

    In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

  17. Developing a Security Metrics Scorecard for Healthcare Organizations.

    Science.gov (United States)

    Elrefaey, Heba; Borycki, Elizabeth; Kushniruk, Andrea

    2015-01-01

    In healthcare, information security is a key aspect of protecting a patient's privacy and ensuring systems availability to support patient care. Security managers need to measure the performance of security systems and this can be achieved by using evidence-based metrics. In this paper, we describe the development of an evidence-based security metrics scorecard specific to healthcare organizations. Study participants were asked to comment on the usability and usefulness of a prototype of a security metrics scorecard that was developed based on current research in the area of general security metrics. Study findings revealed that scorecards need to be customized for the healthcare setting in order for the security information to be useful and usable in healthcare organizations. The study findings resulted in the development of a security metrics scorecard that matches the healthcare security experts' information requirements.

  18. A General Attribute and Rule Based Role-Based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

  19. Quantification of Dynamic Model Validation Metrics Using Uncertainty Propagation from Requirements

    Science.gov (United States)

    Brown, Andrew M.; Peck, Jeffrey A.; Stewart, Eric C.

    2018-01-01

    The Space Launch System, NASA's new large launch vehicle for long range space exploration, is presently in the final design and construction phases, with the first launch scheduled for 2019. A dynamic model of the system has been created and is critical for calculation of interface loads and natural frequencies and mode shapes for guidance, navigation, and control (GNC). Because of the program and schedule constraints, a single modal test of the SLS will be performed while bolted down to the Mobile Launch Pad just before the first launch. A Monte Carlo and optimization scheme will be performed to create thousands of possible models based on given dispersions in model properties and to determine which model best fits the natural frequencies and mode shapes from modal test. However, the question still remains as to whether this model is acceptable for the loads and GNC requirements. An uncertainty propagation and quantification (UP and UQ) technique to develop a quantitative set of validation metrics that is based on the flight requirements has therefore been developed and is discussed in this paper. There has been considerable research on UQ and UP and validation in the literature, but very little on propagating the uncertainties from requirements, so most validation metrics are "rules-of-thumb;" this research seeks to come up with more reason-based metrics. One of the main assumptions used to achieve this task is that the uncertainty in the modeling of the fixed boundary condition is accurate, so therefore that same uncertainty can be used in propagating the fixed-test configuration to the free-free actual configuration. The second main technique applied here is the usage of the limit-state formulation to quantify the final probabilistic parameters and to compare them with the requirements. These techniques are explored with a simple lumped spring-mass system and a simplified SLS model. When completed, it is anticipated that this requirements-based validation

  20. Knowledge rule base for the beam optics program TRACE 3-D

    International Nuclear Information System (INIS)

    Gillespie, G.H.; Van Staagen, P.K.; Hill, B.W.

    1993-01-01

    An expert system type of knowledge rule base has been developed for the input parameters used by the particle beam transport program TRACE 3-D. The goal has been to provide the program's user with adequate on-screen information to allow him to initially set up a problem with minimal open-quotes off-lineclose quotes calculations. The focus of this work has been in developing rules for the parameters which define the beam line transport elements. Ten global parameters, the particle mass and charge, beam energy, etc., are used to provide open-quotes expertclose quotes estimates of lower and upper limits for each of the transport element parameters. For example, the limits for the field strength of the quadrupole element are based on a water-cooled, iron-core electromagnet with dimensions derived from practical engineering constraints, and the upper limit for the effective length is scaled with the particle momenta so that initially parallel trajectories do not cross the axis inside the magnet. Limits for the quadrupole doublet and triplet parameters incorporate these rules and additional rules based on stable FODO lattices and bidirectional focusing requirements. The structure of the rule base is outlined and examples for the quadrupole singlet, doublet and triplet are described. The rule base has been implemented within the Shell for Particle Accelerator Related Codes (SPARC) graphical user interface (GUI)

  1. A Belief Rule-Based Expert System to Diagnose Influenza

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin; Akter, Shamima

    2014-01-01

    , development and application of an expert system to diagnose influenza under uncertainty. The recently developed generic belief rule-based inference methodology by using the evidential reasoning (RIMER) approach is employed to develop this expert system, termed as Belief Rule Based Expert System (BRBES......). The RIMER approach can handle different types of uncertainties, both in knowledge representation, and in inference procedures. The knowledge-base of this system was constructed by using records of the real patient data along with in consultation with the Influenza specialists of Bangladesh. Practical case...

  2. Metric-based approach and tool for modeling the I and C system using Markov chains

    International Nuclear Information System (INIS)

    Butenko, Valentyna; Kharchenko, Vyacheslav; Odarushchenko, Elena; Butenko, Dmitriy

    2015-01-01

    Markov's chains (MC) are well-know and widely applied in dependability and performability analysis of safety-critical systems, because of the flexible representation of system components dependencies and synchronization. There are few radblocks for greater application of the MC: accounting the additional system components increases the model state-space and complicates analysis; the non-numerically sophisticated user may find it difficult to decide between the variety of numerical methods to determine the most suitable and accurate for their application. Thus obtaining the high accurate and trusted modeling results becomes a nontrivial task. In this paper, we present the metric-based approach for selection of the applicable solution approach, based on the analysis of MCs stiffness, decomposability, sparsity and fragmentedness. Using this selection procedure the modeler can provide the verification of earlier obtained results. The presented approach was implemented in utility MSMC, which supports the MC construction, metric-based analysis, recommendations shaping and model solution. The model can be exported to the wall-known off-the-shelf mathematical packages for verification. The paper presents the case study of the industrial NPP I and C system, manufactured by RPC Radiy. The paper shows an application of metric-based approach and MSMC fool for dependability and safety analysis of RTS, and procedure of results verification. (author)

  3. Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with Porgy

    OpenAIRE

    Andrei , Oana; Fernández , Maribel; Kirchner , Hélène; Pinaud , Bruno

    2016-01-01

    This paper presents Porgy – an interactive visual environment for rule-based modelling of biochemical systems. We model molecules and molecule interactions as port graphs and port graph rewrite rules, respectively. We use rewriting strategies to control which rules to apply, and where and when to apply them. Our main contributions to rule-based modelling of biochemical systems lie in the strategy language and the associated visual and interactive features offered by Porgy. These features faci...

  4. High resolution metric imaging payload

    Science.gov (United States)

    Delclaud, Y.

    2017-11-01

    Alcatel Space Industries has become Europe's leader in the field of high and very high resolution optical payloads, in the frame work of earth observation system able to provide military government with metric images from space. This leadership allowed ALCATEL to propose for the export market, within a French collaboration frame, a complete space based system for metric observation.

  5. Idioms-based Business Rule Extraction

    NARCIS (Netherlands)

    R Smit (Rob)

    2011-01-01

    htmlabstractThis thesis studies the extraction of embedded business rules, using the idioms of the used framework to identify them. Embedded business rules exist as source code in the software system and knowledge about them may get lost. Extraction of those business rules could make them accessible

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Local behavioral rules sustain the cell allocation pattern in the combs of honey bee colonies (Apis mellifera).

    Science.gov (United States)

    Montovan, Kathryn J; Karst, Nathaniel; Jones, Laura E; Seeley, Thomas D

    2013-11-07

    In the beeswax combs of honey bees, the cells of brood, pollen, and honey have a consistent spatial pattern that is sustained throughout the life of a colony. This spatial pattern is believed to emerge from simple behavioral rules that specify how the queen moves, where foragers deposit honey/pollen and how honey/pollen is consumed from cells. Prior work has shown that a set of such rules can explain the formation of the allocation pattern starting from an empty comb. We show that these rules cannot maintain the pattern once the brood start to vacate their cells, and we propose new, biologically realistic rules that better sustain the observed allocation pattern. We analyze the three resulting models by performing hundreds of simulation runs over many gestational periods and a wide range of parameter values. We develop new metrics for pattern assessment and employ them in analyzing pattern retention over each simulation run. Applied to our simulation results, these metrics show alteration of an accepted model for honey/pollen consumption based on local information can stabilize the cell allocation pattern over time. We also show that adding global information, by biasing the queen's movements towards the center of the comb, expands the parameter regime over which pattern retention occurs. © 2013 Published by Elsevier Ltd. All rights reserved.

  8. Factor structure of the Tomimatsu-Sato metrics

    International Nuclear Information System (INIS)

    Perjes, Z.

    1989-02-01

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

  9. Sharp metric obstructions for quasi-Einstein metrics

    Science.gov (United States)

    Case, Jeffrey S.

    2013-02-01

    Using the tractor calculus to study smooth metric measure spaces, we adapt results of Gover and Nurowski to give sharp metric obstructions to the existence of quasi-Einstein metrics on suitably generic manifolds. We do this by introducing an analogue of the Weyl tractor W to the setting of smooth metric measure spaces. The obstructions we obtain can be realized as tensorial invariants which are polynomial in the Riemann curvature tensor and its divergence. By taking suitable limits of their tensorial forms, we then find obstructions to the existence of static potentials, generalizing to higher dimensions a result of Bartnik and Tod, and to the existence of potentials for gradient Ricci solitons.

  10. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes.

    Science.gov (United States)

    Liu, Hengli; Luo, Jun; Wu, Peng; Xie, Shaorong; Li, Hengyu

    2015-01-01

    A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  11. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

    Directory of Open Access Journals (Sweden)

    Hengli Liu

    2015-01-01

    Full Text Available A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  12. Changing from a Rules-based to a Principles-based Accounting Logic: A Review

    Directory of Open Access Journals (Sweden)

    Marta Silva Guerreiro

    2014-06-01

    Full Text Available We explore influences on unlisted companies when Portugal moved from a code law, rules-based accounting system, to a principles-based accounting system of adapted International Financial Reporting Standards (IFRS. Institutionalisation of the new principles-based system was generally facilitated by a socio-economic and political context that increasingly supported IFRS logic. This helped central actors gain political opportunity, mobilise important allies, and accommodate major protagonists. The preparedness of unlisted companies to adopt the new IFRS-based accounting system voluntarily was explained by their desire to maintain social legitimacy. However, it was affected negatively by the embeddedness of rule-based practices in the ‘old’ prevailing institutional logic.

  13. The International Safeguards Technology Base: How is the Patient Doing? An Exploration of Effective Metrics

    International Nuclear Information System (INIS)

    Schanfein, Mark J.; Gouveia, Fernando S.

    2010-01-01

    The term 'Technology Base' is commonly used but what does it mean? Is there a common understanding of the components that comprise a technology base? Does a formal process exist to assess the health of a given technology base? These are important questions the relevance of which is even more pressing given the USDOE/NNSA initiatives to strengthen the safeguards technology base through investments in research and development and human capital development. Accordingly, the authors will establish a high-level framework to define and understand what comprises a technology base. Potential goal-driven metrics to assess the health of a technology base will also be explored, such as linear demographics and resource availability, in the hope that they can be used to better understand and improve the health of the U.S. safeguards technology base. Finally, through the identification of such metrics, the authors will offer suggestions and highlight choices for addressing potential shortfalls.

  14. Opinion evolution based on cellular automata rules in small world networks

    Science.gov (United States)

    Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

    2010-03-01

    In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

  15. Software architecture analysis tool : software architecture metrics collection

    NARCIS (Netherlands)

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

    2002-01-01

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

  16. Hierarchical graphs for rule-based modeling of biochemical systems

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

    Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

  17. Entropies of the automata networks with additive rule

    Institute of Scientific and Technical Information of China (English)

    Guo-qingGU; GeCHEN; 等

    1996-01-01

    The matrix presentation for automata networks with additive rule are described.A set of entropy theorems of additive automata network are proved and an analytic formula of its entropy is built.For example,we proved that the topological entropy is identically equal to metric entropy for an additive antomata network.

  18. A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

    Science.gov (United States)

    Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

    2017-05-01

    Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

  19. Evolving rule-based systems in two medical domains using genetic programming.

    Science.gov (United States)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

    2004-11-01

    To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

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

    Science.gov (United States)

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

    2017-06-01

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

  1. The International Safeguards Technology Base: How is the Patient Doing? An Exploration of Effective Metrics

    Energy Technology Data Exchange (ETDEWEB)

    Schanfein, Mark J; Gouveia, Fernando S

    2010-07-01

    The term “Technology Base” is commonly used but what does it mean? Is there a common understanding of the components that comprise a technology base? Does a formal process exist to assess the health of a given technology base? These are important questions the relevance of which is even more pressing given the USDOE/NNSA initiatives to strengthen the safeguards technology base through investments in research & development and human capital development. Accordingly, the authors will establish a high-level framework to define and understand what comprises a technology base. Potential goal-driven metrics to assess the health of a technology base will also be explored, such as linear demographics and resource availability, in the hope that they can be used to better understand and improve the health of the U.S. safeguards technology base. Finally, through the identification of such metrics, the authors will offer suggestions and highlight choices for addressing potential shortfalls.

  2. Measurable Control System Security through Ideal Driven Technical Metrics

    Energy Technology Data Exchange (ETDEWEB)

    Miles McQueen; Wayne Boyer; Sean McBride; Marie Farrar; Zachary Tudor

    2008-01-01

    The Department of Homeland Security National Cyber Security Division supported development of a small set of security ideals as a framework to establish measurable control systems security. Based on these ideals, a draft set of proposed technical metrics was developed to allow control systems owner-operators to track improvements or degradations in their individual control systems security posture. The technical metrics development effort included review and evaluation of over thirty metrics-related documents. On the bases of complexity, ambiguity, or misleading and distorting effects the metrics identified during the reviews were determined to be weaker than necessary to aid defense against the myriad threats posed by cyber-terrorism to human safety, as well as to economic prosperity. Using the results of our metrics review and the set of security ideals as a starting point for metrics development, we identified thirteen potential technical metrics - with at least one metric supporting each ideal. Two case study applications of the ideals and thirteen metrics to control systems were then performed to establish potential difficulties in applying both the ideals and the metrics. The case studies resulted in no changes to the ideals, and only a few deletions and refinements to the thirteen potential metrics. This led to a final proposed set of ten core technical metrics. To further validate the security ideals, the modifications made to the original thirteen potential metrics, and the final proposed set of ten core metrics, seven separate control systems security assessments performed over the past three years were reviewed for findings and recommended mitigations. These findings and mitigations were then mapped to the security ideals and metrics to assess gaps in their coverage. The mappings indicated that there are no gaps in the security ideals and that the ten core technical metrics provide significant coverage of standard security issues with 87% coverage. Based

  3. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  4. Methodological approaches based on business rules

    OpenAIRE

    Anca Ioana ANDREESCU; Adina UTA

    2008-01-01

    Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize...

  5. $\\eta$-metric structures

    OpenAIRE

    Gaba, Yaé Ulrich

    2017-01-01

    In this paper, we discuss recent results about generalized metric spaces and fixed point theory. We introduce the notion of $\\eta$-cone metric spaces, give some topological properties and prove some fixed point theorems for contractive type maps on these spaces. In particular we show that theses $\\eta$-cone metric spaces are natural generalizations of both cone metric spaces and metric type spaces.

  6. Performance based regulation - The maintenance rule

    Energy Technology Data Exchange (ETDEWEB)

    Correia, Richard P. [NRR/DOTS/TQMP, U.S. Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation, M/S OWFN 10A19, Washington, D.C. 20555 (United States)

    1997-07-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  7. Performance based regulation - The maintenance rule

    International Nuclear Information System (INIS)

    Correia, Richard P.

    1997-01-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  8. Enhancing Authentication Models Characteristic Metrics via ...

    African Journals Online (AJOL)

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

  9. New exposure-based metric approach for evaluating O3 risk to North American aspen forests

    International Nuclear Information System (INIS)

    Percy, K.E.; Nosal, M.; Heilman, W.; Dann, T.; Sober, J.; Legge, A.H.; Karnosky, D.F.

    2007-01-01

    The United States and Canada currently use exposure-based metrics to protect vegetation from O 3 . Using 5 years (1999-2003) of co-measured O 3 , meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient air quality context. The models comprised growing season fourth-highest daily maximum 8-h average O 3 concentration, growing degree days, and wind speed. They had high statistical significance, high goodness of fit, include 95% confidence intervals for tree growth change, and are simple to use. Averaged across a wide range of clonal sensitivity, historical 2001-2003 growth change over most of the 26 M ha P. tremuloides distribution was estimated to have ranged from no impact (0%) to strong negative impacts (-31%). With four aspen clones responding negatively (one responded positively) to O 3 , the growing season fourth-highest daily maximum 8-h average O 3 concentration performed much better than growing season SUM06, AOT40 or maximum 1 h average O 3 concentration metrics as a single indicator of aspen stem cross-sectional area growth. - A new exposure-based metric approach to predict O 3 risk to North American aspen forests has been developed

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

    Science.gov (United States)

    Fenner, Martin

    2013-10-01

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

  11. A self-learning rule base for command following in dynamical systems

    Science.gov (United States)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  12. Fuzzy Sets-based Control Rules for Terminating Algorithms

    Directory of Open Access Journals (Sweden)

    Jose L. VERDEGAY

    2002-01-01

    Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.

  13. Attenuation-based size metric for estimating organ dose to patients undergoing tube current modulated CT exams

    Energy Technology Data Exchange (ETDEWEB)

    Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Lu, Peiyun; Kim, Hyun J.; Cagnon, Chris H.; McNitt-Gray, Michael F. [Departments of Biomedical Physics and Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024 (United States); DeMarco, John J. [Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California 90095 (United States)

    2015-02-15

    Purpose: Task Group 204 introduced effective diameter (ED) as the patient size metric used to correlate size-specific-dose-estimates. However, this size metric fails to account for patient attenuation properties and has been suggested to be replaced by an attenuation-based size metric, water equivalent diameter (D{sub W}). The purpose of this study is to investigate different size metrics, effective diameter, and water equivalent diameter, in combination with regional descriptions of scanner output to establish the most appropriate size metric to be used as a predictor for organ dose in tube current modulated CT exams. Methods: 101 thoracic and 82 abdomen/pelvis scans from clinically indicated CT exams were collected retrospectively from a multidetector row CT (Sensation 64, Siemens Healthcare) with Institutional Review Board approval to generate voxelized patient models. Fully irradiated organs (lung and breasts in thoracic scans and liver, kidneys, and spleen in abdominal scans) were segmented and used as tally regions in Monte Carlo simulations for reporting organ dose. Along with image data, raw projection data were collected to obtain tube current information for simulating tube current modulation scans using Monte Carlo methods. Additionally, previously described patient size metrics [ED, D{sub W}, and approximated water equivalent diameter (D{sub Wa})] were calculated for each patient and reported in three different ways: a single value averaged over the entire scan, a single value averaged over the region of interest, and a single value from a location in the middle of the scan volume. Organ doses were normalized by an appropriate mAs weighted CTDI{sub vol} to reflect regional variation of tube current. Linear regression analysis was used to evaluate the correlations between normalized organ doses and each size metric. Results: For the abdominal organs, the correlations between normalized organ dose and size metric were overall slightly higher for all three

  14. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  15. Significant Pairwise Co-occurrence Patterns Are Not the Rule in the Majority of Biotic Communities

    Directory of Open Access Journals (Sweden)

    Spyros Sfenthourakis

    2012-04-01

    Full Text Available Our aim was to investigate species co-occurrence patterns in a large number of published biotic communities, in order to document to what extent species associations can be found in presence-absence matrices. We also aim to compare and evaluate two metrics that focus on species pairs (the ‘natural’ and the ‘checkerboard’ metric using also artificial matrices. We applied the two metrics to many data sets from a huge variety of insular systems around the world. Both metrics reliably recover deviating species pairs and provide similar, albeit not identical, results. Nevertheless, only a few matrices exhibit significant deviations from random patterns, mostly vertebrates and higher plants. The benchmark cases cited in literature in favor of such assembly rules are indeed included in these exceptional cases. In conclusion, competitive or cooperative species interactions shaping communities cannot be inferred from patterns exhibited by presence-absence matrices. When such an analysis is attempted though, both the ‘natural’ and the ‘checkerboard’ metric should be set in a proper framework in order to provide useful insights regarding species associations. A large part of the discussion on species co-occurrence had originally been based on a few exceptional data sets that are not indicative of general patterns.

  16. A Fuzzy Rule-Based Expert System for Evaluating Intellectual Capital

    Directory of Open Access Journals (Sweden)

    Mohammad Hossein Fazel Zarandi

    2012-01-01

    Full Text Available A fuzzy rule-based expert system is developed for evaluating intellectual capital. A fuzzy linguistic approach assists managers to understand and evaluate the level of each intellectual capital item. The proposed fuzzy rule-based expert system applies fuzzy linguistic variables to express the level of qualitative evaluation and criteria of experts. Feasibility of the proposed model is demonstrated by the result of intellectual capital performance evaluation for a sample company.

  17. Test of the FLRW Metric and Curvature with Strong Lens Time Delays

    International Nuclear Information System (INIS)

    Liao, Kai; Li, Zhengxiang; Wang, Guo-Jian; Fan, Xi-Long

    2017-01-01

    We present a new model-independent strategy for testing the Friedmann–Lemaître–Robertson–Walker (FLRW) metric and constraining cosmic curvature, based on future time-delay measurements of strongly lensed quasar-elliptical galaxy systems from the Large Synoptic Survey Telescope and supernova observations from the Dark Energy Survey. The test only relies on geometric optics. It is independent of the energy contents of the universe and the validity of the Einstein equation on cosmological scales. The study comprises two levels: testing the FLRW metric through the distance sum rule (DSR) and determining/constraining cosmic curvature. We propose an effective and efficient (redshift) evolution model for performing the former test, which allows us to concretely specify the violation criterion for the FLRW DSR. If the FLRW metric is consistent with the observations, then on the second level the cosmic curvature parameter will be constrained to ∼0.057 or ∼0.041 (1 σ ), depending on the availability of high-redshift supernovae, which is much more stringent than current model-independent techniques. We also show that the bias in the time-delay method might be well controlled, leading to robust results. The proposed method is a new independent tool for both testing the fundamental assumptions of homogeneity and isotropy in cosmology and for determining cosmic curvature. It is complementary to cosmic microwave background plus baryon acoustic oscillation analyses, which normally assume a cosmological model with dark energy domination in the late-time universe.

  18. Test of the FLRW Metric and Curvature with Strong Lens Time Delays

    Energy Technology Data Exchange (ETDEWEB)

    Liao, Kai [School of Science, Wuhan University of Technology, Wuhan 430070 (China); Li, Zhengxiang; Wang, Guo-Jian [Department of Astronomy, Beijing Normal University, Beijing 100875 (China); Fan, Xi-Long, E-mail: liaokai@whut.edu.cn, E-mail: xilong.fan@glasgow.ac.uk [Department of Physics and Mechanical and Electrical Engineering, Hubei University of Education, Wuhan 430205 (China)

    2017-04-20

    We present a new model-independent strategy for testing the Friedmann–Lemaître–Robertson–Walker (FLRW) metric and constraining cosmic curvature, based on future time-delay measurements of strongly lensed quasar-elliptical galaxy systems from the Large Synoptic Survey Telescope and supernova observations from the Dark Energy Survey. The test only relies on geometric optics. It is independent of the energy contents of the universe and the validity of the Einstein equation on cosmological scales. The study comprises two levels: testing the FLRW metric through the distance sum rule (DSR) and determining/constraining cosmic curvature. We propose an effective and efficient (redshift) evolution model for performing the former test, which allows us to concretely specify the violation criterion for the FLRW DSR. If the FLRW metric is consistent with the observations, then on the second level the cosmic curvature parameter will be constrained to ∼0.057 or ∼0.041 (1 σ ), depending on the availability of high-redshift supernovae, which is much more stringent than current model-independent techniques. We also show that the bias in the time-delay method might be well controlled, leading to robust results. The proposed method is a new independent tool for both testing the fundamental assumptions of homogeneity and isotropy in cosmology and for determining cosmic curvature. It is complementary to cosmic microwave background plus baryon acoustic oscillation analyses, which normally assume a cosmological model with dark energy domination in the late-time universe.

  19. Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks.

    Science.gov (United States)

    Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

    2016-07-07

    In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles.

  20. THE ROLE OF ARTICLE LEVEL METRICS IN SCIENTIFIC PUBLISHING

    Directory of Open Access Journals (Sweden)

    Vladimir TRAJKOVSKI

    2016-04-01

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

  1. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  2. Rule-based topology system for spatial databases to validate complex geographic datasets

    Science.gov (United States)

    Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

    2017-06-01

    A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

  3. Performance metrics for the evaluation of hyperspectral chemical identification systems

    Science.gov (United States)

    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.

  4. Optimal Sequential Rules for Computer-Based Instruction.

    Science.gov (United States)

    Vos, Hans J.

    1998-01-01

    Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…

  5. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  6. Metric Learning for Hyperspectral Image Segmentation

    Science.gov (United States)

    Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

    2011-01-01

    We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

  7. Sigma Routing Metric for RPL Protocol

    Directory of Open Access Journals (Sweden)

    Paul Sanmartin

    2018-04-01

    Full Text Available This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX. However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.

  8. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  9. Good and Bad Objects : Cardinality-Based Rules

    NARCIS (Netherlands)

    Dimitrov, D.A.; Borm, P.E.M.; Hendrickx, R.L.P.

    2003-01-01

    We consider the problem of ranking sets of objects, the members of which are mutually compatible.Assuming that each object is either good or bad, we axiomatically characterize three cardinality-based rules which arise naturally in this dichotomous setting.They are what we call the symmetric

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

    African Journals Online (AJOL)

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

  11. GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA

    Directory of Open Access Journals (Sweden)

    T. Nadana Ravishankar

    2015-07-01

    Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.

  12. A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

    Directory of Open Access Journals (Sweden)

    Anton Setiawan Honggowibowo

    2009-12-01

    Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

  13. Species-Level Differences in Hyperspectral Metrics among Tropical Rainforest Trees as Determined by a Tree-Based Classifier

    Directory of Open Access Journals (Sweden)

    Dar A. Roberts

    2012-06-01

    Full Text Available This study explores a method to classify seven tropical rainforest tree species from full-range (400–2,500 nm hyperspectral data acquired at tissue (leaf and bark, pixel and crown scales using laboratory and airborne sensors. Metrics that respond to vegetation chemistry and structure were derived using narrowband indices, derivative- and absorption-based techniques, and spectral mixture analysis. We then used the Random Forests tree-based classifier to discriminate species with minimally-correlated, importance-ranked metrics. At all scales, best overall accuracies were achieved with metrics derived from all four techniques and that targeted chemical and structural properties across the visible to shortwave infrared spectrum (400–2500 nm. For tissue spectra, overall accuracies were 86.8% for leaves, 74.2% for bark, and 84.9% for leaves plus bark. Variation in tissue metrics was best explained by an axis of red absorption related to photosynthetic leaves and an axis distinguishing bark water and other chemical absorption features. Overall accuracies for individual tree crowns were 71.5% for pixel spectra, 70.6% crown-mean spectra, and 87.4% for a pixel-majority technique. At pixel and crown scales, tree structure and phenology at the time of image acquisition were important factors that determined species spectral separability.

  14. A two-stage stochastic rule-based model to determine pre-assembly buffer content

    Science.gov (United States)

    Gunay, Elif Elcin; Kula, Ufuk

    2018-01-01

    This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decides the spare vehicle quantities, where the second stage model recovers the scrambled sequence respect to pre-defined rules. The problem is solved by sample average approximation (SAA) algorithm. We conduct a numerical study to compare the solutions of heuristic model with optimal ones and provide following insights: (i) as the mismatch between paint entrance and scheduled sequence decreases, the rule-based heuristic model recovers the scrambled sequence as good as the optimal resequencing model, (ii) the rule-based model is more sensitive to the mismatch between the paint entrance and scheduled sequences for recovering the scrambled sequence, (iii) as the defect rate increases, the difference in recovery effectiveness between rule-based heuristic and optimal solutions increases, (iv) as buffer capacity increases, the recovery effectiveness of the optimization model outperforms heuristic model, (v) as expected the rule-based model holds more inventory than the optimization model.

  15. Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

    Science.gov (United States)

    Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. PMID:24511304

  16. Classification based on pruning and double covered rule sets for the internet of things applications.

    Science.gov (United States)

    Li, Shasha; Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  18. National Metrical Types in Nineteenth Century Art Song

    Directory of Open Access Journals (Sweden)

    Leigh VanHandel

    2010-01-01

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

  19. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  20. Evaluating the Rule of 10s in Cleft Lip Repair: Do Data Support Dogma?

    Science.gov (United States)

    Chow, Ian; Purnell, Chad A; Hanwright, Philip J; Gosain, Arun K

    2016-09-01

    Cleft lip represents one of the most common birth defects in the world. Although the timing of cleft lip repair is contingent on a number of factors, the "rule of 10s" remains a frequently quoted safety benchmark. Initially reported by Wilhelmsen and Musgrave in 1966 and modified by Millard in 1976, this rule referred to performing surgery once patients had reached cutoffs in weight, hemoglobin, and age/leukocyte count. Despite significant advances in both surgical and anesthetic technique, the oft-quoted "rule of 10s" has not been systematically investigated since its inception. Patients who underwent primary cleft lip repair were identified from the National Surgical Quality Improvement Program Pediatric database. Multivariate logistic regression models were used to determine the independent effect of each rule of 10 metric or violation of the rule of 10s as a whole on postoperative complications, and to determine independent risk factors for complications in cleft lip surgery. One thousand three hundred thirteen patients met inclusion criteria, with a 3.6 percent complication rate. Of the included patients, 151 (11.5 percent) violated at least one facet of the rule of 10s. Other than patient weight, neither the rule of 10s nor any individual metric was significantly predictive of postoperative complications. Since its introduction nearly a half century ago, the risks associated with performing surgery in patients who violate the rule of 10s has undergone dramatic reductions. This analysis highlights the need to continually validate and evaluate dogma as the field continues to advance. Risk, III.

  1. Rule-based conversion of closely-related languages: a Dutch-to-Afrikaans convertor

    CSIR Research Space (South Africa)

    Van Huyssteen, GB

    2009-11-01

    Full Text Available and performance of a rule-based Dutch-to-Afrikaans converter, with the aim to transform Dutch text so that it looks more like an Afrikaans text (even though it might not even be a good Dutch translation). The rules we used is based on systematic orthographic...

  2. Using Publication Metrics to Highlight Academic Productivity and Research Impact

    Science.gov (United States)

    Carpenter, Christopher R.; Cone, David C.; Sarli, Cathy C.

    2016-01-01

    This article provides a broad overview of widely available measures of academic productivity and impact using publication data and highlights uses of these metrics for various purposes. Metrics based on publication data include measures such as number of publications, number of citations, the journal impact factor score, and the h-index, as well as emerging metrics based on document-level metrics. Publication metrics can be used for a variety of purposes for tenure and promotion, grant applications and renewal reports, benchmarking, recruiting efforts, and administrative purposes for departmental or university performance reports. The authors also highlight practical applications of measuring and reporting academic productivity and impact to emphasize and promote individual investigators, grant applications, or department output. PMID:25308141

  3. Metrics-based assessments of research: incentives for 'institutional plagiarism'?

    Science.gov (United States)

    Berry, Colin

    2013-06-01

    The issue of plagiarism--claiming credit for work that is not one's own, rightly, continues to cause concern in the academic community. An analysis is presented that shows the effects that may arise from metrics-based assessments of research, when credit for an author's outputs (chiefly publications) is given to an institution that did not support the research but which subsequently employs the author. The incentives for what is termed here "institutional plagiarism" are demonstrated with reference to the UK Research Assessment Exercise in which submitting units of assessment are shown in some instances to derive around twice the credit for papers produced elsewhere by new recruits, compared to papers produced 'in-house'.

  4. Oxytocin modulates trait-based rule following

    NARCIS (Netherlands)

    Gross, J.; de Dreu, C.K.W.

    Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive

  5. An evaluation and implementation of rule-based Home Energy Management System using the Rete algorithm.

    Science.gov (United States)

    Kawakami, Tomoya; Fujita, Naotaka; Yoshihisa, Tomoki; Tsukamoto, Masahiko

    2014-01-01

    In recent years, sensors become popular and Home Energy Management System (HEMS) takes an important role in saving energy without decrease in QoL (Quality of Life). Currently, many rule-based HEMSs have been proposed and almost all of them assume "IF-THEN" rules. The Rete algorithm is a typical pattern matching algorithm for IF-THEN rules. Currently, we have proposed a rule-based Home Energy Management System (HEMS) using the Rete algorithm. In the proposed system, rules for managing energy are processed by smart taps in network, and the loads for processing rules and collecting data are distributed to smart taps. In addition, the number of processes and collecting data are reduced by processing rules based on the Rete algorithm. In this paper, we evaluated the proposed system by simulation. In the simulation environment, rules are processed by a smart tap that relates to the action part of each rule. In addition, we implemented the proposed system as HEMS using smart taps.

  6. Semantic metrics

    OpenAIRE

    Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel

    2006-01-01

    In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...

  7. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  8. Application of Sigma Metrics Analysis for the Assessment and Modification of Quality Control Program in the Clinical Chemistry Laboratory of a Tertiary Care Hospital.

    Science.gov (United States)

    Iqbal, Sahar; Mustansar, Tazeen

    2017-03-01

    Sigma is a metric that quantifies the performance of a process as a rate of Defects-Per-Million opportunities. In clinical laboratories, sigma metric analysis is used to assess the performance of laboratory process system. Sigma metric is also used as a quality management strategy for a laboratory process to improve the quality by addressing the errors after identification. The aim of this study is to evaluate the errors in quality control of analytical phase of laboratory system by sigma metric. For this purpose sigma metric analysis was done for analytes using the internal and external quality control as quality indicators. Results of sigma metric analysis were used to identify the gaps and need for modification in the strategy of laboratory quality control procedure. Sigma metric was calculated for quality control program of ten clinical chemistry analytes including glucose, chloride, cholesterol, triglyceride, HDL, albumin, direct bilirubin, total bilirubin, protein and creatinine, at two control levels. To calculate the sigma metric imprecision and bias was calculated with internal and external quality control data, respectively. The minimum acceptable performance was considered as 3 sigma. Westgard sigma rules were applied to customize the quality control procedure. Sigma level was found acceptable (≥3) for glucose (L2), cholesterol, triglyceride, HDL, direct bilirubin and creatinine at both levels of control. For rest of the analytes sigma metric was found control levels (8.8 and 8.0 at L2 and L3, respectively). We conclude that analytes with the sigma value quality control procedure. In this study application of sigma rules provided us the practical solution for improved and focused design of QC procedure.

  9. Techniques and implementation of the embedded rule-based expert system using Ada

    Science.gov (United States)

    Liberman, Eugene M.; Jones, Robert E.

    1991-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  10. Metric modular spaces

    CERN Document Server

    Chistyakov, Vyacheslav

    2015-01-01

    Aimed toward researchers and graduate students familiar with elements of functional analysis, linear algebra, and general topology; this book contains a general study of modulars, modular spaces, and metric modular spaces. Modulars may be thought of as generalized velocity fields and serve two important purposes: generate metric spaces in a unified manner and provide a weaker convergence, the modular convergence, whose topology is non-metrizable in general. Metric modular spaces are extensions of metric spaces, metric linear spaces, and classical modular linear spaces. The topics covered include the classification of modulars, metrizability of modular spaces, modular transforms and duality between modular spaces, metric  and modular topologies. Applications illustrated in this book include: the description of superposition operators acting in modular spaces, the existence of regular selections of set-valued mappings, new interpretations of spaces of Lipschitzian and absolutely continuous mappings, the existe...

  11. A Metric on Phylogenetic Tree Shapes.

    Science.gov (United States)

    Colijn, C; Plazzotta, G

    2018-01-01

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

  12. Next-Generation Metrics: Responsible Metrics & Evaluation for Open Science

    Energy Technology Data Exchange (ETDEWEB)

    Wilsdon, J.; Bar-Ilan, J.; Peters, I.; Wouters, P.

    2016-07-01

    Metrics evoke a mixed reaction from the research community. A commitment to using data to inform decisions makes some enthusiastic about the prospect of granular, real-time analysis o of research and its wider impacts. Yet we only have to look at the blunt use of metrics such as journal impact factors, h-indices and grant income targets, to be reminded of the pitfalls. Some of the most precious qualities of academic culture resist simple quantification, and individual indicators often struggle to do justice to the richness and plurality of research. Too often, poorly designed evaluation criteria are “dominating minds, distorting behaviour and determining careers (Lawrence, 2007).” Metrics hold real power: they are constitutive of values, identities and livelihoods. How to exercise that power to more positive ends has been the focus of several recent and complementary initiatives, including the San Francisco Declaration on Research Assessment (DORA1), the Leiden Manifesto2 and The Metric Tide3 (a UK government review of the role of metrics in research management and assessment). Building on these initiatives, the European Commission, under its new Open Science Policy Platform4, is now looking to develop a framework for responsible metrics for research management and evaluation, which can be incorporated into the successor framework to Horizon 2020. (Author)

  13. A Rules-Based Simulation of Bacterial Turbulence

    Science.gov (United States)

    Mikel-Stites, Maxwell; Staples, Anne

    2015-11-01

    In sufficiently dense bacterial populations (>40% bacteria by volume), unusual collective swimming behaviors have been consistently observed, resembling von Karman vortex streets. The source of these collective swimming behavior has yet to be fully determined, and as of yet, no research has been conducted that would define whether or not this behavior is derived predominantly from the properties of the surrounding media, or if it is an emergent behavior as a result of the ``rules'' governing the behavior of individual bacteria. The goal of this research is to ascertain whether or not it is possible to design a simulation that can replicate the qualitative behavior of the densely packed bacterial populations using only behavioral rules to govern the actions of each bacteria, with the physical properties of the media being neglected. The results of the simulation will address whether or not it is possible for the system's overall behavior to be driven exclusively by these rule-based dynamics. In order to examine this, the behavioral simulation was written in MATLAB on a fixed grid, and updated sequentially with the bacterial behavior, including randomized tumbling, gathering and perceptual sub-functions. If the simulation is successful, it will serve as confirmation that it is possible to generate these qualitatively vortex-like behaviors without specific physical media (that the phenomena arises in emergent fashion from behavioral rules), or as evidence that the observed behavior requires some specific set of physical parameters.

  14. Low-complexity atlas-based prostate segmentation by combining global, regional, and local metrics

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Qiuliang; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California Los Angeles, California 90095 (United States)

    2014-04-15

    Purpose: To improve the efficiency of atlas-based segmentation without compromising accuracy, and to demonstrate the validity of the proposed method on MRI-based prostate segmentation application. Methods: Accurate and efficient automatic structure segmentation is an important task in medical image processing. Atlas-based methods, as the state-of-the-art, provide good segmentation at the cost of a large number of computationally intensive nonrigid registrations, for anatomical sites/structures that are subject to deformation. In this study, the authors propose to utilize a combination of global, regional, and local metrics to improve the accuracy yet significantly reduce the number of required nonrigid registrations. The authors first perform an affine registration to minimize the global mean squared error (gMSE) to coarsely align each atlas image to the target. Subsequently, atarget-specific regional MSE (rMSE), demonstrated to be a good surrogate for dice similarity coefficient (DSC), is used to select a relevant subset from the training atlas. Only within this subset are nonrigid registrations performed between the training images and the target image, to minimize a weighted combination of gMSE and rMSE. Finally, structure labels are propagated from the selected training samples to the target via the estimated deformation fields, and label fusion is performed based on a weighted combination of rMSE and local MSE (lMSE) discrepancy, with proper total-variation-based spatial regularization. Results: The proposed method was applied to a public database of 30 prostate MR images with expert-segmented structures. The authors’ method, utilizing only eight nonrigid registrations, achieved a performance with a median/mean DSC of over 0.87/0.86, outperforming the state-of-the-art full-fledged atlas-based segmentation approach of which the median/mean DSC was 0.84/0.82 when applying to their data set. Conclusions: The proposed method requires a fixed number of nonrigid

  15. In the pursuit of a semantic similarity metric based on UMLS annotations for articles in PubMed Central Open Access.

    Science.gov (United States)

    Garcia Castro, Leyla Jael; Berlanga, Rafael; Garcia, Alexander

    2015-10-01

    Although full-text articles are provided by the publishers in electronic formats, it remains a challenge to find related work beyond the title and abstract context. Identifying related articles based on their abstract is indeed a good starting point; this process is straightforward and does not consume as many resources as full-text based similarity would require. However, further analyses may require in-depth understanding of the full content. Two articles with highly related abstracts can be substantially different regarding the full content. How similarity differs when considering title-and-abstract versus full-text and which semantic similarity metric provides better results when dealing with full-text articles are the main issues addressed in this manuscript. We have benchmarked three similarity metrics - BM25, PMRA, and Cosine, in order to determine which one performs best when using concept-based annotations on full-text documents. We also evaluated variations in similarity values based on title-and-abstract against those relying on full-text. Our test dataset comprises the Genomics track article collection from the 2005 Text Retrieval Conference. Initially, we used an entity recognition software to semantically annotate titles and abstracts as well as full-text with concepts defined in the Unified Medical Language System (UMLS®). For each article, we created a document profile, i.e., a set of identified concepts, term frequency, and inverse document frequency; we then applied various similarity metrics to those document profiles. We considered correlation, precision, recall, and F1 in order to determine which similarity metric performs best with concept-based annotations. For those full-text articles available in PubMed Central Open Access (PMC-OA), we also performed dispersion analyses in order to understand how similarity varies when considering full-text articles. We have found that the PubMed Related Articles similarity metric is the most suitable for

  16. Design of a Fuzzy Rule Base Expert System to Predict and Classify ...

    African Journals Online (AJOL)

    The main objective of design of a rule base expert system using fuzzy logic approach is to predict and forecast the risk level of cardiac patients to avoid sudden death. In this proposed system, uncertainty is captured using rule base and classification using fuzzy c-means clustering is discussed to overcome the risk level, ...

  17. Metrics for energy resilience

    International Nuclear Information System (INIS)

    Roege, Paul E.; Collier, Zachary A.; Mancillas, James; McDonagh, John A.; Linkov, Igor

    2014-01-01

    Energy lies at the backbone of any advanced society and constitutes an essential prerequisite for economic growth, social order and national defense. However there is an Achilles heel to today's energy and technology relationship; namely a precarious intimacy between energy and the fiscal, social, and technical systems it supports. Recently, widespread and persistent disruptions in energy systems have highlighted the extent of this dependence and the vulnerability of increasingly optimized systems to changing conditions. Resilience is an emerging concept that offers to reconcile considerations of performance under dynamic environments and across multiple time frames by supplementing traditionally static system performance measures to consider behaviors under changing conditions and complex interactions among physical, information and human domains. This paper identifies metrics useful to implement guidance for energy-related planning, design, investment, and operation. Recommendations are presented using a matrix format to provide a structured and comprehensive framework of metrics relevant to a system's energy resilience. The study synthesizes previously proposed metrics and emergent resilience literature to provide a multi-dimensional model intended for use by leaders and practitioners as they transform our energy posture from one of stasis and reaction to one that is proactive and which fosters sustainable growth. - Highlights: • Resilience is the ability of a system to recover from adversity. • There is a need for methods to quantify and measure system resilience. • We developed a matrix-based approach to generate energy resilience metrics. • These metrics can be used in energy planning, system design, and operations

  18. Rule-based emergency action level monitor prototype

    International Nuclear Information System (INIS)

    Touchton, R.A.; Gunter, A.D.; Cain, D.

    1985-01-01

    In late 1983, the Electric Power Research Institute (EPRI) began a program to encourage and stimulate the development of artificial intelligence (AI) applications for the nuclear industry. Development of a rule-based emergency action level classification system prototype is discussed. The paper describes both the full prototype currently under development and the completed, simplified prototype

  19. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  20. Supplier selection using different metric functions

    Directory of Open Access Journals (Sweden)

    Omosigho S.E.

    2015-01-01

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

  1. Four rules for taking your message to Wall Street.

    Science.gov (United States)

    Hutton, A

    2001-05-01

    Managers fail to communicate effectively with Wall Street for all sorts of reasons. But neglecting the investment community--particularly the analysts whose opinions shape the market and whose recommendations often make or break a company's share price--can knock the most carefully conceived and brilliantly executed strategy off course. The companies that struggle the most with providing good information to analysts are those in rapidly evolving industries, where the gap between traditional performance metrics and economic realities is at its widest. In these industries, a company's strategy and the variables that govern its performance can change radically in a short time. What's more, the metrics used to report performance often fail to capture the drivers of value in today's information economy. Few accounting measures are helpful when it comes to assessing the intangible assets--knowledge, skilled employees, and so forth--on which many of today's fastest-growing companies build their strategies. According to Amy Hutton, an associate professor at Harvard Business School, there are four basic rules for clear communications with Wall Street. First, make sure that your company's financial reporting reflects your strategy as closely as possible. Second, popularize the nonfinancial metrics that best predict--and flatter--the performance of your businesses. Third, appoint managers with recognized credibility to your strategic operations. Finally, cultivate the market experts who cover the industries in which you seek to compete. Hutton shows how AOL successfully followed these rules as it significantly changed its strategic direction and competitive arena.

  2. Landscape pattern metrics and regional assessment

    Science.gov (United States)

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

    1999-01-01

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

  3. Rule-based category learning in children: the role of age and executive functioning.

    Directory of Open Access Journals (Sweden)

    Rahel Rabi

    Full Text Available Rule-based category learning was examined in 4-11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning.

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

    Science.gov (United States)

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

    2015-09-01

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

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

    International Nuclear Information System (INIS)

    Gonzalez-Diaz, P.F.

    1991-01-01

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

  6. Evidence Based Cataloguing: Moving Beyond the Rules

    Directory of Open Access Journals (Sweden)

    Kathy Carter

    2010-12-01

    Full Text Available Cataloguing is sometimes regarded as a rule-bound, production-based activity that offers little scope for professional judgement and decision-making. In reality, cataloguing involves challenging decisions that can have significant service and financial impacts. The current environment for cataloguing is a maelstrom of changing demands and competing visions for the future. With information-seekers turning en masse to Google and their behaviour receiving greater attention, library vendors are offering “discovery layer” products to replace traditional OPACs, and cataloguers are examining and debating a transformed version of their descriptive cataloguing rules (Resource Description and Access or RDA. In his “Perceptions of the future of cataloging: Is the sky really falling?” (2009, Ivey provides a good summary of this environment. At the same time, myriad new metadata formats and schema are being developed and applied for digital collections in libraries and other institutions. In today’s libraries, cataloguing is no longer limited to management of traditional AACR and MARC-based metadata for traditional library collections. And like their parent institutions, libraries cannot ignore growing pressures to demonstrate accountability and tangible value provided by their services. More than ever, research and an evidence based approach can help guide cataloguing decision-making.

  7. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    Science.gov (United States)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  8. GraDit: graph-based data repair algorithm for multiple data edits rule violations

    Science.gov (United States)

    Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

    2018-03-01

    Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

  9. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  10. A rule-based smart automated fertilization and irrigation systems

    Science.gov (United States)

    Yousif, Musab El-Rashid; Ghafar, Khairuddin; Zahari, Rahimi; Lim, Tiong Hoo

    2018-04-01

    Smart automation in industries has become very important as it can improve the reliability and efficiency of the systems. The use of smart technologies in agriculture have increased over the year to ensure and control the production of crop and address food security. However, it is important to use proper irrigation systems avoid water wastage and overfeeding of the plant. In this paper, a Smart Rule-based Automated Fertilization and Irrigation System is proposed and evaluated. We propose a rule based decision making algorithm to monitor and control the food supply to the plant and the soil quality. A build-in alert system is also used to update the farmer using a text message. The system is developed and evaluated using a real hardware.

  11. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  12. Properties of C-metric spaces

    Science.gov (United States)

    Croitoru, Anca; Apreutesei, Gabriela; Mastorakis, Nikos E.

    2017-09-01

    The subject of this paper belongs to the theory of approximate metrics [23]. An approximate metric on X is a real application defined on X × X that satisfies only a part of the metric axioms. In a recent paper [23], we introduced a new type of approximate metric, named C-metric, that is an application which satisfies only two metric axioms: symmetry and triangular inequality. The remarkable fact in a C-metric space is that a topological structure induced by the C-metric can be defined. The innovative idea of this paper is that we obtain some convergence properties of a C-metric space in the absence of a metric. In this paper we investigate C-metric spaces. The paper is divided into four sections. Section 1 is for Introduction. In Section 2 we recall some concepts and preliminary results. In Section 3 we present some properties of C-metric spaces, such as convergence properties, a canonical decomposition and a C-fixed point theorem. Finally, in Section 4 some conclusions are highlighted.

  13. Learning Low-Dimensional Metrics

    OpenAIRE

    Jain, Lalit; Mason, Blake; Nowak, Robert

    2017-01-01

    This paper investigates the theoretical foundations of metric learning, focused on three key questions that are not fully addressed in prior work: 1) we consider learning general low-dimensional (low-rank) metrics as well as sparse metrics; 2) we develop upper and lower (minimax)bounds on the generalization error; 3) we quantify the sample complexity of metric learning in terms of the dimension of the feature space and the dimension/rank of the underlying metric;4) we also bound the accuracy ...

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

    Science.gov (United States)

    Bonnell, Andrew G.

    2016-01-01

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

  15. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    International Nuclear Information System (INIS)

    Wang, M; Hu, N Q; Qin, G J

    2011-01-01

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  16. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Wang, M; Hu, N Q; Qin, G J, E-mail: hnq@nudt.edu.cn, E-mail: wm198063@yahoo.com.cn [School of Mechatronic Engineering and Automation, National University of Defense Technology, ChangSha, Hunan, 410073 (China)

    2011-07-19

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  17. Rule-based Test Generation with Mind Maps

    Directory of Open Access Journals (Sweden)

    Dimitry Polivaev

    2012-02-01

    Full Text Available This paper introduces basic concepts of rule based test generation with mind maps, and reports experiences learned from industrial application of this technique in the domain of smart card testing by Giesecke & Devrient GmbH over the last years. It describes the formalization of test selection criteria used by our test generator, our test generation architecture and test generation framework.

  18. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

    Science.gov (United States)

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-01-01

    Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

  19. A guide to calculating habitat-quality metrics to inform conservation of highly mobile species

    Science.gov (United States)

    Bieri, Joanna A.; Sample, Christine; Thogmartin, Wayne E.; Diffendorfer, James E.; Earl, Julia E.; Erickson, Richard A.; Federico, Paula; Flockhart, D. T. Tyler; Nicol, Sam; Semmens, Darius J.; Skraber, T.; Wiederholt, Ruscena; Mattsson, Brady J.

    2018-01-01

    Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.Considerations for Resource ManagersManagement objectives, proposed actions, data availability and quality, and model assumptions are all relevant considerations when applying and interpreting habitat-quality metrics.Graph-based metrics answer questions related to habitat centrality and connectivity, are suitable for populations with any movement pattern, quantify basic spatial and temporal patterns of occupancy and movement, and require the least data.Occupancy-based metrics answer questions about likelihood of persistence or colonization, are suitable for populations that undergo localized extinctions, quantify spatial and temporal patterns of occupancy and movement, and require a moderate amount of data.Demographic-based metrics answer questions about relative or absolute population size, are suitable for populations with any movement pattern, quantify demographic

  20. The Hidden Flow Structure and Metric Space of Network Embedding Algorithms Based on Random Walks.

    Science.gov (United States)

    Gu, Weiwei; Gong, Li; Lou, Xiaodan; Zhang, Jiang

    2017-10-13

    Network embedding which encodes all vertices in a network as a set of numerical vectors in accordance with it's local and global structures, has drawn widespread attention. Network embedding not only learns significant features of a network, such as the clustering and linking prediction but also learns the latent vector representation of the nodes which provides theoretical support for a variety of applications, such as visualization, link prediction, node classification, and recommendation. As the latest progress of the research, several algorithms based on random walks have been devised. Although those algorithms have drawn much attention for their high scores in learning efficiency and accuracy, there is still a lack of theoretical explanation, and the transparency of those algorithms has been doubted. Here, we propose an approach based on the open-flow network model to reveal the underlying flow structure and its hidden metric space of different random walk strategies on networks. We show that the essence of embedding based on random walks is the latent metric structure defined on the open-flow network. This not only deepens our understanding of random- walk-based embedding algorithms but also helps in finding new potential applications in network embedding.

  1. Scalar-metric and scalar-metric-torsion gravitational theories

    International Nuclear Information System (INIS)

    Aldersley, S.J.

    1977-01-01

    The techniques of dimensional analysis and of the theory of tensorial concomitants are employed to study field equations in gravitational theories which incorporate scalar fields of the Brans-Dicke type. Within the context of scalar-metric gravitational theories, a uniqueness theorem for the geometric (or gravitational) part of the field equations is proven and a Lagrangian is determined which is uniquely specified by dimensional analysis. Within the context of scalar-metric-torsion gravitational theories a uniqueness theorem for field Lagrangians is presented and the corresponding Euler-Lagrange equations are given. Finally, an example of a scalar-metric-torsion theory is presented which is similar in many respects to the Brans-Dicke theory and the Einstein-Cartan theory

  2. Moving from Rule-based to Principle-based in Public Sector: Preparers' Perspective

    OpenAIRE

    Roshayani Arshad; Normah Omar; Siti Fatimah Awang

    2013-01-01

    The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived signific...

  3. Metrics of quantum states

    International Nuclear Information System (INIS)

    Ma Zhihao; Chen Jingling

    2011-01-01

    In this work we study metrics of quantum states, which are natural generalizations of the usual trace metric and Bures metric. Some useful properties of the metrics are proved, such as the joint convexity and contractivity under quantum operations. Our result has a potential application in studying the geometry of quantum states as well as the entanglement detection.

  4. Enhancing reliable online transaction with intelligent rule-based ...

    African Journals Online (AJOL)

    Enhancing reliable online transaction with intelligent rule-based fraud detection technique. ... These are with a bid to reducing amongst other things the cost of production and also dissuade the poor handling of Nigeria currency. The CBN pronouncement has necessitated the upsurge in transactions completed with credit ...

  5. Reservoir adaptive operating rules based on both of historical streamflow and future projections

    Science.gov (United States)

    Zhang, Wei; Liu, Pan; Wang, Hao; Chen, Jie; Lei, Xiaohui; Feng, Maoyuan

    2017-10-01

    Climate change is affecting hydrological variables and consequently is impacting water resources management. Historical strategies are no longer applicable under climate change. Therefore, adaptive management, especially adaptive operating rules for reservoirs, has been developed to mitigate the possible adverse effects of climate change. However, to date, adaptive operating rules are generally based on future projections involving uncertainties under climate change, yet ignoring historical information. To address this, we propose an approach for deriving adaptive operating rules considering both historical information and future projections, namely historical and future operating rules (HAFOR). A robustness index was developed by comparing benefits from HAFOR with benefits from conventional operating rules (COR). For both historical and future streamflow series, maximizations of both average benefits and the robustness index were employed as objectives, and four trade-offs were implemented to solve the multi-objective problem. Based on the integrated objective, the simulation-based optimization method was used to optimize the parameters of HAFOR. Using the Dongwushi Reservoir in China as a case study, HAFOR was demonstrated to be an effective and robust method for developing adaptive operating rules under the uncertain changing environment. Compared with historical or projected future operating rules (HOR or FPOR), HAFOR can reduce the uncertainty and increase the robustness for future projections, especially regarding results of reservoir releases and volumes. HAFOR, therefore, facilitates adaptive management in the context that climate change is difficult to predict accurately.

  6. A heuristic way of obtaining the Kerr metric

    International Nuclear Information System (INIS)

    Enderlein, J.

    1997-01-01

    An intuitive, straightforward way of finding the metric of a rotating black hole is presented, based on the algebra of differential forms. The representation obtained for the metric displays a simplicity which is not obvious in the usual Boyer Lindquist coordinates. copyright 1997 American Association of Physics Teachers

  7. Healthcare4VideoStorm: Making Smart Decisions Based on Storm Metrics.

    Science.gov (United States)

    Zhang, Weishan; Duan, Pengcheng; Chen, Xiufeng; Lu, Qinghua

    2016-04-23

    Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies' granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications.

  8. A rule-based stemmer for Arabic Gulf dialect

    Directory of Open Access Journals (Sweden)

    Belal Abuata

    2015-04-01

    Full Text Available Arabic dialects arewidely used from many years ago instead of Modern Standard Arabic language in many fields. The presence of dialects in any language is a big challenge. Dialects add a new set of variational dimensions in some fields like natural language processing, information retrieval and even in Arabic chatting between different Arab nationals. Spoken dialects have no standard morphological, phonological and lexical like Modern Standard Arabic. Hence, the objective of this paper is to describe a procedure or algorithm by which a stem for the Arabian Gulf dialect can be defined. The algorithm is rule based. Special rules are created to remove the suffixes and prefixes of the dialect words. Also, the algorithm applies rules related to the word size and the relation between adjacent letters. The algorithm was tested for a number of words and given a good correct stem ratio. The algorithm is also compared with two Modern Standard Arabic algorithms. The results showed that Modern Standard Arabic stemmers performed poorly with Arabic Gulf dialect and our algorithm performed poorly when applied for Modern Standard Arabic words.

  9. Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

    Science.gov (United States)

    O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

    2017-12-06

    Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

  10. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis

    International Nuclear Information System (INIS)

    Li Qiang; Doi Kunio

    2006-01-01

    Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists detect various lesions in medical images. In CAD schemes, classifiers play a key role in achieving a high lesion detection rate and a low false-positive rate. Although many popular classifiers such as linear discriminant analysis and artificial neural networks have been employed in CAD schemes for reduction of false positives, a rule-based classifier has probably been the simplest and most frequently used one since the early days of development of various CAD schemes. However, with existing rule-based classifiers, there are major disadvantages that significantly reduce their practicality and credibility. The disadvantages include manual design, poor reproducibility, poor evaluation methods such as resubstitution, and a large overtraining effect. An automated rule-based classifier with a minimized overtraining effect can overcome or significantly reduce the extent of the above-mentioned disadvantages. In this study, we developed an 'optimal' method for the selection of cutoff thresholds and a fully automated rule-based classifier. Experimental results performed with Monte Carlo simulation and a real lung nodule CT data set demonstrated that the automated threshold selection method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the constructed rule-based classifier. We believe that this threshold selection method is very useful in the construction of automated rule-based classifiers with minimized overtraining effect

  11. Optimization of Simple Monetary Policy Rules on the Base of Estimated DSGE-model

    OpenAIRE

    Shulgin, A.

    2015-01-01

    Optimization of coefficients in monetary policy rules is performed on the base of the DSGE-model with two independent monetary policy instruments estimated on the Russian data. It was found that welfare maximizing policy rules lead to inadequate result and pro-cyclical monetary policy. Optimal coefficients in Taylor rule and exchange rate rule allow to decrease volatility estimated on Russian data of 2001-2012 by about 20%. The degree of exchange rate flexibility parameter was found to be low...

  12. Association-rule-based tuberculosis disease diagnosis

    Science.gov (United States)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  13. Rule-based detection of intrathoracic airway trees

    International Nuclear Information System (INIS)

    Sonka, M.; Park, W.; Hoffman, E.A.

    1996-01-01

    New sensitive and reliable methods for assessing alterations in regional lung structure and function are critically important for the investigation and treatment of pulmonary diseases. Accurate identification of the airway tree will provide an assessment of airway structure and will provide a means by which multiple volumetric images of the lung at the same lung volume over time can be used to assess regional parenchymal changes. The authors describe a novel rule-based method for the segmentation of airway trees from three-dimensional (3-D) sets of computed tomography (CT) images, and its validation. The presented method takes advantage of a priori anatomical knowledge about pulmonary airway and vascular trees and their interrelationships. The method is based on a combination of 3-D seeded region growing that is used to identify large airways, rule-based two-dimensional (2-D) segmentation of individual CT slices to identify probable locations of smaller diameter airways, and merging of airway regions across the 3-D set of slices resulting in a tree-like airway structure. The method was validated in 40 3-mm-thick CT sections from five data sets of canine lungs scanned via electron beam CT in vivo with lung volume held at a constant pressure. The method's performance was compared with that of the conventional 3-D region growing method. The method substantially outperformed an existing conventional approach to airway tree detection

  14. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    OpenAIRE

    Chen, Qipeng; Fan, Zhong; Kaleshi, Dritan; Armour, Simon M D

    2015-01-01

    Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induct...

  15. Neural Substrates of Similarity and Rule-based Strategies in Judgment

    Directory of Open Access Journals (Sweden)

    Bettina eVon Helversen

    2014-10-01

    Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

  16. Ruled-based control of off-grid desalination powered by renewable energies

    Directory of Open Access Journals (Sweden)

    Alvaro Serna

    2015-08-01

    Full Text Available A rule-based control is presented for desalination plants operating under variable, renewable power availability. This control algorithm is based on two sets of rules: first, a list that prioritizes the reverse osmosis (RO units of the plant is created, based on the current state and the expected water demand; secondly, the available energy is then dispatched to these units following this prioritized list. The selected strategy is tested on a specific case study: a reverse osmosis plant designed for the production of desalinated water powered by wind and wave energy. Simulation results illustrate the correct performance of the plant under this control.

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

    Science.gov (United States)

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

    2018-05-01

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

  18. DEVELOP-FPS: a First Person Shooter Development Tool for Rule-based Scripts

    Directory of Open Access Journals (Sweden)

    Bruno Correia

    2012-09-01

    Full Text Available We present DEVELOP-FPS, a software tool specially designed for the development of First Person Shooter (FPS players controlled by Rule Based Scripts. DEVELOP-FPS may be used by FPS developers to create, debug, maintain and compare rule base player behaviours, providing a set of useful functionalities: i for an easy preparation of the right scenarios for game debugging and testing; ii for controlling the game execution: users can stop and resume the game execution at any instant, monitoring and controlling every player in the game, monitoring the state of each player, their rule base activation, being able to issue commands to control their behaviour; and iii to automatically run a certain number of game executions and collect data in order to evaluate and compare the players performance along a sufficient number of similar experiments.

  19. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  20. Application of Entropy-Based Metrics to Identify Emotional Distress from Electroencephalographic Recordings

    Directory of Open Access Journals (Sweden)

    Beatriz García-Martínez

    2016-06-01

    Full Text Available Recognition of emotions is still an unresolved challenge, which could be helpful to improve current human-machine interfaces. Recently, nonlinear analysis of some physiological signals has shown to play a more relevant role in this context than their traditional linear exploration. Thus, the present work introduces for the first time the application of three recent entropy-based metrics: sample entropy (SE, quadratic SE (QSE and distribution entropy (DE to discern between emotional states of calm and negative stress (also called distress. In the last few years, distress has received growing attention because it is a common negative factor in the modern lifestyle of people from developed countries and, moreover, it may lead to serious mental and physical health problems. Precisely, 279 segments of 32-channel electroencephalographic (EEG recordings from 32 subjects elicited to be calm or negatively stressed have been analyzed. Results provide that QSE is the first single metric presented to date with the ability to identify negative stress. Indeed, this metric has reported a discriminant ability of around 70%, which is only slightly lower than the one obtained by some previous works. Nonetheless, discriminant models from dozens or even hundreds of features have been previously obtained by using advanced classifiers to yield diagnostic accuracies about 80%. Moreover, in agreement with previous neuroanatomy findings, QSE has also revealed notable differences for all the brain regions in the neural activation triggered by the two considered emotions. Consequently, given these results, as well as easy interpretation of QSE, this work opens a new standpoint in the detection of emotional distress, which may gain new insights about the brain’s behavior under this negative emotion.

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

    NARCIS (Netherlands)

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

    1996-01-01

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

  2. Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

    Science.gov (United States)

    Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

    In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

  3. Validation of Metrics as Error Predictors

    Science.gov (United States)

    Mendling, Jan

    In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

  4. Rule-based modularization in model transformation languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    2007-01-01

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the basis of relations between source and target metamodels and on the base of generic transformation

  5. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    Science.gov (United States)

    Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

    2007-10-01

    Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

  6. Evaluating and Estimating the WCET Criticality Metric

    DEFF Research Database (Denmark)

    Jordan, Alexander

    2014-01-01

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

  7. Fusion of Thresholding Rules During Wavelet-Based Noisy Image Compression

    Directory of Open Access Journals (Sweden)

    Bekhtin Yury

    2016-01-01

    Full Text Available The new method for combining semisoft thresholding rules during wavelet-based data compression of images with multiplicative noise is suggested. The method chooses the best thresholding rule and the threshold value using the proposed criteria which provide the best nonlinear approximations and take into consideration errors of quantization. The results of computer modeling have shown that the suggested method provides relatively good image quality after restoration in the sense of some criteria such as PSNR, SSIM, etc.

  8. Joining of Ukraine to the European scientific and metric systems

    Directory of Open Access Journals (Sweden)

    O.M. Sazonets

    2015-09-01

    Full Text Available At the present stage of development it is necessary to form the knowledge which structures knowledge as the object of management. In conditions of technological globalism there are structural changes in the information environment of countries. Scientific metrics is sufficiently developed in other countries, especially in the EU. The article contains the description of the first index calculation system of scientific references called Science Citation Index (SCI. The main advantage of this project was searching for information not only by the author and thematic categories, but also by the list of cited literature. The authors define the scientific and metric base in the following way: scientific and metric database (SMBD is the bibliographic and abstract database with the tools for tracking citations of articles published in scientific journals. The most prominent European scientific and metric bases are examined. The authors show that the bases have the performance assessment tools which track down the impact of scientific papers and publications of individual scientists and research institutions. The state of crisis in scientific and technological activities in Ukraine as well as the economy as a whole, needs immediate organization of national scientific and metric system.

  9. Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles.

    Science.gov (United States)

    Pasquier, M; Quek, C; Toh, M

    2001-10-01

    This paper presents part of our research work concerned with the realisation of an Intelligent Vehicle and the technologies required for its routing, navigation, and control. An automated driver prototype has been developed using a self-organising fuzzy rule-based system (POPFNN-CRI(S)) to model and subsequently emulate human driving expertise. The ability of fuzzy logic to represent vague information using linguistic variables makes it a powerful tool to develop rule-based control systems when an exact working model is not available, as is the case of any vehicle-driving task. Designing a fuzzy system, however, is a complex endeavour, due to the need to define the variables and their associated fuzzy sets, and determine a suitable rule base. Many efforts have thus been devoted to automating this process, yielding the development of learning and optimisation techniques. One of them is the family of POP-FNNs, or Pseudo-Outer Product Fuzzy Neural Networks (TVR, AARS(S), AARS(NS), CRI, Yager). These generic self-organising neural networks developed at the Intelligent Systems Laboratory (ISL/NTU) are based on formal fuzzy mathematical theory and are able to objectively extract a fuzzy rule base from training data. In this application, a driving simulator has been developed, that integrates a detailed model of the car dynamics, complete with engine characteristics and environmental parameters, and an OpenGL-based 3D-simulation interface coupled with driving wheel and accelerator/ brake pedals. The simulator has been used on various road scenarios to record from a human pilot driving data consisting of steering and speed control actions associated to road features. Specifically, the POPFNN-CRI(S) system is used to cluster the data and extract a fuzzy rule base modelling the human driving behaviour. Finally, the effectiveness of the generated rule base has been validated using the simulator in autopilot mode.

  10. Metric diffusion along foliations

    CERN Document Server

    Walczak, Szymon M

    2017-01-01

    Up-to-date research in metric diffusion along compact foliations is presented in this book. Beginning with fundamentals from the optimal transportation theory and the theory of foliations; this book moves on to cover Wasserstein distance, Kantorovich Duality Theorem, and the metrization of the weak topology by the Wasserstein distance. Metric diffusion is defined, the topology of the metric space is studied and the limits of diffused metrics along compact foliations are discussed. Essentials on foliations, holonomy, heat diffusion, and compact foliations are detailed and vital technical lemmas are proved to aide understanding. Graduate students and researchers in geometry, topology and dynamics of foliations and laminations will find this supplement useful as it presents facts about the metric diffusion along non-compact foliation and provides a full description of the limit for metrics diffused along foliation with at least one compact leaf on the two dimensions.

  11. Metric reconstruction from Weyl scalars

    Energy Technology Data Exchange (ETDEWEB)

    Whiting, Bernard F; Price, Larry R [Department of Physics, PO Box 118440, University of Florida, Gainesville, FL 32611 (United States)

    2005-08-07

    The Kerr geometry has remained an elusive world in which to explore physics and delve into the more esoteric implications of general relativity. Following the discovery, by Kerr in 1963, of the metric for a rotating black hole, the most major advance has been an understanding of its Weyl curvature perturbations based on Teukolsky's discovery of separable wave equations some ten years later. In the current research climate, where experiments across the globe are preparing for the first detection of gravitational waves, a more complete understanding than concerns just the Weyl curvature is now called for. To understand precisely how comparatively small masses move in response to the gravitational waves they emit, a formalism has been developed based on a description of the whole spacetime metric perturbation in the neighbourhood of the emission region. Presently, such a description is not available for the Kerr geometry. While there does exist a prescription for obtaining metric perturbations once curvature perturbations are known, it has become apparent that there are gaps in that formalism which are still waiting to be filled. The most serious gaps include gauge inflexibility, the inability to include sources-which are essential when the emitting masses are considered-and the failure to describe the l = 0 and 1 perturbation properties. Among these latter properties of the perturbed spacetime, arising from a point mass in orbit, are the perturbed mass and axial component of angular momentum, as well as the very elusive Carter constant for non-axial angular momentum. A status report is given on recent work which begins to repair these deficiencies in our current incomplete description of Kerr metric perturbations.

  12. Metric reconstruction from Weyl scalars

    International Nuclear Information System (INIS)

    Whiting, Bernard F; Price, Larry R

    2005-01-01

    The Kerr geometry has remained an elusive world in which to explore physics and delve into the more esoteric implications of general relativity. Following the discovery, by Kerr in 1963, of the metric for a rotating black hole, the most major advance has been an understanding of its Weyl curvature perturbations based on Teukolsky's discovery of separable wave equations some ten years later. In the current research climate, where experiments across the globe are preparing for the first detection of gravitational waves, a more complete understanding than concerns just the Weyl curvature is now called for. To understand precisely how comparatively small masses move in response to the gravitational waves they emit, a formalism has been developed based on a description of the whole spacetime metric perturbation in the neighbourhood of the emission region. Presently, such a description is not available for the Kerr geometry. While there does exist a prescription for obtaining metric perturbations once curvature perturbations are known, it has become apparent that there are gaps in that formalism which are still waiting to be filled. The most serious gaps include gauge inflexibility, the inability to include sources-which are essential when the emitting masses are considered-and the failure to describe the l = 0 and 1 perturbation properties. Among these latter properties of the perturbed spacetime, arising from a point mass in orbit, are the perturbed mass and axial component of angular momentum, as well as the very elusive Carter constant for non-axial angular momentum. A status report is given on recent work which begins to repair these deficiencies in our current incomplete description of Kerr metric perturbations

  13. A Validation of Object-Oriented Design Metrics as Quality Indicators

    Science.gov (United States)

    Basili, Victor R.; Briand, Lionel C.; Melo, Walcelio

    1997-01-01

    This paper presents the results of a study in which we empirically investigated the suits of object-oriented (00) design metrics introduced in another work. More specifically, our goal is to assess these metrics as predictors of fault-prone classes and, therefore, determine whether they can be used as early quality indicators. This study is complementary to the work described where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on empirical and quantitative analysis, the advantages and drawbacks of these 00 metrics are discussed. Several of Chidamber and Kamerer's 00 metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle. Also, on our data set, they are better predictors than 'traditional' code metrics, which can only be collected at a later phase of the software development processes.

  14. Research on key technology of the verification system of steel rule based on vision measurement

    Science.gov (United States)

    Jia, Siyuan; Wang, Zhong; Liu, Changjie; Fu, Luhua; Li, Yiming; Lu, Ruijun

    2018-01-01

    The steel rule plays an important role in quantity transmission. However, the traditional verification method of steel rule based on manual operation and reading brings about low precision and low efficiency. A machine vison based verification system of steel rule is designed referring to JJG1-1999-Verificaiton Regulation of Steel Rule [1]. What differentiates this system is that it uses a new calibration method of pixel equivalent and decontaminates the surface of steel rule. Experiments show that these two methods fully meet the requirements of the verification system. Measuring results strongly prove that these methods not only meet the precision of verification regulation, but also improve the reliability and efficiency of the verification system.

  15. Fault Management Metrics

    Science.gov (United States)

    Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig

    2017-01-01

    This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.

  16. Completion of a Dislocated Metric Space

    Directory of Open Access Journals (Sweden)

    P. Sumati Kumari

    2015-01-01

    Full Text Available We provide a construction for the completion of a dislocated metric space (abbreviated d-metric space; we also prove that the completion of the metric associated with a d-metric coincides with the metric associated with the completion of the d-metric.

  17. Development of a clinician reputation metric to identify appropriate problem-medication pairs in a crowdsourced knowledge base.

    Science.gov (United States)

    McCoy, Allison B; Wright, Adam; Rogith, Deevakar; Fathiamini, Safa; Ottenbacher, Allison J; Sittig, Dean F

    2014-04-01

    Correlation of data within electronic health records is necessary for implementation of various clinical decision support functions, including patient summarization. A key type of correlation is linking medications to clinical problems; while some databases of problem-medication links are available, they are not robust and depend on problems and medications being encoded in particular terminologies. Crowdsourcing represents one approach to generating robust knowledge bases across a variety of terminologies, but more sophisticated approaches are necessary to improve accuracy and reduce manual data review requirements. We sought to develop and evaluate a clinician reputation metric to facilitate the identification of appropriate problem-medication pairs through crowdsourcing without requiring extensive manual review. We retrieved medications from our clinical data warehouse that had been prescribed and manually linked to one or more problems by clinicians during e-prescribing between June 1, 2010 and May 31, 2011. We identified measures likely to be associated with the percentage of accurate problem-medication links made by clinicians. Using logistic regression, we created a metric for identifying clinicians who had made greater than or equal to 95% appropriate links. We evaluated the accuracy of the approach by comparing links made by those physicians identified as having appropriate links to a previously manually validated subset of problem-medication pairs. Of 867 clinicians who asserted a total of 237,748 problem-medication links during the study period, 125 had a reputation metric that predicted the percentage of appropriate links greater than or equal to 95%. These clinicians asserted a total of 2464 linked problem-medication pairs (983 distinct pairs). Compared to a previously validated set of problem-medication pairs, the reputation metric achieved a specificity of 99.5% and marginally improved the sensitivity of previously described knowledge bases. A

  18. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

    Directory of Open Access Journals (Sweden)

    Saurav Mallik

    2017-12-01

    Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  19. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

    Science.gov (United States)

    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

    For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  20. Development of soil quality metrics using mycorrhizal fungi

    Energy Technology Data Exchange (ETDEWEB)

    Baar, J.

    2010-07-01

    Based on the Treaty on Biological Diversity of Rio de Janeiro in 1992 for maintaining and increasing biodiversity, several countries have started programmes monitoring soil quality and the above- and below ground biodiversity. Within the European Union, policy makers are working on legislation for soil protection and management. Therefore, indicators are needed to monitor the status of the soils and these indicators reflecting the soil quality, can be integrated in working standards or soil quality metrics. Soil micro-organisms, particularly arbuscular mycorrhizal fungi (AMF), are indicative of soil changes. These soil fungi live in symbiosis with the great majority of plants and are sensitive to changes in the physico-chemical conditions of the soil. The aim of this study was to investigate whether AMF are reliable and sensitive indicators for disturbances in the soils and can be used for the development of soil quality metrics. Also, it was studied whether soil quality metrics based on AMF meet requirements to applicability by users and policy makers. Ecological criterions were set for the development of soil quality metrics for different soils. Multiple root samples containing AMF from various locations in The Netherlands were analyzed. The results of the analyses were related to the defined criterions. This resulted in two soil quality metrics, one for sandy soils and a second one for clay soils, with six different categories ranging from very bad to very good. These soil quality metrics meet the majority of requirements for applicability and are potentially useful for the development of legislations for the protection of soil quality. (Author) 23 refs.

  1. Novel Clustering Method Based on K-Medoids and Mobility Metric

    Directory of Open Access Journals (Sweden)

    Y. Hamzaoui

    2018-06-01

    Full Text Available The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head.

  2. Hedging Rules for Water Supply Reservoir Based on the Model of Simulation and Optimization

    Directory of Open Access Journals (Sweden)

    Yi Ji

    2016-06-01

    Full Text Available This study proposes a hedging rule model which is composed of a two-period reservior operation model considering the damage depth and hedging rule parameter optimization model. The former solves hedging rules based on a given poriod’s water supply weighting factor and carryover storage target, while the latter optimization model is used to optimize the weighting factor and carryover storage target based on the hedging rules. The coupling model gives the optimal poriod’s water supply weighting factor and carryover storage target to guide release. The conclusions achieved from this study as follows: (1 the water supply weighting factor and carryover storage target have a direct impact on the three elements of the hedging rule; (2 parameters can guide reservoirs to supply water reasonably after optimization of the simulation and optimization model; and (3 in order to verify the utility of the hedging rule, the Heiquan reservoir is used as a case study and particle swarm optimization algorithm with a simulation model is adopted for optimizing the parameter. The results show that the proposed hedging rule can improve the operation performances of the water supply reservoir.

  3. Sistem Evaluasi Jamunan Mutu Menggunakan Rule Based System Untuk Monitoring Mutu Perguruan Tinggi

    Directory of Open Access Journals (Sweden)

    Sri Hartono

    2017-05-01

    Full Text Available The needs for continuous quality improvement resulting in the more complex. The research aims to develop system of quality assurance evaluation using rule based system to monitor the quality of higher education. This process of the research begins by documenting the daily activity of study program which consists of lecturer data, research data, service data, staff data, student data, and infrastructure data into a database. The data were evaluated by using rule based system  by adopting rules on quality standards of study program of National Accreditation Board for Higher Education as the knowledge base. Evaluation process was carried out by using the forward chaining methods by matching the existing data to the knowledge base to determine the quality status of each quality standard. While the reccomendation process was carried out by using the backward chaining methods by matching the results of quality status to the desired projection of quality status to determine the nearest target which can be achieved. The result of the research is system of quality assurance evaluation with rule based system that is capable of producing an output system in the form of internal evaluation report and recommendation system that can be used to monitor the quality of higher education.

  4. Metrics with vanishing quantum corrections

    International Nuclear Information System (INIS)

    Coley, A A; Hervik, S; Gibbons, G W; Pope, C N

    2008-01-01

    We investigate solutions of the classical Einstein or supergravity equations that solve any set of quantum corrected Einstein equations in which the Einstein tensor plus a multiple of the metric is equated to a symmetric conserved tensor T μν (g αβ , ∂ τ g αβ , ∂ τ ∂ σ g αβ , ...,) constructed from sums of terms, the involving contractions of the metric and powers of arbitrary covariant derivatives of the curvature tensor. A classical solution, such as an Einstein metric, is called universal if, when evaluated on that Einstein metric, T μν is a multiple of the metric. A Ricci flat classical solution is called strongly universal if, when evaluated on that Ricci flat metric, T μν vanishes. It is well known that pp-waves in four spacetime dimensions are strongly universal. We focus attention on a natural generalization; Einstein metrics with holonomy Sim(n - 2) in which all scalar invariants are zero or constant. In four dimensions we demonstrate that the generalized Ghanam-Thompson metric is weakly universal and that the Goldberg-Kerr metric is strongly universal; indeed, we show that universality extends to all four-dimensional Sim(2) Einstein metrics. We also discuss generalizations to higher dimensions

  5. SOCIAL METRICS APPLIED TO SMART TOURISM

    Directory of Open Access Journals (Sweden)

    O. Cervantes

    2016-09-01

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

  6. Social Metrics Applied to Smart Tourism

    Science.gov (United States)

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

    2016-09-01

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

  7. Remarks on G-Metric Spaces

    Directory of Open Access Journals (Sweden)

    Bessem Samet

    2013-01-01

    Full Text Available In 2005, Mustafa and Sims (2006 introduced and studied a new class of generalized metric spaces, which are called G-metric spaces, as a generalization of metric spaces. We establish some useful propositions to show that many fixed point theorems on (nonsymmetric G-metric spaces given recently by many authors follow directly from well-known theorems on metric spaces. Our technique can be easily extended to other results as shown in application.

  8. A software quality model and metrics for risk assessment

    Science.gov (United States)

    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.

  9. Crowdsourcing metrics of digital collections

    Directory of Open Access Journals (Sweden)

    Tuula Pääkkönen

    2015-12-01

    Full Text Available In the National Library of Finland (NLF there are millions of digitized newspaper and journal pages, which are openly available via the public website  http://digi.kansalliskirjasto.fi. To serve users better, last year the front end was completely overhauled with its main aim in crowdsourcing features, e.g., by giving end-users the opportunity to create digital clippings and a personal scrapbook from the digital collections. But how can you know whether crowdsourcing has had an impact? How much crowdsourcing functionalities have been used so far? Did crowdsourcing work? In this paper the statistics and metrics of a recent crowdsourcing effort are analysed across the different digitized material types (newspapers, journals, ephemera. The subjects, categories and keywords given by the users are analysed to see which topics are the most appealing. Some notable public uses of the crowdsourced article clippings are highlighted. These metrics give us indications on how the end-users, based on their own interests, are investigating and using the digital collections. Therefore, the suggested metrics illustrate the versatility of the information needs of the users, varying from citizen science to research purposes. By analysing the user patterns, we can respond to the new needs of the users by making minor changes to accommodate the most active participants, while still making the service more approachable for those who are trying out the functionalities for the first time. Participation in the clippings and annotations can enrich the materials in unexpected ways and can possibly pave the way for opportunities of using crowdsourcing more also in research contexts. This creates more opportunities for the goals of open science since source data becomes ­available, making it possible for researchers to reach out to the general public for help. In the long term, utilizing, for example, text mining methods can allow these different end-user segments to

  10. Adaptive metric learning with deep neural networks for video-based facial expression recognition

    Science.gov (United States)

    Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

    2018-01-01

    Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

  11. Resource-level QoS metric for CPU-based guarantees in cloud providers

    OpenAIRE

    Goiri Presa, Íñigo; Julià Massó, Ferran; Fitó, Josep Oriol; Macías Lloret, Mario; Guitart Fernández, Jordi

    2010-01-01

    Success of Cloud computing requires that both customers and providers can be confident that signed Service Level Agreements (SLA) are supporting their respective business activities to their best extent. Currently used SLAs fail in providing such confidence, especially when providers outsource resources to other providers. These resource providers typically support very simple metrics, or metrics that hinder an efficient exploitation of their resources. In this paper, we propose a re...

  12. Accuracy and precision in the calculation of phenology metrics

    DEFF Research Database (Denmark)

    Ferreira, Ana Sofia; Visser, Andre; MacKenzie, Brian

    2014-01-01

    a phenology metric is first determined from a noise- and gap-free time series, and again once it has been modified. We show that precision is a greater concern than accuracy for many of these metrics, an important point that has been hereto overlooked in the literature. The variability in precision between...... phenology metrics is substantial, but it can be improved by the use of preprocessing techniques (e.g., gap-filling or smoothing). Furthermore, there are important differences in the inherent variability of the metrics that may be crucial in the interpretation of studies based upon them. Of the considered......Phytoplankton phenology (the timing of seasonal events) is a commonly used indicator for evaluating responses of marine ecosystems to climate change. However, phenological metrics are vulnerable to observation-(bloom amplitude, missing data, and observational noise) and analysis-related (temporal...

  13. Metric-adjusted skew information

    DEFF Research Database (Denmark)

    Liang, Cai; Hansen, Frank

    2010-01-01

    on a bipartite system and proved superadditivity of the Wigner-Yanase-Dyson skew informations for such states. We extend this result to the general metric-adjusted skew information. We finally show that a recently introduced extension to parameter values 1 ...We give a truly elementary proof of the convexity of metric-adjusted skew information following an idea of Effros. We extend earlier results of weak forms of superadditivity to general metric-adjusted skew information. Recently, Luo and Zhang introduced the notion of semi-quantum states...... of (unbounded) metric-adjusted skew information....

  14. Associations between rule-based parenting practices and child screen viewing: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Joanna M. Kesten

    2015-01-01

    Conclusions: Limit setting is associated with greater SV. Collaborative rule setting may be effective for managing boys' game-console use. More research is needed to understand rule-based parenting practices.

  15. The metrics and correlates of physician migration from Africa

    Directory of Open Access Journals (Sweden)

    Arah Onyebuchi A

    2007-05-01

    Full Text Available Abstract Background Physician migration from poor to rich countries is considered an important contributor to the growing health workforce crisis in the developing world. This is particularly true for Africa. The perceived magnitude of such migration for each source country might, however, depend on the choice of metrics used in the analysis. This study examined the influence of choice of migration metrics on the rankings of African countries that suffered the most physician migration, and investigated the correlates of physician migration. Methods Ranking and correlational analyses were conducted on African physician migration data adjusted for bilateral net flows, and supplemented with developmental, economic and health system data. The setting was the 53 African birth countries of African-born physicians working in nine wealthier destination countries. Three metrics of physician migration were used: total number of physician émigrés; emigration fraction defined as the proportion of the potential physician pool working in destination countries; and physician migration density defined as the number of physician émigrés per 1000 population of the African source country. Results Rankings based on any of the migration metrics differed substantially from those based on the other two metrics. Although the emigration fraction and physician migration density metrics gave proportionality to the migration crisis, only the latter was consistently associated with source countries' workforce capacity, health, health spending, economic and development characteristics. As such, higher physician migration density was seen among African countries with relatively higher health workforce capacity (0.401 ≤ r ≤ 0.694, p ≤ 0.011, health status, health spending, and development. Conclusion The perceived magnitude of physician migration is sensitive to the choice of metrics. Complementing the emigration fraction, the physician migration density is a metric

  16. Proof of Kochen–Specker Theorem: Conversion of Product Rule to Sum Rule

    International Nuclear Information System (INIS)

    Toh, S.P.; Zainuddin, Hishamuddin

    2009-01-01

    Valuation functions of observables in quantum mechanics are often expected to obey two constraints called the sum rule and product rule. However, the Kochen–Specker (KS) theorem shows that for a Hilbert space of quantum mechanics of dimension d ≤ 3, these constraints contradict individually with the assumption of value definiteness. The two rules are not irrelated and Peres [Found. Phys. 26 (1996) 807] has conceived a method of converting the product rule into a sum rule for the case of two qubits. Here we apply this method to a proof provided by Mermin based on the product rule for a three-qubit system involving nine operators. We provide the conversion of this proof to one based on sum rule involving ten operators. (general)

  17. Flavours of XChange, a Rule-Based Reactive Language for the (Semantic) Web

    OpenAIRE

    Bailey, James; Bry, François; Eckert, Michael; Patrânjan, Paula Lavinia

    2005-01-01

    This article introduces XChange, a rule-based reactive language for the Web. Stressing application scenarios, it first argues that high-level reactive languages are needed for bothWeb and SemanticWeb applications. Then, it discusses technologies and paradigms relevant to high-level reactive languages for the (Semantic) Web. Finally, it presents the Event-Condition-Action rules of XChange.

  18. A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun

    2016-01-01

    to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema......Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies...

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

    Science.gov (United States)

    Post, J. V.

    1981-01-01

    Software quality metrics was extended to cover distributed computer systems. Emphasis is placed on studying embedded computer systems and on viewing them within a system life cycle. The hierarchy of quality factors, criteria, and metrics was maintained. New software quality factors were added, including survivability, expandability, and evolvability.

  20. Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment

    Science.gov (United States)

    Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.

    2017-12-01

    We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.

  1. Evaluation of Subjective and Objective Performance Metrics for Haptically Controlled Robotic Systems

    Directory of Open Access Journals (Sweden)

    Cong Dung Pham

    2014-07-01

    Full Text Available This paper studies in detail how different evaluation methods perform when it comes to describing the performance of haptically controlled mobile manipulators. Particularly, we investigate how well subjective metrics perform compared to objective metrics. To find the best metrics to describe the performance of a control scheme is challenging when human operators are involved; how the user perceives the performance of the controller does not necessarily correspond to the directly measurable metrics normally used in controller evaluation. It is therefore important to study whether there is any correspondence between how the user perceives the performance of a controller, and how it performs in terms of directly measurable metrics such as the time used to perform a task, number of errors, accuracy, and so on. To perform these tests we choose a system that consists of a mobile manipulator that is controlled by an operator through a haptic device. This is a good system for studying different performance metrics as the performance can be determined by subjective metrics based on feedback from the users, and also as objective and directly measurable metrics. The system consists of a robotic arm which provides for interaction and manipulation, which is mounted on a mobile base which extends the workspace of the arm. The operator thus needs to perform both interaction and locomotion using a single haptic device. While the position of the on-board camera is determined by the base motion, the principal control objective is the motion of the manipulator arm. This calls for intelligent control allocation between the base and the manipulator arm in order to obtain intuitive control of both the camera and the arm. We implement three different approaches to the control allocation problem, i.e., whether the vehicle or manipulator arm actuation is applied to generate the desired motion. The performance of the different control schemes is evaluated, and our

  2. The metric system: An introduction

    Science.gov (United States)

    Lumley, Susan M.

    On 13 Jul. 1992, Deputy Director Duane Sewell restated the Laboratory's policy on conversion to the metric system which was established in 1974. Sewell's memo announced the Laboratory's intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory's conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on 25 Jul. 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation's conversion to the metric system. The second part of this report is on applying the metric system.

  3. The metric system: An introduction

    Energy Technology Data Exchange (ETDEWEB)

    Lumley, S.M.

    1995-05-01

    On July 13, 1992, Deputy Director Duane Sewell restated the Laboratory`s policy on conversion to the metric system which was established in 1974. Sewell`s memo announced the Laboratory`s intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory`s conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on July 25, 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation`s conversion to the metric system. The second part of this report is on applying the metric system.

  4. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  5. Attack-Resistant Trust Metrics

    Science.gov (United States)

    Levien, Raph

    The Internet is an amazingly powerful tool for connecting people together, unmatched in human history. Yet, with that power comes great potential for spam and abuse. Trust metrics are an attempt to compute the set of which people are trustworthy and which are likely attackers. This chapter presents two specific trust metrics developed and deployed on the Advogato Website, which is a community blog for free software developers. This real-world experience demonstrates that the trust metrics fulfilled their goals, but that for good results, it is important to match the assumptions of the abstract trust metric computation to the real-world implementation.

  6. A family of metric gravities

    Science.gov (United States)

    Shuler, Robert

    2018-04-01

    The goal of this paper is to take a completely fresh approach to metric gravity, in which the metric principle is strictly adhered to but its properties in local space-time are derived from conservation principles, not inferred from a global field equation. The global field strength variation then gains some flexibility, but only in the regime of very strong fields (2nd-order terms) whose measurement is now being contemplated. So doing provides a family of similar gravities, differing only in strong fields, which could be developed into meaningful verification targets for strong fields after the manner in which far-field variations were used in the 20th century. General Relativity (GR) is shown to be a member of the family and this is demonstrated by deriving the Schwarzschild metric exactly from a suitable field strength assumption. The method of doing so is interesting in itself because it involves only one differential equation rather than the usual four. Exact static symmetric field solutions are also given for one pedagogical alternative based on potential, and one theoretical alternative based on inertia, and the prospects of experimentally differentiating these are analyzed. Whether the method overturns the conventional wisdom that GR is the only metric theory of gravity and that alternatives must introduce additional interactions and fields is somewhat semantical, depending on whether one views the field strength assumption as a field and whether the assumption that produces GR is considered unique in some way. It is of course possible to have other fields, and the local space-time principle can be applied to field gravities which usually are weak-field approximations having only time dilation, giving them the spatial factor and promoting them to full metric theories. Though usually pedagogical, some of them are interesting from a quantum gravity perspective. Cases are noted where mass measurement errors, or distributions of dark matter, can cause one

  7. Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

    Science.gov (United States)

    Dai, Guoxian; Xie, Jin; Fang, Yi

    2018-07-01

    How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

  8. Towards a framework for threaded inference in rule-based systems

    Directory of Open Access Journals (Sweden)

    Luis Casillas Santillan

    2013-11-01

    Full Text Available nformation and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing with knowledge is turning the axis for organizations in the new economy. One of the choices to gather the goal of knowledge managing is the use of rule-based systems. This kind of approach is the new chance for expert-systems’ technology. Modern languages and cheap computing allow the implementation of concurrent systems for dealing huge volumes of information in organizations. The present work is aimed at proposing the use of contemporary programming elements, as easy to exploit threading, when implementing rule-based treatment over huge data volumes.

  9. Systematic construction of qualitative physics-based rules for process diagnostics

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.

    1995-01-01

    A novel first-principles-based expert system is proposed for on-line detection and identification of faulty component candidates during incipient off-normal process operations. The system performs function-oriented diagnostics and can be reused for diagnosing single-component failures in different processes and different plants through the provision of the appropriate process schematics information. The function-oriented and process-independent diagnostic features of the proposed expert system are achieved by constructing a knowledge base containing three distinct types of information, qualitative balance equation rules, functional classification of process components, and the process piping and instrumentation diagram. The various types of qualitative balance equation rules for processes utilizing single-phase liquids are derived and their usage is illustrated through simulation results of a realistic process in a nuclear power plant

  10. Symmetries of the dual metrics

    International Nuclear Information System (INIS)

    Baleanu, D.

    1998-01-01

    The geometric duality between the metric g μν and a Killing tensor K μν is studied. The conditions were found when the symmetries of the metric g μν and the dual metric K μν are the same. Dual spinning space was constructed without introduction of torsion. The general results are applied to the case of Kerr-Newmann metric

  11. Rule-based Information Integration

    NARCIS (Netherlands)

    de Keijzer, Ander; van Keulen, Maurice

    2005-01-01

    In this report, we show the process of information integration. We specifically discuss the language used for integration. We show that integration consists of two phases, the schema mapping phase and the data integration phase. We formally define transformation rules, conversion, evolution and

  12. Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

    Science.gov (United States)

    Idris, Husni; Shen, Ni; Wing, David J.

    2011-01-01

    The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

  13. A condition metric for Eucalyptus woodland derived from expert evaluations.

    Science.gov (United States)

    Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D

    2018-02-01

    The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.

  14. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  15. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin

    2014-01-01

    conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...... and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system....

  16. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

    Directory of Open Access Journals (Sweden)

    Bernardin Keni

    2008-01-01

    Full Text Available Abstract Simultaneous tracking of multiple persons in real-world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. Recently, there has been a growing interest in organizing systematic evaluations to compare the various techniques. Unfortunately, the lack of common metrics for measuring the performance of multiple object trackers still makes it hard to compare their results. In this work, we introduce two intuitive and general metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently label objects over time. These metrics have been extensively used in two large-scale international evaluations, the 2006 and 2007 CLEAR evaluations, to measure and compare the performance of multiple object trackers for a wide variety of tracking tasks. Selected performance results are presented and the advantages and drawbacks of the presented metrics are discussed based on the experience gained during the evaluations.

  17. Assessing Software Quality Through Visualised Cohesion Metrics

    Directory of Open Access Journals (Sweden)

    Timothy Shih

    2001-05-01

    Full Text Available Cohesion is one of the most important factors for software quality as well as maintainability, reliability and reusability. Module cohesion is defined as a quality attribute that seeks for measuring the singleness of the purpose of a module. The module of poor quality can be a serious obstacle to the system quality. In order to design a good software quality, software managers and engineers need to introduce cohesion metrics to measure and produce desirable software. A highly cohesion software is thought to be a desirable constructing. In this paper, we propose a function-oriented cohesion metrics based on the analysis of live variables, live span and the visualization of processing element dependency graph. We give six typical cohesion examples to be measured as our experiments and justification. Therefore, a well-defined, well-normalized, well-visualized and well-experimented cohesion metrics is proposed to indicate and thus enhance software cohesion strength. Furthermore, this cohesion metrics can be easily incorporated with software CASE tool to help software engineers to improve software quality.

  18. Overview of journal metrics

    Directory of Open Access Journals (Sweden)

    Kihong Kim

    2018-02-01

    Full Text Available Various kinds of metrics used for the quantitative evaluation of scholarly journals are reviewed. The impact factor and related metrics including the immediacy index and the aggregate impact factor, which are provided by the Journal Citation Reports, are explained in detail. The Eigenfactor score and the article influence score are also reviewed. In addition, journal metrics such as CiteScore, Source Normalized Impact per Paper, SCImago Journal Rank, h-index, and g-index are discussed. Limitations and problems that these metrics have are pointed out. We should be cautious to rely on those quantitative measures too much when we evaluate journals or researchers.

  19. ABOUT CLINICAL EXPERT SYSTEM BASED ON RULES USING DATA MINING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. P. Martsenyuk

    2015-05-01

    Full Text Available In the work the topics of software implementation of rule induction method based on sequential covering algorithm are considered. Such approach allows us to develop clinical decision support system. The project is implemented within Netbeans IDE based on Java-classes.

  20. A Combinatorial Reasoning Mechanism with Topological and Metric Relations for Change Detection in River Planforms: An Application to GlobeLand30’s Water Bodies

    Directory of Open Access Journals (Sweden)

    Liang Leng

    2017-01-01

    Full Text Available Changes in river plane shapes are called river planform changes (RPCs. Such changes can impact sustainable human development (e.g., human habitations, industrial and agricultural development, and national border security. RPCs can be identified through field surveys—a method that is highly precise but time-consuming, or through remote sensing (RS and geographic information system (GIS, which are less precise but more efficient. Previous studies that have addressed RPCs often used RS, GIS, or digital elevation models (DEMs and focused on only one or a few rivers in specific areas with the goal of identifying the reasons underlying these changes. In contrast, in this paper, we developed a combinatorial reasoning mechanism based on topological and metric relations that can be used to classify RPCs. This approach does not require DEMs and can eliminate most false-change information caused by varying river water levels. First, we present GIS models of river planforms based on their natural properties and, then, modify these models into simple GIS river planform models (SGRPMs using straight lines rather than common lines to facilitate computational and human understanding. Second, we used double straight line 4-intersection models (DSL4IMs and intersection and difference models (IDMs of the regions to represent the topological relations between the SGRPMs and used double-start-point 8-distance models (DS8DMs to express the metric relations between the SGRPMs. Then, we combined topological and metric relations to analyse the changes in the SGRPMs. Finally, to compensate for the complexity of common river planforms in nature, we proposed three segmentation rules to turn common river planforms into SGRPMs and used combinatorial reasoning mechanism tables (CRMTs to describe the spatial relations among different river planforms. Based on our method, users can describe common river planforms and their changes in detail and confidently reject false

  1. Fisher information metrics for binary classifier evaluation and training

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Different evaluation metrics for binary classifiers are appropriate to different scientific domains and even to different problems within the same domain. This presentation focuses on the optimisation of event selection to minimise statistical errors in HEP parameter estimation, a problem that is best analysed in terms of the maximisation of Fisher information about the measured parameters. After describing a general formalism to derive evaluation metrics based on Fisher information, three more specific metrics are introduced for the measurements of signal cross sections in counting experiments (FIP1) or distribution fits (FIP2) and for the measurements of other parameters from distribution fits (FIP3). The FIP2 metric is particularly interesting because it can be derived from any ROC curve, provided that prevalence is also known. In addition to its relation to measurement errors when used as an evaluation criterion (which makes it more interesting that the ROC AUC), a further advantage of the FIP2 metric is ...

  2. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    Science.gov (United States)

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  3. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

    Science.gov (United States)

    Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

    2014-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

  4. A Belief Rule-Based Expert System to Assess Bronchiolitis Suspicion from Signs and Symptoms Under Uncertainty

    DEFF Research Database (Denmark)

    Karim, Rezuan; Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin

    2017-01-01

    developed generic belief rule-based inference methodology by using evidential reasoning (RIMER) acts as the inference engine of this BRBES while belief rule base as the knowledge representation schema. The knowledge base of the system is constructed by using real patient data and expert opinion from...

  5. Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

    OpenAIRE

    Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

    2017-01-01

    In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

  6. Estimation of Tree Cover in an Agricultural Parkland of Senegal Using Rule-Based Regression Tree Modeling

    Directory of Open Access Journals (Sweden)

    Stefanie M. Herrmann

    2013-10-01

    Full Text Available Field trees are an integral part of the farmed parkland landscape in West Africa and provide multiple benefits to the local environment and livelihoods. While field trees have received increasing interest in the context of strengthening resilience to climate variability and change, the actual extent of farmed parkland and spatial patterns of tree cover are largely unknown. We used the rule-based predictive modeling tool Cubist® to estimate field tree cover in the west-central agricultural region of Senegal. A collection of rules and associated multiple linear regression models was constructed from (1 a reference dataset of percent tree cover derived from very high spatial resolution data (2 m Orbview as the dependent variable, and (2 ten years of 10-day 250 m Moderate Resolution Imaging Spectrometer (MODIS Normalized Difference Vegetation Index (NDVI composites and derived phenological metrics as independent variables. Correlation coefficients between modeled and reference percent tree cover of 0.88 and 0.77 were achieved for training and validation data respectively, with absolute mean errors of 1.07 and 1.03 percent tree cover. The resulting map shows a west-east gradient from high tree cover in the peri-urban areas of horticulture and arboriculture to low tree cover in the more sparsely populated eastern part of the study area. A comparison of current (2000s tree cover along this gradient with historic cover as seen on Corona images reveals dynamics of change but also areas of remarkable stability of field tree cover since 1968. The proposed modeling approach can help to identify locations of high and low tree cover in dryland environments and guide ground studies and management interventions aimed at promoting the integration of field trees in agricultural systems.

  7. Holographic Spherically Symmetric Metrics

    Science.gov (United States)

    Petri, Michael

    The holographic principle (HP) conjectures, that the maximum number of degrees of freedom of any realistic physical system is proportional to the system's boundary area. The HP has its roots in the study of black holes. It has recently been applied to cosmological solutions. In this article we apply the HP to spherically symmetric static space-times. We find that any regular spherically symmetric object saturating the HP is subject to tight constraints on the (interior) metric, energy-density, temperature and entropy-density. Whenever gravity can be described by a metric theory, gravity is macroscopically scale invariant and the laws of thermodynamics hold locally and globally, the (interior) metric of a regular holographic object is uniquely determined up to a constant factor and the interior matter-state must follow well defined scaling relations. When the metric theory of gravity is general relativity, the interior matter has an overall string equation of state (EOS) and a unique total energy-density. Thus the holographic metric derived in this article can serve as simple interior 4D realization of Mathur's string fuzzball proposal. Some properties of the holographic metric and its possible experimental verification are discussed. The geodesics of the holographic metric describe an isotropically expanding (or contracting) universe with a nearly homogeneous matter-distribution within the local Hubble volume. Due to the overall string EOS the active gravitational mass-density is zero, resulting in a coasting expansion with Ht = 1, which is compatible with the recent GRB-data.

  8. A high-level language for rule-based modelling.

    Science.gov (United States)

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

  9. Critical thinking skills in nursing students: comparison of simulation-based performance with metrics

    Science.gov (United States)

    Fero, Laura J.; O’Donnell, John M.; Zullo, Thomas G.; Dabbs, Annette DeVito; Kitutu, Julius; Samosky, Joseph T.; Hoffman, Leslie A.

    2018-01-01

    Aim This paper is a report of an examination of the relationship between metrics of critical thinking skills and performance in simulated clinical scenarios. Background Paper and pencil assessments are commonly used to assess critical thinking but may not reflect simulated performance. Methods In 2007, a convenience sample of 36 nursing students participated in measurement of critical thinking skills and simulation-based performance using videotaped vignettes, high-fidelity human simulation, the California Critical Thinking Disposition Inventory and California Critical Thinking Skills Test. Simulation- based performance was rated as ‘meeting’ or ‘not meeting’ overall expectations. Test scores were categorized as strong, average, or weak. Results Most (75·0%) students did not meet overall performance expectations using videotaped vignettes or high-fidelity human simulation; most difficulty related to problem recognition and reporting findings to the physician. There was no difference between overall performance based on method of assessment (P = 0·277). More students met subcategory expectations for initiating nursing interventions (P ≤ 0·001) using high-fidelity human simulation. The relationship between video-taped vignette performance and critical thinking disposition or skills scores was not statistically significant, except for problem recognition and overall critical thinking skills scores (Cramer’s V = 0·444, P = 0·029). There was a statistically significant relationship between overall high-fidelity human simulation performance and overall critical thinking disposition scores (Cramer’s V = 0·413, P = 0·047). Conclusion Students’ performance reflected difficulty meeting expectations in simulated clinical scenarios. High-fidelity human simulation performance appeared to approximate scores on metrics of critical thinking best. Further research is needed to determine if simulation-based performance correlates with critical thinking skills

  10. Critical thinking skills in nursing students: comparison of simulation-based performance with metrics.

    Science.gov (United States)

    Fero, Laura J; O'Donnell, John M; Zullo, Thomas G; Dabbs, Annette DeVito; Kitutu, Julius; Samosky, Joseph T; Hoffman, Leslie A

    2010-10-01

    This paper is a report of an examination of the relationship between metrics of critical thinking skills and performance in simulated clinical scenarios. Paper and pencil assessments are commonly used to assess critical thinking but may not reflect simulated performance. In 2007, a convenience sample of 36 nursing students participated in measurement of critical thinking skills and simulation-based performance using videotaped vignettes, high-fidelity human simulation, the California Critical Thinking Disposition Inventory and California Critical Thinking Skills Test. Simulation-based performance was rated as 'meeting' or 'not meeting' overall expectations. Test scores were categorized as strong, average, or weak. Most (75.0%) students did not meet overall performance expectations using videotaped vignettes or high-fidelity human simulation; most difficulty related to problem recognition and reporting findings to the physician. There was no difference between overall performance based on method of assessment (P = 0.277). More students met subcategory expectations for initiating nursing interventions (P ≤ 0.001) using high-fidelity human simulation. The relationship between videotaped vignette performance and critical thinking disposition or skills scores was not statistically significant, except for problem recognition and overall critical thinking skills scores (Cramer's V = 0.444, P = 0.029). There was a statistically significant relationship between overall high-fidelity human simulation performance and overall critical thinking disposition scores (Cramer's V = 0.413, P = 0.047). Students' performance reflected difficulty meeting expectations in simulated clinical scenarios. High-fidelity human simulation performance appeared to approximate scores on metrics of critical thinking best. Further research is needed to determine if simulation-based performance correlates with critical thinking skills in the clinical setting. © 2010 The Authors. Journal of Advanced

  11. SPATKIN: a simulator for rule-based modeling of biomolecular site dynamics on surfaces.

    Science.gov (United States)

    Kochanczyk, Marek; Hlavacek, William S; Lipniacki, Tomasz

    2017-11-15

    Rule-based modeling is a powerful approach for studying biomolecular site dynamics. Here, we present SPATKIN, a general-purpose simulator for rule-based modeling in two spatial dimensions. The simulation algorithm is a lattice-based method that tracks Brownian motion of individual molecules and the stochastic firing of rule-defined reaction events. Because rules are used as event generators, the algorithm is network-free, meaning that it does not require to generate the complete reaction network implied by rules prior to simulation. In a simulation, each molecule (or complex of molecules) is taken to occupy a single lattice site that cannot be shared with another molecule (or complex). SPATKIN is capable of simulating a wide array of membrane-associated processes, including adsorption, desorption and crowding. Models are specified using an extension of the BioNetGen language, which allows to account for spatial features of the simulated process. The C ++ source code for SPATKIN is distributed freely under the terms of the GNU GPLv3 license. The source code can be compiled for execution on popular platforms (Windows, Mac and Linux). An installer for 64-bit Windows and a macOS app are available. The source code and precompiled binaries are available at the SPATKIN Web site (http://pmbm.ippt.pan.pl/software/spatkin). spatkin.simulator@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

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

  13. On the effects of adaptive reservoir operating rules in hydrological physically-based models

    Science.gov (United States)

    Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo

    2017-04-01

    Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling

  14. A rule-based computer control system for PBX-M neutral beams

    International Nuclear Information System (INIS)

    Frank, K.T.; Kozub, T.A.; Kugel, H.W.

    1987-01-01

    The Princeton Beta Experiment (PBX) neutral beams have been routinely operated under automatic computer control. A major upgrade of the computer configuration was undertaken to coincide with the PBX machine modification. The primary tasks included in the computer control system are data acquisition, waveform reduction, automatic control and data storage. The portion of the system which will remain intact is the rule-based approach to automatic control. Increased computational and storage capability will allow the expansion of the knowledge base previously used. The hardware configuration supported by the PBX Neutral Beam (XNB) software includes a dedicated Microvax with five CAMAC crates and four process controllers. The control algorithms are rule-based and goal-driven. The automatic control system raises ion source electrical parameters to selected energy goals and maintains these levels until new goals are requested or faults are detected

  15. Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory.

    Science.gov (United States)

    Kumar, B Vinodh; Mohan, Thuthi

    2018-01-01

    Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of sigma level. For all analytes sigma level, the quality goal index (QGI) was 1.2 indicated inaccuracy. This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes.

  16. Method for automatic control rod operation using rule-based control

    International Nuclear Information System (INIS)

    Kinoshita, Mitsuo; Yamada, Naoyuki; Kiguchi, Takashi

    1988-01-01

    An automatic control rod operation method using rule-based control is proposed. Its features are as follows: (1) a production system to recognize plant events, determine control actions and realize fast inference (fast selection of a suitable production rule), (2) use of the fuzzy control technique to determine quantitative control variables. The method's performance was evaluated by simulation tests on automatic control rod operation at a BWR plant start-up. The results were as follows; (1) The performance which is related to stabilization of controlled variables and time required for reactor start-up, was superior to that of other methods such as PID control and program control methods, (2) the process time to select and interpret the suitable production rule, which was the same as required for event recognition or determination of control action, was short (below 1 s) enough for real time control. The results showed that the method is effective for automatic control rod operation. (author)

  17. Landscape metrics for three-dimension urban pattern recognition

    Science.gov (United States)

    Liu, M.; Hu, Y.; Zhang, W.; Li, C.

    2017-12-01

    Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.

  18. Evaluation metrics for biostatistical and epidemiological collaborations.

    Science.gov (United States)

    Rubio, Doris McGartland; Del Junco, Deborah J; Bhore, Rafia; Lindsell, Christopher J; Oster, Robert A; Wittkowski, Knut M; Welty, Leah J; Li, Yi-Ju; Demets, Dave

    2011-10-15

    Increasing demands for evidence-based medicine and for the translation of biomedical research into individual and public health benefit have been accompanied by the proliferation of special units that offer expertise in biostatistics, epidemiology, and research design (BERD) within academic health centers. Objective metrics that can be used to evaluate, track, and improve the performance of these BERD units are critical to their successful establishment and sustainable future. To develop a set of reliable but versatile metrics that can be adapted easily to different environments and evolving needs, we consulted with members of BERD units from the consortium of academic health centers funded by the Clinical and Translational Science Award Program of the National Institutes of Health. Through a systematic process of consensus building and document drafting, we formulated metrics that covered the three identified domains of BERD practices: the development and maintenance of collaborations with clinical and translational science investigators, the application of BERD-related methods to clinical and translational research, and the discovery of novel BERD-related methodologies. In this article, we describe the set of metrics and advocate their use for evaluating BERD practices. The routine application, comparison of findings across diverse BERD units, and ongoing refinement of the metrics will identify trends, facilitate meaningful changes, and ultimately enhance the contribution of BERD activities to biomedical research. Copyright © 2011 John Wiley & Sons, Ltd.

  19. Left-invariant Einstein metrics on S3 ×S3

    Science.gov (United States)

    Belgun, Florin; Cortés, Vicente; Haupt, Alexander S.; Lindemann, David

    2018-06-01

    The classification of homogeneous compact Einstein manifolds in dimension six is an open problem. We consider the remaining open case, namely left-invariant Einstein metrics g on G = SU(2) × SU(2) =S3 ×S3. Einstein metrics are critical points of the total scalar curvature functional for fixed volume. The scalar curvature S of a left-invariant metric g is constant and can be expressed as a rational function in the parameters determining the metric. The critical points of S, subject to the volume constraint, are given by the zero locus of a system of polynomials in the parameters. In general, however, the determination of the zero locus is apparently out of reach. Instead, we consider the case where the isotropy group K of g in the group of motions is non-trivial. When K ≇Z2 we prove that the Einstein metrics on G are given by (up to homothety) either the standard metric or the nearly Kähler metric, based on representation-theoretic arguments and computer algebra. For the remaining case K ≅Z2 we present partial results.

  20. Automatic detection of esophageal pressure events. Is there an alternative to rule-based criteria?

    DEFF Research Database (Denmark)

    Kruse-Andersen, S; Rütz, K; Kolberg, Jens Godsk

    1995-01-01

    of relevant pressure peaks at the various recording levels. Until now, this selection has been performed entirely by rule-based systems, requiring each pressure deflection to fit within predefined rigid numerical limits in order to be detected. However, due to great variations in the shapes of the pressure...... curves generated by muscular contractions, rule-based criteria do not always select the pressure events most relevant for further analysis. We have therefore been searching for a new concept for automatic event recognition. The present study describes a new system, based on the method of neurocomputing.......79-0.99 and accuracies of 0.89-0.98, depending on the recording level within the esophageal lumen. The neural networks often recognized peaks that clearly represented true contractions but that had been rejected by a rule-based system. We conclude that neural networks have potentials for automatic detections...

  1. Integration of object-oriented knowledge representation with the CLIPS rule based system

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

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

    Directory of Open Access Journals (Sweden)

    S. Ilgin Guler

    2016-08-01

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

  3. Eckart frame vibration-rotation Hamiltonians: Contravariant metric tensor

    International Nuclear Information System (INIS)

    Pesonen, Janne

    2014-01-01

    Eckart frame is a unique embedding in the theory of molecular vibrations and rotations. It is defined by the condition that the Coriolis coupling of the reference structure of the molecule is zero for every choice of the shape coordinates. It is far from trivial to set up Eckart kinetic energy operators (KEOs), when the shape of the molecule is described by curvilinear coordinates. In order to obtain the KEO, one needs to set up the corresponding contravariant metric tensor. Here, I derive explicitly the Eckart frame rotational measuring vectors. Their inner products with themselves give the rotational elements, and their inner products with the vibrational measuring vectors (which, in the absence of constraints, are the mass-weighted gradients of the shape coordinates) give the Coriolis elements of the contravariant metric tensor. The vibrational elements are given as the inner products of the vibrational measuring vectors with themselves, and these elements do not depend on the choice of the body-frame. The present approach has the advantage that it does not depend on any particular choice of the shape coordinates, but it can be used in conjunction with all shape coordinates. Furthermore, it does not involve evaluation of covariant metric tensors, chain rules of derivation, or numerical differentiation, and it can be easily modified if there are constraints on the shape of the molecule. Both the planar and non-planar reference structures are accounted for. The present method is particular suitable for numerical work. Its computational implementation is outlined in an example, where I discuss how to evaluate vibration-rotation energies and eigenfunctions of a general N-atomic molecule, the shape of which is described by a set of local polyspherical coordinates

  4. Metric regularity and subdifferential calculus

    International Nuclear Information System (INIS)

    Ioffe, A D

    2000-01-01

    The theory of metric regularity is an extension of two classical results: the Lyusternik tangent space theorem and the Graves surjection theorem. Developments in non-smooth analysis in the 1980s and 1990s paved the way for a number of far-reaching extensions of these results. It was also well understood that the phenomena behind the results are of metric origin, not connected with any linear structure. At the same time it became clear that some basic hypotheses of the subdifferential calculus are closely connected with the metric regularity of certain set-valued maps. The survey is devoted to the metric theory of metric regularity and its connection with subdifferential calculus in Banach spaces

  5. Uncertain rule-based fuzzy systems introduction and new directions

    CERN Document Server

    Mendel, Jerry M

    2017-01-01

    The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy se...

  6. Context-dependent ATC complexity metric

    NARCIS (Netherlands)

    Mercado Velasco, G.A.; Borst, C.

    2015-01-01

    Several studies have investigated Air Traffic Control (ATC) complexity metrics in a search for a metric that could best capture workload. These studies have shown how daunting the search for a universal workload metric (one that could be applied in different contexts: sectors, traffic patterns,

  7. Rough set and rule-based multicriteria decision aiding

    Directory of Open Access Journals (Sweden)

    Roman Slowinski

    2012-08-01

    Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

  8. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  9. Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

    Science.gov (United States)

    Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

    2015-12-01

    Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

  10. Evaluation of Rule-based Modularization in Model Transformation Languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the base of the relations between source and target metamodels and on the base of generic transformation

  11. DLA Energy Biofuel Feedstock Metrics Study

    Science.gov (United States)

    2012-12-11

    moderately/highly in- vasive  Metric 2: Genetically modified organism ( GMO ) hazard, Yes/No and Hazard Category  Metric 3: Species hybridization...4– biofuel distribution Stage # 5– biofuel use Metric 1: State inva- siveness ranking Yes Minimal Minimal No No Metric 2: GMO hazard Yes...may utilize GMO microbial or microalgae species across the applicable biofuel life cycles (stages 1–3). The following consequence Metrics 4–6 then

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

    Science.gov (United States)

    Yulisda Badri, Alifiah; Darmaji

    2018-03-01

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

  13. Temporal variability of daily personal magnetic field exposure metrics in pregnant women.

    Science.gov (United States)

    Lewis, Ryan C; Evenson, Kelly R; Savitz, David A; Meeker, John D

    2015-01-01

    Recent epidemiology studies of power-frequency magnetic fields and reproductive health have characterized exposures using data collected from personal exposure monitors over a single day, possibly resulting in exposure misclassification due to temporal variability in daily personal magnetic field exposure metrics, but relevant data in adults are limited. We assessed the temporal variability of daily central tendency (time-weighted average, median) and peak (upper percentiles, maximum) personal magnetic field exposure metrics over 7 consecutive days in 100 pregnant women. When exposure was modeled as a continuous variable, central tendency metrics had substantial reliability, whereas peak metrics had fair (maximum) to moderate (upper percentiles) reliability. The predictive ability of a single-day metric to accurately classify participants into exposure categories based on a weeklong metric depended on the selected exposure threshold, with sensitivity decreasing with increasing exposure threshold. Consistent with the continuous measures analysis, sensitivity was higher for central tendency metrics than for peak metrics. If there is interest in peak metrics, more than 1 day of measurement is needed over the window of disease susceptibility to minimize measurement error, but 1 day may be sufficient for central tendency metrics.

  14. Optical Generation of Fuzzy-Based Rules

    Science.gov (United States)

    Gur, Eran; Mendlovic, David; Zalevsky, Zeev

    2002-08-01

    In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.

  15. Two projects in theoretical neuroscience: A convolution-based metric for neural membrane potentials and a combinatorial connectionist semantic network method

    Science.gov (United States)

    Evans, Garrett Nolan

    In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of

  16. Compensatory Processing During Rule-Based Category Learning in Older Adults

    Science.gov (United States)

    Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522

  17. METRICS FOR DYNAMIC SCALING OF DATABASE IN CLOUDS

    Directory of Open Access Journals (Sweden)

    Alexander V. Boichenko

    2013-01-01

    Full Text Available This article analyzes the main methods of scaling databases (replication, sharding and their support at the popular relational databases and NoSQL solutions with different data models: a document-oriented, key-value, column-oriented, graph. The article provides an assessment of the capabilities of modern cloud-based solution and gives a model for the organization of dynamic scaling in the cloud infrastructure. In the article are analyzed different types of metrics and are included the basic metrics that characterize the functioning parameters and database technology, as well as sets the goals of the integral metrics, necessary for the implementation of adaptive algorithms for dynamic scaling databases in the cloud infrastructure. This article was prepared with the support of RFBR grant № 13-07-00749.

  18. A no-reference image and video visual quality metric based on machine learning

    Science.gov (United States)

    Frantc, Vladimir; Voronin, Viacheslav; Semenishchev, Evgenii; Minkin, Maxim; Delov, Aliy

    2018-04-01

    The paper presents a novel visual quality metric for lossy compressed video quality assessment. High degree of correlation with subjective estimations of quality is due to using of a convolutional neural network trained on a large amount of pairs video sequence-subjective quality score. We demonstrate how our predicted no-reference quality metric correlates with qualitative opinion in a human observer study. Results are shown on the EVVQ dataset with comparison existing approaches.

  19. An Evaluation of the IntelliMetric[SM] Essay Scoring System

    Science.gov (United States)

    Rudner, Lawrence M.; Garcia, Veronica; Welch, Catherine

    2006-01-01

    This report provides a two-part evaluation of the IntelliMetric[SM] automated essay scoring system based on its performance scoring essays from the Analytic Writing Assessment of the Graduate Management Admission Test[TM] (GMAT[TM]). The IntelliMetric system performance is first compared to that of individual human raters, a Bayesian system…

  20. Symmetries of Taub-NUT dual metrics

    International Nuclear Information System (INIS)

    Baleanu, D.; Codoban, S.

    1998-01-01

    Recently geometric duality was analyzed for a metric which admits Killing tensors. An interesting example arises when the manifold has Killing-Yano tensors. The symmetries of the dual metrics in the case of Taub-NUT metric are investigated. Generic and non-generic symmetries of dual Taub-NUT metric are analyzed

  1. Consistence of Network Filtering Rules

    Institute of Scientific and Technical Information of China (English)

    SHE Kun; WU Yuancheng; HUANG Juncai; ZHOU Mingtian

    2004-01-01

    The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost.With development of Multinational Company,SOHO office,E-government the number of firewalls/VPN will increase rapidly.Rule table in stand-alone or network will be increased in geometric series accordingly.Checking the consistence of rule table manually is inadequate.A formal approach can define semantic consistence,make a theoretic foundation of intelligent management about rule tables.In this paper,a kind of formalization of host rules and network ones for auto rule-validation based on SET theory were proporsed and a rule validation scheme was defined.The analysis results show the superior performance of the methods and demonstrate its potential for the intelligent management based on rule tables.

  2. Metric learning

    CERN Document Server

    Bellet, Aurelien; Sebban, Marc

    2015-01-01

    Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learnin

  3. Development of a rule-based diagnostic platform on an object-oriented expert system shell

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming; Seong, Poong Hyun

    2016-01-01

    Highlights: • Multilevel Flow Model represents system knowledge as a domain map in expert system. • Rule-based fault diagnostic expert system can identify root cause via a causal chain. • Rule-based fault diagnostic expert system can be used for fault simulation training. - Abstract: This paper presents the development and implementation of a real-time rule-based diagnostic platform. The knowledge is acquired from domain experts and textbooks and the design of the fault diagnosis expert system was performed in the following ways: (i) establishing of corresponding classes and instances to build the domain map, (ii) creating of generic fault models based on events, and (iii) building of diagnostic reasoning based on rules. Knowledge representation is a complicated issue of expert systems. One highlight of this paper is that the Multilevel Flow Model has been used to represent the knowledge, which composes the domain map within the expert system as well as providing a concise description of the system. The developed platform is illustrated using the pressure safety system of a pressurized water reactor as an example of the simulation test bed; the platform is developed using the commercial and industrially validated software G2. The emulation test was conducted and it has been proven that the fault diagnosis expert system can identify the faults correctly and in a timely way; this system can be used as a simulation-based training tool to assist operators to make better decisions.

  4. Inferring feature relevances from metric learning

    DEFF Research Database (Denmark)

    Schulz, Alexander; Mokbel, Bassam; Biehl, Michael

    2015-01-01

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

  5. Technical Privacy Metrics: a Systematic Survey

    OpenAIRE

    Wagner, Isabel; Eckhoff, David

    2018-01-01

    The file attached to this record is the author's final peer reviewed version The goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies. In this way, privacy metrics contribute to improving user privacy in the digital world. The diversity and complexity of privacy metrics in the literature makes an informed choice of metrics challenging. As a result, instead of using existing metrics, n...

  6. Measures of agreement between computation and experiment:validation metrics.

    Energy Technology Data Exchange (ETDEWEB)

    Barone, Matthew Franklin; Oberkampf, William Louis

    2005-08-01

    With the increasing role of computational modeling in engineering design, performance estimation, and safety assessment, improved methods are needed for comparing computational results and experimental measurements. Traditional methods of graphically comparing computational and experimental results, though valuable, are essentially qualitative. Computable measures are needed that can quantitatively compare computational and experimental results over a range of input, or control, variables and sharpen assessment of computational accuracy. This type of measure has been recently referred to as a validation metric. We discuss various features that we believe should be incorporated in a validation metric and also features that should be excluded. We develop a new validation metric that is based on the statistical concept of confidence intervals. Using this fundamental concept, we construct two specific metrics: one that requires interpolation of experimental data and one that requires regression (curve fitting) of experimental data. We apply the metrics to three example problems: thermal decomposition of a polyurethane foam, a turbulent buoyant plume of helium, and compressibility effects on the growth rate of a turbulent free-shear layer. We discuss how the present metrics are easily interpretable for assessing computational model accuracy, as well as the impact of experimental measurement uncertainty on the accuracy assessment.

  7. Multilevel Association Rule Mining for Bridge Resource Management Based on Immune Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Ou

    2014-01-01

    Full Text Available This paper is concerned with the problem of multilevel association rule mining for bridge resource management (BRM which is announced by IMO in 2010. The goal of this paper is to mine the association rules among the items of BRM and the vessel accidents. However, due to the indirect data that can be collected, which seems useless for the analysis of the relationship between items of BIM and the accidents, the cross level association rules need to be studied, which builds the relation between the indirect data and items of BRM. In this paper, firstly, a cross level coding scheme for mining the multilevel association rules is proposed. Secondly, we execute the immune genetic algorithm with the coding scheme for analyzing BRM. Thirdly, based on the basic maritime investigation reports, some important association rules of the items of BRM are mined and studied. Finally, according to the results of the analysis, we provide the suggestions for the work of seafarer training, assessment, and management.

  8. Assessment of six dissimilarity metrics for climate analogues

    Science.gov (United States)

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

    2013-04-01

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

  9. Classification and Evaluation of Mobility Metrics for Mobility Model Movement Patterns in Mobile Ad-Hoc Networks

    OpenAIRE

    Santosh Kumar S C Sharma Bhupendra Suman

    2011-01-01

    A mobile ad hoc network is collection of self configuring and adaption of wireless link between communicating devices (mobile devices) to form an arbitrary topology and multihop wireless connectivity without the use of existing infrastructure. It requires efficient dynamic routing protocol to determine the routes subsequent to a set of rules that enables two or more devices to communicate with each others. This paper basically classifies and evaluates the mobility metrics into two categories-...

  10. Generalized Painleve-Gullstrand metrics

    Energy Technology Data Exchange (ETDEWEB)

    Lin Chunyu [Department of Physics, National Cheng Kung University, Tainan 70101, Taiwan (China)], E-mail: l2891112@mail.ncku.edu.tw; Soo Chopin [Department of Physics, National Cheng Kung University, Tainan 70101, Taiwan (China)], E-mail: cpsoo@mail.ncku.edu.tw

    2009-02-02

    An obstruction to the implementation of spatially flat Painleve-Gullstrand (PG) slicings is demonstrated, and explicitly discussed for Reissner-Nordstroem and Schwarzschild-anti-deSitter spacetimes. Generalizations of PG slicings which are not spatially flat but which remain regular at the horizons are introduced. These metrics can be obtained from standard spherically symmetric metrics by physical Lorentz boosts. With these generalized PG metrics, problematic contributions to the imaginary part of the action in the Parikh-Wilczek derivation of Hawking radiation due to the obstruction can be avoided.

  11. Flight Crew State Monitoring Metrics, Phase I

    Data.gov (United States)

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

  12. Kerr metric in the deSitter background

    International Nuclear Information System (INIS)

    Vaidya, P.C.

    1984-01-01

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

  13. FACTORS AND METRICS THAT INFLUENCE FRANCHISEE PERFORMANCE: AN APPROACH BASED ON BRAZILIAN FRANCHISES

    OpenAIRE

    Aguiar, Helder de Souza; Consoni, Flavia

    2017-01-01

    The article searches to map the manager’s decisions in order to understand what has been the franchisor system for choose regarding to characteristics, and what the metrics has been adopted to measure the performance Though 15 interviews with Brazilian franchise there was confirmation that revenue is the main metric used by national franchises to measure performance, although other indicators are also used in a complementary way. In addition, two other factors were cited by the interviewees a...

  14. An expert system design to diagnose cancer by using a new method reduced rule base.

    Science.gov (United States)

    Başçiftçi, Fatih; Avuçlu, Emre

    2018-04-01

    A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controlled instead of all possibilities (2 13 = 8192 different possibilities occur). By controlling reduced rules, results are found more quickly. The method of two-level simplification of Boolean functions was used to obtain Reduced Rule Base. Thanks to the developed application with the number of dynamic inputs and outputs on different platforms, anyone can easily test their own cancer easily. More accurate results were obtained considering all the possibilities related to cancer. Thirteen different risk factors were determined to determine the type of cancer. The truth table produced in our study has 13 inputs and 4 outputs. The Boolean Function Minimization method is used to obtain less situations by simplifying logical functions. Diagnosis of cancer quickly thanks to control of the simplified 4 output functions. Diagnosis made with the 4 output values obtained using Reduced Rule Base was found to be quicker than diagnosis made by screening all 2 13 = 8192 possibilities. With the improved MES, more probabilities were added to the process and more accurate diagnostic results were obtained. As a result of the simplification process in breast and renal cancer diagnosis 100% diagnosis speed gain, in cervical cancer and lung cancer diagnosis rate gain of 99% was obtained. With Boolean function minimization, less number of rules is evaluated instead of evaluating a large number of rules. Reducing the number of rules allows the designed system to work more efficiently and to save time, and facilitates to transfer the rules to the designed Expert systems. Interfaces were developed in different software platforms to enable users to test the accuracy of the application. Any one is able to diagnose the cancer itself using determinative risk factors. Thereby

  15. Comparing Resource Adequacy Metrics and Their Influence on Capacity Value: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Ibanez, E.; Milligan, M.

    2014-04-01

    Traditional probabilistic methods have been used to evaluate resource adequacy. The increasing presence of variable renewable generation in power systems presents a challenge to these methods because, unlike thermal units, variable renewable generation levels change over time because they are driven by meteorological events. Thus, capacity value calculations for these resources are often performed to simple rules of thumb. This paper follows the recommendations of the North American Electric Reliability Corporation?s Integration of Variable Generation Task Force to include variable generation in the calculation of resource adequacy and compares different reliability metrics. Examples are provided using the Western Interconnection footprint under different variable generation penetrations.

  16. Kerr metric in cosmological background

    Energy Technology Data Exchange (ETDEWEB)

    Vaidya, P C [Gujarat Univ., Ahmedabad (India). Dept. of Mathematics

    1977-06-01

    A metric satisfying Einstein's equation is given which in the vicinity of the source reduces to the well-known Kerr metric and which at large distances reduces to the Robertson-Walker metric of a nomogeneous cosmological model. The radius of the event horizon of the Kerr black hole in the cosmological background is found out.

  17. Relevance of motion-related assessment metrics in laparoscopic surgery.

    Science.gov (United States)

    Oropesa, Ignacio; Chmarra, Magdalena K; Sánchez-González, Patricia; Lamata, Pablo; Rodrigues, Sharon P; Enciso, Silvia; Sánchez-Margallo, Francisco M; Jansen, Frank-Willem; Dankelman, Jenny; Gómez, Enrique J

    2013-06-01

    Motion metrics have become an important source of information when addressing the assessment of surgical expertise. However, their direct relationship with the different surgical skills has not been fully explored. The purpose of this study is to investigate the relevance of motion-related metrics in the evaluation processes of basic psychomotor laparoscopic skills and their correlation with the different abilities sought to measure. A framework for task definition and metric analysis is proposed. An explorative survey was first conducted with a board of experts to identify metrics to assess basic psychomotor skills. Based on the output of that survey, 3 novel tasks for surgical assessment were designed. Face and construct validation was performed, with focus on motion-related metrics. Tasks were performed by 42 participants (16 novices, 22 residents, and 4 experts). Movements of the laparoscopic instruments were registered with the TrEndo tracking system and analyzed. Time, path length, and depth showed construct validity for all 3 tasks. Motion smoothness and idle time also showed validity for tasks involving bimanual coordination and tasks requiring a more tactical approach, respectively. Additionally, motion smoothness and average speed showed a high internal consistency, proving them to be the most task-independent of all the metrics analyzed. Motion metrics are complementary and valid for assessing basic psychomotor skills, and their relevance depends on the skill being evaluated. A larger clinical implementation, combined with quality performance information, will give more insight on the relevance of the results shown in this study.

  18. Physics in space-time with scale-dependent metrics

    Science.gov (United States)

    Balankin, Alexander S.

    2013-10-01

    We construct three-dimensional space Rγ3 with the scale-dependent metric and the corresponding Minkowski space-time Mγ,β4 with the scale-dependent fractal (DH) and spectral (DS) dimensions. The local derivatives based on scale-dependent metrics are defined and differential vector calculus in Rγ3 is developed. We state that Mγ,β4 provides a unified phenomenological framework for dimensional flow observed in quite different models of quantum gravity. Nevertheless, the main attention is focused on the special case of flat space-time M1/3,14 with the scale-dependent Cantor-dust-like distribution of admissible states, such that DH increases from DH=2 on the scale ≪ℓ0 to DH=4 in the infrared limit ≫ℓ0, where ℓ0 is the characteristic length (e.g. the Planck length, or characteristic size of multi-fractal features in heterogeneous medium), whereas DS≡4 in all scales. Possible applications of approach based on the scale-dependent metric to systems of different nature are briefly discussed.

  19. Formulation of the verbal thought process based on generative rules

    Energy Technology Data Exchange (ETDEWEB)

    Suehiro, N; Fujisaki, H

    1984-01-01

    As assumption is made on the generative nature of the verbal thought process, based on an analogy between language use and verbal thought. A procedure is then presented for acquiring the set of generative rules from a given set of concept strings, leading to an efficient representation of verbal knowledge. The non-terminal symbols derived in the acquisition process are found to correspond to concepts and superordinate concepts in the human process of verbal thought. The validity of the formulation and the efficiency of knowledge representation is demonstrated by an example in which knowledge of biological properties of animals is reorganized into a set of generative rules. The process of inductive inference is then defined as a generalization of the acquired knowledge, and the principle of maximum simplicity of rules is proposed as a possible criterion for such generalization. The proposal is also tested by an example in which only a small part of a systematic body of knowledge is utilized to make interferences on the unknown parts of the system. 6 references.

  20. Analysis on the Metrics used in Optimizing Electronic Business based on Learning Techniques

    Directory of Open Access Journals (Sweden)

    Irina-Steliana STAN

    2014-09-01

    Full Text Available The present paper proposes a methodology of analyzing the metrics related to electronic business. The drafts of the optimizing models include KPIs that can highlight the business specific, if only they are integrated by using learning-based techniques. Having set the most important and high-impact elements of the business, the models should get in the end the link between them, by automating business flows. The human resource will be found in the situation of collaborating more and more with the optimizing models which will translate into high quality decisions followed by profitability increase.

  1. Delayed rule following.

    Science.gov (United States)

    Schmitt, D R

    2001-01-01

    Although the elements of a fully stated rule (discriminative stimulus [S(D)], some behavior, and a consequence) can occur nearly contemporaneously with the statement of the rule, there is often a delay between the rule statement and the S(D). The effects of this delay on rule following have not been studied in behavior analysis, but they have been investigated in rule-like settings in the areas of prospective memory (remembering to do something in the future) and goal pursuit. Discriminative events for some behavior can be event based (a specific setting stimulus) or time based. The latter are more demanding with respect to intention following and show age-related deficits. Studies suggest that the specificity with which the components of a rule (termed intention) are stated has a substantial effect on intention following, with more detailed specifications increasing following. Reminders of an intention, too, are most effective when they refer specifically to both the behavior and its occasion. Covert review and written notes are two effective strategies for remembering everyday intentions, but people who use notes appear not to be able to switch quickly to covert review. By focusing on aspects of the setting and rule structure, research on prospective memory and goal pursuit expands the agenda for a more complete explanation of rule effects.

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

    Science.gov (United States)

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

    2016-01-01

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

  3. Metrics for Electronic-Nursing-Record-Based Narratives: Cross-sectional Analysis

    Science.gov (United States)

    Kim, Kidong; Jeong, Suyeon; Lee, Kyogu; Park, Hyeoun-Ae; Min, Yul Ha; Lee, Joo Yun; Kim, Yekyung; Yoo, Sooyoung; Doh, Gippeum

    2016-01-01

    Summary Objectives We aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses. Methods We collected 135,406,873 electronic, structured coded nursing narratives from 231,494 hospital admissions of patients discharged between 2008 and 2012 at a tertiary teaching institution that routinely uses an electronic health records system. The standardized number of nursing narratives (i.e., the total number of nursing narratives divided by the length of the hospital stay) was suggested to integrate the frequency and quantity of nursing documentation. Results The standardized number of nursing narratives was higher for patients aged 70 years (median = 30.2 narratives/day, interquartile range [IQR] = 24.0–39.4 narratives/day), long (8 days) hospital stays (median = 34.6 narratives/day, IQR = 27.2–43.5 narratives/day), and hospital deaths (median = 59.1 narratives/day, IQR = 47.0–74.8 narratives/day). The standardized number of narratives was higher in “pregnancy, childbirth, and puerperium” (median = 46.5, IQR = 39.0–54.7) and “diseases of the circulatory system” admissions (median = 35.7, IQR = 29.0–43.4). Conclusions Diverse hospital admissions can be consistently described with nursing-document-derived metrics for similar hospital admissions and diagnoses. Some areas of hospital admissions may have consistently increasing volumes of nursing documentation across years. Usability of electronic nursing document metrics for evaluating healthcare requires multiple aspects of hospital admissions to be considered. PMID:27901174

  4. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    Science.gov (United States)

    Giraldo, Sergio I.; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules

  5. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music.

    Science.gov (United States)

    Giraldo, Sergio I; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules.

  6. Cophenetic metrics for phylogenetic trees, after Sokal and Rohlf.

    Science.gov (United States)

    Cardona, Gabriel; Mir, Arnau; Rosselló, Francesc; Rotger, Lucía; Sánchez, David

    2013-01-16

    Phylogenetic tree comparison metrics are an important tool in the study of evolution, and hence the definition of such metrics is an interesting problem in phylogenetics. In a paper in Taxon fifty years ago, Sokal and Rohlf proposed to measure quantitatively the difference between a pair of phylogenetic trees by first encoding them by means of their half-matrices of cophenetic values, and then comparing these matrices. This idea has been used several times since then to define dissimilarity measures between phylogenetic trees but, to our knowledge, no proper metric on weighted phylogenetic trees with nested taxa based on this idea has been formally defined and studied yet. Actually, the cophenetic values of pairs of different taxa alone are not enough to single out phylogenetic trees with weighted arcs or nested taxa. For every (rooted) phylogenetic tree T, let its cophenetic vectorφ(T) consist of all pairs of cophenetic values between pairs of taxa in T and all depths of taxa in T. It turns out that these cophenetic vectors single out weighted phylogenetic trees with nested taxa. We then define a family of cophenetic metrics dφ,p by comparing these cophenetic vectors by means of Lp norms, and we study, either analytically or numerically, some of their basic properties: neighbors, diameter, distribution, and their rank correlation with each other and with other metrics. The cophenetic metrics can be safely used on weighted phylogenetic trees with nested taxa and no restriction on degrees, and they can be computed in O(n2) time, where n stands for the number of taxa. The metrics dφ,1 and dφ,2 have positive skewed distributions, and they show a low rank correlation with the Robinson-Foulds metric and the nodal metrics, and a very high correlation with each other and with the splitted nodal metrics. The diameter of dφ,p, for p⩾1 , is in O(n(p+2)/p), and thus for low p they are more discriminative, having a wider range of values.

  7. Metrical presentation boosts implicit learning of artificial grammar.

    Science.gov (United States)

    Selchenkova, Tatiana; François, Clément; Schön, Daniele; Corneyllie, Alexandra; Perrin, Fabien; Tillmann, Barbara

    2014-01-01

    The present study investigated whether a temporal hierarchical structure favors implicit learning. An artificial pitch grammar implemented with a set of tones was presented in two different temporal contexts, notably with either a strongly metrical structure or an isochronous structure. According to the Dynamic Attending Theory, external temporal regularities can entrain internal oscillators that guide attention over time, allowing for temporal expectations that influence perception of future events. Based on this framework, it was hypothesized that the metrical structure provides a benefit for artificial grammar learning in comparison to an isochronous presentation. Our study combined behavioral and event-related potential measurements. Behavioral results demonstrated similar learning in both participant groups. By contrast, analyses of event-related potentials showed a larger P300 component and an earlier N2 component for the strongly metrical group during the exposure phase and the test phase, respectively. These findings suggests that the temporal expectations in the strongly metrical condition helped listeners to better process the pitch dimension, leading to improved learning of the artificial grammar.

  8. Verification of Equivalence of the Axial Gauge to the Coulomb Gauge in QED by Embedding in the Indefinite Metric Hilbert Space : Particles and Fields

    OpenAIRE

    Yuji, NAKAWAKI; Azuma, TANAKA; Kazuhiko, OZAKI; Division of Physics and Mathematics, Faculty of Engineering Setsunan University; Junior College of Osaka Institute of Technology; Faculty of General Education, Osaka Institute of Technology

    1994-01-01

    Gauge Equivalence of the A_3=0 (axial) gauge to the Coulomb gauge is directly verified in QED. For that purpose a pair of conjugate zero-norm fields are introduced. This enables us to construct a canonical formulation in the axial gauge embedded in the indefinite metric Hilbert space in such a way that the Feynman rules are not altered. In the indefinite metric Hilbert space we can implement a gauge transformation, which otherwise has to be carried out only by hand, as main parts of a canonic...

  9. Two classes of metric spaces

    Directory of Open Access Journals (Sweden)

    Isabel Garrido

    2016-04-01

    Full Text Available The class of metric spaces (X,d known as small-determined spaces, introduced by Garrido and Jaramillo, are properly defined by means of some type of real-valued Lipschitz functions on X. On the other hand, B-simple metric spaces introduced by Hejcman are defined in terms of some kind of bornologies of bounded subsets of X. In this note we present a common framework where both classes of metric spaces can be studied which allows us to see not only the relationships between them but also to obtain new internal characterizations of these metric properties.

  10. An Emperical Analysis of Co-Movements in High- and Low-Frequency Metrics for Financial Market Efficiency

    NARCIS (Netherlands)

    D.M. Rösch (Dominik); A. Subrahmanyam (Avanidhar); M.A. van Dijk (Mathijs)

    2014-01-01

    textabstractSeveral high- and low-frequency metrics for financial market efficiency have been proposed in distinct lines of research. We explore the joint dynamics of these metrics. High-frequency metrics co-move across individual stocks, and also co-move with lower-frequency metrics based on

  11. Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mokhamad Iklil Mustofa

    2017-05-01

    Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

  12. Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mar Fuah

    2017-05-01

    Full Text Available One of the problems in the criminal case completions is that the difficulty of making decision to estimate when the settlement of the case file will be fulfilled. It is caused by the number of case files handled and detention time changing. Therefore, the fast and accurate information is needed. The research aims to develop a monitoring system tracking and tracking of scheduling rules using Rule Based Expert Systems method with 17 rules, and supported by Radio Frequency Identification technology (RFID in the form of computer applications. Based on the output of the system, an analysis is performed in the criminal case settlement process with a set of IF-THEN rules. The RFID reader read the data of case files through radio wave signals emitted by the antenna toward active-Tag attached in the criminal case file. The system is designed to monitor the tracking and tracing of RFID-based scheduling rules in realtime way that was built in the form of computer application in accordance with the system design. This study results in no failure in reading active tags by the RFID reader to detect criminal case files that had been examined. There were many case files handled in three different location, they were the constabulary, prosecutor, and judges of district court and RFID was able to identify them simultaneously. So, RFID supports the implementation of Rule Based Expert Systems very much for realtime monitoring in criminal case accomplishment.

  13. Better Metrics to Automatically Predict the Quality of a Text Summary

    Directory of Open Access Journals (Sweden)

    Judith D. Schlesinger

    2012-09-01

    Full Text Available In this paper we demonstrate a family of metrics for estimating the quality of a text summary relative to one or more human-generated summaries. The improved metrics are based on features automatically computed from the summaries to measure content and linguistic quality. The features are combined using one of three methods—robust regression, non-negative least squares, or canonical correlation, an eigenvalue method. The new metrics significantly outperform the previous standard for automatic text summarization evaluation, ROUGE.

  14. A rule of seven in Watson-Crick base-pairing of mismatched sequences.

    Science.gov (United States)

    Cisse, Ibrahim I; Kim, Hajin; Ha, Taekjip

    2012-05-13

    Sequence recognition through base-pairing is essential for DNA repair and gene regulation, but the basic rules governing this process remain elusive. In particular, the kinetics of annealing between two imperfectly matched strands is not well characterized, despite its potential importance in nucleic acid-based biotechnologies and gene silencing. Here we use single-molecule fluorescence to visualize the multiple annealing and melting reactions of two untethered strands inside a porous vesicle, allowing us to precisely quantify the annealing and melting rates. The data as a function of mismatch position suggest that seven contiguous base pairs are needed for rapid annealing of DNA and RNA. This phenomenological rule of seven may underlie the requirement for seven nucleotides of complementarity to seed gene silencing by small noncoding RNA and may help guide performance improvement in DNA- and RNA-based bio- and nanotechnologies, in which off-target effects can be detrimental.

  15. Landscape metrics application in ecological and visual landscape assessment

    Directory of Open Access Journals (Sweden)

    Gavrilović Suzana

    2017-01-01

    Full Text Available The development of landscape-ecological approach application in spatial planning provides exact theoretical and empirical evidence for monitoring ecological consequences of natural and/or anthropogenic factors, particularly changes in spatial structures caused by them. Landscape pattern which feature diverse landscape values is the holder of the unique landscape character at different spatial levels and represents a perceptual domain for its users. Using the landscape metrics, the parameters of landscape composition and configuration are mathematical algorithms that quantify the specific spatial characteristics used for interpretation of landscape features and processes (physical and ecological aspect, as well as forms (visual aspect and the meaning (cognitive aspect of the landscape. Landscape metrics has been applied mostly in the ecological and biodiversity assessments as well as in the determination of the level of structural change of landscape, but more and more applied in the assessment of the visual character of the landscape. Based on a review of relevant literature, the aim of this work is to show the main trends of landscape metrics within the aspect of ecological and visual assessments. The research methodology is based on the analysis, classification and systematization of the research studies published from 2000 to 2016, where the landscape metrics is applied: (1 the analysis of landscape pattern and its changes, (2 the analysis of biodiversity and habitat function and (3 a visual landscape assessment. By selecting representative metric parameters for the landscape composition and configuration, for each category is formed the basis for further landscape metrics research and application for the integrated ecological and visual assessment of the landscape values. Contemporary conceptualization of the landscape is seen holistically, and the future research should be directed towards the development of integrated landscape assessment

  16. A Metric for Heterotic Moduli

    Science.gov (United States)

    Candelas, Philip; de la Ossa, Xenia; McOrist, Jock

    2017-12-01

    Heterotic vacua of string theory are realised, at large radius, by a compact threefold with vanishing first Chern class together with a choice of stable holomorphic vector bundle. These form a wide class of potentially realistic four-dimensional vacua of string theory. Despite all their phenomenological promise, there is little understanding of the metric on the moduli space of these. What is sought is the analogue of special geometry for these vacua. The metric on the moduli space is important in phenomenology as it normalises D-terms and Yukawa couplings. It is also of interest in mathematics, since it generalises the metric, first found by Kobayashi, on the space of gauge field connections, to a more general context. Here we construct this metric, correct to first order in {α^{\\backprime}}, in two ways: first by postulating a metric that is invariant under background gauge transformations of the gauge field, and also by dimensionally reducing heterotic supergravity. These methods agree and the resulting metric is Kähler, as is required by supersymmetry. Checking the metric is Kähler is intricate and the anomaly cancellation equation for the H field plays an essential role. The Kähler potential nevertheless takes a remarkably simple form: it is the Kähler potential of special geometry with the Kähler form replaced by the {α^{\\backprime}}-corrected hermitian form.

  17. Rule-based expert system for maritime anomaly detection

    Science.gov (United States)

    Roy, Jean

    2010-04-01

    Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

  18. Oil palm fresh fruit bunch ripeness classification based on rule- based expert system of ROI image processing technique results

    International Nuclear Information System (INIS)

    Alfatni, M S M; Shariff, A R M; Marhaban, M H; Shafie, S B; Saaed, O M B; Abdullah, M Z; BAmiruddin, M D

    2014-01-01

    There is a processing need for a fast, easy and accurate classification system for oil palm fruit ripeness. Such a system will be invaluable to farmers and plantation managers who need to sell their oil palm fresh fruit bunch (FFB) for the mill as this will avoid disputes. In this paper,a new approach was developed under the name of expert rules-based systembased on the image processing techniques results of thethree different oil palm FFB region of interests (ROIs), namely; ROI1 (300x300 pixels), ROI2 (50x50 pixels) and ROI3 (100x100 pixels). The results show that the best rule-based ROIs for statistical colour feature extraction with k-nearest neighbors (KNN) classifier at 94% were chosen as well as the ROIs that indicated results higher than the rule-based outcome, such as the ROIs of statistical colour feature extraction with artificial neural network (ANN) classifier at 94%, were selected for further FFB ripeness inspection system

  19. On characterizations of quasi-metric completeness

    Energy Technology Data Exchange (ETDEWEB)

    Dag, H.; Romaguera, S.; Tirado, P.

    2017-07-01

    Hu proved in [4] that a metric space (X, d) is complete if and only if for any closed subspace C of (X, d), every Banach contraction on C has fixed point. Since then several authors have investigated the problem of characterizing the metric completeness by means of fixed point theorems. Recently this problem has been studied in the more general context of quasi-metric spaces for different notions of completeness. Here we present a characterization of a kind of completeness for quasi-metric spaces by means of a quasi-metric versions of Hu’s theorem. (Author)

  20. MO-FG-202-07: Real-Time EPID-Based Detection Metric For VMAT Delivery Errors

    International Nuclear Information System (INIS)

    Passarge, M; Fix, M K; Manser, P; Stampanoni, M F M; Siebers, J V

    2016-01-01

    Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling and translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error

  1. MO-FG-202-07: Real-Time EPID-Based Detection Metric For VMAT Delivery Errors

    Energy Technology Data Exchange (ETDEWEB)

    Passarge, M; Fix, M K; Manser, P [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern (Switzerland); Stampanoni, M F M [Institute for Biomedical Engineering, ETH Zurich, and PSI, Villigen (Switzerland); Siebers, J V [Department of Radiation Oncology, University of Virginia, Charlottesville, VA (United States)

    2016-06-15

    Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling and translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error

  2. Constructing a no-reference H.264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression

    OpenAIRE

    Staelens, Nicolas; Deschrijver, Dirk; Vladislavleva, E; Vermeulen, Brecht; Dhaene, Tom; Demeester, Piet

    2013-01-01

    In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers. Objective video quality metrics try to estimate perceived quality with high accuracy and in an automated manner. In traditional approaches, these metrics model the complex properties of the human visual system. More recently, however, it has been shown that machine learning approaches can also yield comp...

  3. 77 FR 22042 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Science.gov (United States)

    2012-04-12

    ... provide information regarding, for example, volume metrics, number of MQP Market Makers in target...-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule Change, as Modified by Amendment No. 1 Thereto, To Establish the Market Quality Program April 6, 2012. Pursuant to...

  4. Research on quality metrics of wireless adaptive video streaming

    Science.gov (United States)

    Li, Xuefei

    2018-04-01

    With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

  5. Belief-rule-based expert systems for evaluation of e-government

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Zander, Pär-Ola Mikael; Kamal, Md Sarwar

    2015-01-01

    , known as the Belief Rule Based Expert System (BRBES) and implemented in the local e-government of Bangladesh. The results have been compared with a recently developed method of evaluating e-government, and it is demonstrated that the results of the BRBES are more accurate and reliable. The BRBES can...

  6. LPS: a rule-based, schema-oriented knowledge representation system

    Energy Technology Data Exchange (ETDEWEB)

    Anzai, Y; Mitsuya, Y; Nakajima, S; Ura, S

    1981-01-01

    A new knowledge representation system called LPS is presented. The global control structure of LPS is rule-based, but the local representational structure is schema-oriented. The present version of LPS was designed to increase the understandability of representation while keeping time efficiency reasonable. Pattern matching through slot-networks and meta-actions from among the implemented facilities of LPS, are especially described in detail. 7 references.

  7. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  8. Two Phase Non-Rigid Multi-Modal Image Registration Using Weber Local Descriptor-Based Similarity Metrics and Normalized Mutual Information

    Directory of Open Access Journals (Sweden)

    Feng Yang

    2013-06-01

    Full Text Available Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI and sum of squared differences (SSD cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD based similarity metrics with the normalized mutual information (NMI using the diffeomorphic free-form deformation (FFD model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD or weighted structural similarity (wldWSSIM. Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI, the SSD on entropy images (ESSD and the ESSD-NMI in terms of registration accuracy and computation efficiency.

  9. Experiences with Software Quality Metrics in the EMI Middleware

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The EMI Quality Model has been created to define, and later review, the EMI (European Middleware Initiative) software product and process quality. A quality model is based on a set of software quality metrics and helps to set clear and measurable quality goals for software products and processes. The EMI Quality Model follows the ISO/IEC 9126 Software Engineering – Product Quality to identify a set of characteristics that need to be present in the EMI software. For each software characteristic, such as portability, maintainability, compliance, etc, a set of associated metrics and KPIs (Key Performance Indicators) are identified. This article presents how the EMI Quality Model and the EMI Metrics have been defined in the context of the software quality assurance activities carried out in EMI. It also describes the measurement plan and presents some of the metrics reports that have been produced for the EMI releases and updates. It also covers which tools and techniques can be used by any software project t...

  10. Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Bima Sena Bayu Dewantara

    2014-12-01

    Full Text Available Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time. Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm

  11. A Rule-Based Data Transfer Protocol for On-Demand Data Exchange in Vehicular Environment

    Directory of Open Access Journals (Sweden)

    Liao Hsien-Chou

    2009-01-01

    Full Text Available The purpose of Intelligent Transport System (ITS is mainly to increase the driving safety and efficiency. Data exchange is an important way to achieve the purpose. An on-demand data exchange is especially useful to assist a driver avoiding some emergent events. In order to handle the data exchange under dynamic situations, a rule-based data transfer protocol is proposed in this paper. A set of rules is designed according to the principle of request-forward-reply (RFR. That is, they are used to determine the timing of data broadcasting, forwarding, and replying automatically. Two typical situations are used to demonstrate the operation of rules. One is the front view of a driver occluded by other vehicles. The other is the traffic jam. The proposed protocol is flexible and extensible for unforeseen situations. Three simulation tools were also implemented to demonstrate the feasibility of the protocol and measure the network transmission under high density of vehicles. The simulation results show that the rule-based protocol is efficient on data exchange to increase the driving safety.

  12. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution. The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post

  13. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Science.gov (United States)

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  14. Metrics for Analyzing Quantifiable Differentiation of Designs with Varying Integrity for Hardware Assurance

    Science.gov (United States)

    2017-03-01

    Keywords — Trojan; integrity; trust; quantify; hardware; assurance; verification; metrics ; reference, quality ; profile I. INTRODUCTION A. The Rising...as a framework for benchmarking Trusted Part certifications. Previous work conducted in Trust Metric development has focused on measures at the...the lowest integrities. Based on the analysis, the DI metric shows measurable differentiation between all five Test Article Error Location Error

  15. Relationship between Journal-Ranking Metrics for a Multidisciplinary Set of Journals

    Science.gov (United States)

    Perera, Upeksha; Wijewickrema, Manjula

    2018-01-01

    Ranking of scholarly journals is important to many parties. Studying the relationships among various ranking metrics is key to understanding the significance of one metric based on another. This research investigates the relationship among four major journal-ranking indicators: the impact factor (IF), the Eigenfactor score (ES), the "h."…

  16. Engineering performance metrics

    Science.gov (United States)

    Delozier, R.; Snyder, N.

    1993-03-01

    Implementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including, conceptual design, detailed design, implementation, and integration. The lessons teamed from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system accomplishing project objectives and in achieving improved customer satisfaction. To facilitate this effort, a team was chartered to assist in the development of the metrics system. This team, consisting of customers and Engineering staff members, was utilized to ensure that the needs and views of the customers were considered in the development of performance measurements. The development of a system of metrics is no different than the development of any type of system. It includes the steps of defining performance measurement requirements, measurement process conceptual design, performance measurement and reporting system detailed design, and system implementation and integration.

  17. Ant-based extraction of rules in simple decision systems over ontological graphs

    Directory of Open Access Journals (Sweden)

    Pancerz Krzysztof

    2015-06-01

    Full Text Available In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA. In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

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

    Science.gov (United States)

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

    2012-11-01

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

  19. Brand metrics that matter

    NARCIS (Netherlands)

    Muntinga, D.; Bernritter, S.

    2017-01-01

    Het merk staat steeds meer centraal in de organisatie. Het is daarom essentieel om de gezondheid, prestaties en ontwikkelingen van het merk te meten. Het is echter een uitdaging om de juiste brand metrics te selecteren. Een enorme hoeveelheid metrics vraagt de aandacht van merkbeheerders. Maar welke

  20. Privacy Metrics and Boundaries

    NARCIS (Netherlands)

    L-F. Pau (Louis-François)

    2005-01-01

    textabstractThis paper aims at defining a set of privacy metrics (quantitative and qualitative) in the case of the relation between a privacy protector ,and an information gatherer .The aims with such metrics are: -to allow to assess and compare different user scenarios and their differences; for

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

    Directory of Open Access Journals (Sweden)

    Mostafa Charmi

    2010-06-01

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

  2. Rule-based model of vein graft remodeling.

    Directory of Open Access Journals (Sweden)

    Minki Hwang

    Full Text Available When vein segments are implanted into the arterial system for use in arterial bypass grafting, adaptation to the higher pressure and flow of the arterial system is accomplished thorough wall thickening and expansion. These early remodeling events have been found to be closely coupled to the local hemodynamic forces, such as shear stress and wall tension, and are believed to be the foundation for later vein graft failure. To further our mechanistic understanding of the cellular and extracellular interactions that lead to global changes in tissue architecture, a rule-based modeling method is developed through the application of basic rules of behaviors for these molecular and cellular activities. In the current method, smooth muscle cell (SMC, extracellular matrix (ECM, and monocytes are selected as the three components that occupy the elements of a grid system that comprise the developing vein graft intima. The probabilities of the cellular behaviors are developed based on data extracted from in vivo experiments. At each time step, the various probabilities are computed and applied to the SMC and ECM elements to determine their next physical state and behavior. One- and two-dimensional models are developed to test and validate the computational approach. The importance of monocyte infiltration, and the associated effect in augmenting extracellular matrix deposition, was evaluated and found to be an important component in model development. Final model validation is performed using an independent set of experiments, where model predictions of intimal growth are evaluated against experimental data obtained from the complex geometry and shear stress patterns offered by a mid-graft focal stenosis, where simulation results show good agreements with the experimental data.

  3. Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

    Science.gov (United States)

    Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

    2015-04-01

    In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Some Metric Properties of Planar Gaussian Free Field

    Science.gov (United States)

    Goswami, Subhajit

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

  5. Rule-Based Analytic Asset Management for Space Exploration Systems (RAMSES), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. (PSI) and the Massachusetts Institute of Technology (MIT) were selected to jointly develop the Rule-based Analytic Asset Management for Space...

  6. Human Performance Optimization Metrics: Consensus Findings, Gaps, and Recommendations for Future Research.

    Science.gov (United States)

    Nindl, Bradley C; Jaffin, Dianna P; Dretsch, Michael N; Cheuvront, Samuel N; Wesensten, Nancy J; Kent, Michael L; Grunberg, Neil E; Pierce, Joseph R; Barry, Erin S; Scott, Jonathan M; Young, Andrew J; OʼConnor, Francis G; Deuster, Patricia A

    2015-11-01

    Human performance optimization (HPO) is defined as "the process of applying knowledge, skills and emerging technologies to improve and preserve the capabilities of military members, and organizations to execute essential tasks." The lack of consensus for operationally relevant and standardized metrics that meet joint military requirements has been identified as the single most important gap for research and application of HPO. In 2013, the Consortium for Health and Military Performance hosted a meeting to develop a toolkit of standardized HPO metrics for use in military and civilian research, and potentially for field applications by commanders, units, and organizations. Performance was considered from a holistic perspective as being influenced by various behaviors and barriers. To accomplish the goal of developing a standardized toolkit, key metrics were identified and evaluated across a spectrum of domains that contribute to HPO: physical performance, nutritional status, psychological status, cognitive performance, environmental challenges, sleep, and pain. These domains were chosen based on relevant data with regard to performance enhancers and degraders. The specific objectives at this meeting were to (a) identify and evaluate current metrics for assessing human performance within selected domains; (b) prioritize metrics within each domain to establish a human performance assessment toolkit; and (c) identify scientific gaps and the needed research to more effectively assess human performance across domains. This article provides of a summary of 150 total HPO metrics across multiple domains that can be used as a starting point-the beginning of an HPO toolkit: physical fitness (29 metrics), nutrition (24 metrics), psychological status (36 metrics), cognitive performance (35 metrics), environment (12 metrics), sleep (9 metrics), and pain (5 metrics). These metrics can be particularly valuable as the military emphasizes a renewed interest in Human Dimension efforts

  7. Challenges for Rule Systems on the Web

    Science.gov (United States)

    Hu, Yuh-Jong; Yeh, Ching-Long; Laun, Wolfgang

    The RuleML Challenge started in 2007 with the objective of inspiring the issues of implementation for management, integration, interoperation and interchange of rules in an open distributed environment, such as the Web. Rules are usually classified as three types: deductive rules, normative rules, and reactive rules. The reactive rules are further classified as ECA rules and production rules. The study of combination rule and ontology is traced back to an earlier active rule system for relational and object-oriented (OO) databases. Recently, this issue has become one of the most important research problems in the Semantic Web. Once we consider a computer executable policy as a declarative set of rules and ontologies that guides the behavior of entities within a system, we have a flexible way to implement real world policies without rewriting the computer code, as we did before. Fortunately, we have de facto rule markup languages, such as RuleML or RIF to achieve the portability and interchange of rules for different rule systems. Otherwise, executing real-life rule-based applications on the Web is almost impossible. Several commercial or open source rule engines are available for the rule-based applications. However, we still need a standard rule language and benchmark for not only to compare the rule systems but also to measure the progress in the field. Finally, a number of real-life rule-based use cases will be investigated to demonstrate the applicability of current rule systems on the Web.

  8. General relativity: An erfc metric

    Science.gov (United States)

    Plamondon, Réjean

    2018-06-01

    This paper proposes an erfc potential to incorporate in a symmetric metric. One key feature of this model is that it relies on the existence of an intrinsic physical constant σ, a star-specific proper length that scales all its surroundings. Based thereon, the new metric is used to study the space-time geometry of a static symmetric massive object, as seen from its interior. The analytical solutions to the Einstein equation are presented, highlighting the absence of singularities and discontinuities in such a model. The geodesics are derived in their second- and first-order differential formats. Recalling the slight impact of the new model on the classical general relativity tests in the solar system, a number of facts and open problems are briefly revisited on the basis of a heuristic definition of σ. A special attention is given to gravitational collapses and non-singular black holes.

  9. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  10. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    Directory of Open Access Journals (Sweden)

    Sergio Ivan Giraldo

    2016-12-01

    Full Text Available Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1 quantitatively evaluate the accuracy of the induced models, (2 analyse the relative importance of the considered musical features, (3 discuss some of the learnt expressive performance rules in the context of previous work, and (4 assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules’ performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the

  11. DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

    Science.gov (United States)

    Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

    2018-04-01

    Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

  12. Microservice scaling optimization based on metric collection in Kubernetes

    OpenAIRE

    Blažej, Aljaž

    2017-01-01

    As web applications become more complex and the number of internet users rises, so does the need to optimize the use of hardware supporting these applications. Optimization can be achieved with microservices, as they offer several advantages compared to the monolithic approach, such as better utilization of resources, scalability and isolation of different parts of an application. Another important part is collecting metrics, since they can be used for analysis and debugging as well as the ba...

  13. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...

  14. Survey of source code metrics for evaluating testability of object oriented systems

    OpenAIRE

    Shaheen , Muhammad Rabee; Du Bousquet , Lydie

    2010-01-01

    Software testing is costly in terms of time and funds. Testability is a software characteristic that aims at producing systems easy to test. Several metrics have been proposed to identify the testability weaknesses. But it is sometimes difficult to be convinced that those metrics are really related with testability. This article is a critical survey of the source-code based metrics proposed in the literature for object-oriented software testability. It underlines the necessity to provide test...

  15. Multi-metric model-based structural health monitoring

    Science.gov (United States)

    Jo, Hongki; Spencer, B. F.

    2014-04-01

    ABSTRACT The inspection and maintenance of bridges of all types is critical to the public safety and often critical to the economy of a region. Recent advanced sensor technologies provide accurate and easy-to-deploy means for structural health monitoring and, if the critical locations are known a priori, can be monitored by direct measurements. However, for today's complex civil infrastructure, the critical locations are numerous and often difficult to identify. This paper presents an innovative framework for structural monitoring at arbitrary locations on the structure combining computational models and limited physical sensor information. The use of multi-metric measurements is advocated to improve the accuracy of the approach. A numerical example is provided to illustrate the proposed hybrid monitoring framework, particularly focusing on fatigue life assessment of steel structures.

  16. Cyber threat metrics.

    Energy Technology Data Exchange (ETDEWEB)

    Frye, Jason Neal; Veitch, Cynthia K.; Mateski, Mark Elliot; Michalski, John T.; Harris, James Mark; Trevino, Cassandra M.; Maruoka, Scott

    2012-03-01

    Threats are generally much easier to list than to describe, and much easier to describe than to measure. As a result, many organizations list threats. Fewer describe them in useful terms, and still fewer measure them in meaningful ways. This is particularly true in the dynamic and nebulous domain of cyber threats - a domain that tends to resist easy measurement and, in some cases, appears to defy any measurement. We believe the problem is tractable. In this report we describe threat metrics and models for characterizing threats consistently and unambiguously. The purpose of this report is to support the Operational Threat Assessment (OTA) phase of risk and vulnerability assessment. To this end, we focus on the task of characterizing cyber threats using consistent threat metrics and models. In particular, we address threat metrics and models for describing malicious cyber threats to US FCEB agencies and systems.

  17. Fixed point theory in metric type spaces

    CERN Document Server

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

    2015-01-01

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

  18. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. RULE-BASE METHOD FOR ANALYSIS OF QUALITY E-LEARNING IN HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    darsih darsih darsih

    2016-04-01

    Full Text Available ABSTRACT Assessing the quality of e-learning courses to measure the success of e-learning systems in online learning is essential. The system can be used to improve education. The study analyzes the quality of e-learning course on the web site www.kulon.undip.ac.id used a questionnaire with questions based on the variables of ISO 9126. Penilaiann Likert scale was used with a web app. Rule-base reasoning method is used to subject the quality of e-learningyang assessed. A case study conducted in four e-learning courses with 133 sample / respondents as users of the e-learning course. From the obtained results of research conducted both for the value of e-learning from each subject tested. In addition, each e-learning courses have different advantages depending on certain variables. Keywords : E-Learning, Rule-Base, Questionnaire, Likert, Measuring.

  20. Applicability of creep damage rules to a nickel-base heat-resistant alloy Hastelloy XR

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Nakajima, Najime; Tanabe, Tatsuhiko; Nakasone, Yuji

    1992-01-01

    A series of constant load and temperature creep rupture tests and varying load and/or temperature creep rupture tests was carried out on a nickel-base heat-resistant alloy Hastelloy XR, which was developed for applications in the High-Temperature Engineering Test Reactor, at temperatures ranging from 850 to 1000deg C in order to examine the applicability of the conventional creep damage rules, i.e., the life fraction, the strain fraction and their mixed rules. The life fraction rule showed the best applicability of these three criteria. The good applicability of the rule was considered to result from the fact that the creep strength of Hastelloy XR was not strongly affected by the change of the chemical composition and/or the microstructure during exposure to the high-temperature simulated HTGR helium environment. In conclusion the life fraction rule is applicable in engineering design of high-temperature components made of Hastelloy XR. (orig.)

  1. Deep Transfer Metric Learning.

    Science.gov (United States)

    Junlin Hu; Jiwen Lu; Yap-Peng Tan; Jie Zhou

    2016-12-01

    Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML, where the output of both the hidden layers and the top layer are optimized jointly. To preserve the local manifold of input data points in the metric space, we present two new methods, DTML with autoencoder regularization and DSTML with autoencoder regularization. Experimental results on face verification, person re-identification, and handwritten digit recognition validate the effectiveness of the proposed methods.

  2. Energy functionals for Calabi-Yau metrics

    International Nuclear Information System (INIS)

    Headrick, M; Nassar, A

    2013-01-01

    We identify a set of ''energy'' functionals on the space of metrics in a given Kähler class on a Calabi-Yau manifold, which are bounded below and minimized uniquely on the Ricci-flat metric in that class. Using these functionals, we recast the problem of numerically solving the Einstein equation as an optimization problem. We apply this strategy, using the ''algebraic'' metrics (metrics for which the Kähler potential is given in terms of a polynomial in the projective coordinates), to the Fermat quartic and to a one-parameter family of quintics that includes the Fermat and conifold quintics. We show that this method yields approximations to the Ricci-flat metric that are exponentially accurate in the degree of the polynomial (except at the conifold point, where the convergence is polynomial), and therefore orders of magnitude more accurate than the balanced metrics, previously studied as approximations to the Ricci-flat metric. The method is relatively fast and easy to implement. On the theoretical side, we also show that the functionals can be used to give a heuristic proof of Yau's theorem

  3. 2008 GEM Modeling Challenge: Metrics Study of the Dst Index in Physics-Based Magnetosphere and Ring Current Models and in Statistical and Analytic Specifications

    Science.gov (United States)

    Rastaetter, L.; Kuznetsova, M.; Hesse, M.; Pulkkinen, A.; Glocer, A.; Yu, Y.; Meng, X.; Raeder, J.; Wiltberger, M.; Welling, D.; hide

    2011-01-01

    In this paper the metrics-based results of the Dst part of the 2008-2009 GEM Metrics Challenge are reported. The Metrics Challenge asked modelers to submit results for 4 geomagnetic storm events and 5 different types of observations that can be modeled by statistical or climatological or physics-based (e.g. MHD) models of the magnetosphere-ionosphere system. We present the results of over 25 model settings that were run at the Community Coordinated Modeling Center (CCMC) and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations we use comparisons of one-hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of one-minute model data with the one-minute Dst index calculated by the United States Geologic Survey (USGS).

  4. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Science.gov (United States)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  5. The Finsler spacetime framework. Backgrounds for physics beyond metric geometry

    International Nuclear Information System (INIS)

    Pfeifer, Christian

    2013-11-01

    possible dependence of the speed of light on the relative motion between the observer and the light ray; modified dispersion relation and possible propagation of particle modes faster than light and the propagation of light on Finsler null-geodesics. Our Finsler spacetime framework is the first extension of the framework of general relativity based on non-metric Finslerian geometry which provides causality, observers and their measurements and gravity from a Finsler geometric spacetime structure and yields a viable background on which action based physical field theories can be defined.

  6. The Finsler spacetime framework. Backgrounds for physics beyond metric geometry

    Energy Technology Data Exchange (ETDEWEB)

    Pfeifer, Christian

    2013-11-15

    possible dependence of the speed of light on the relative motion between the observer and the light ray; modified dispersion relation and possible propagation of particle modes faster than light and the propagation of light on Finsler null-geodesics. Our Finsler spacetime framework is the first extension of the framework of general relativity based on non-metric Finslerian geometry which provides causality, observers and their measurements and gravity from a Finsler geometric spacetime structure and yields a viable background on which action based physical field theories can be defined.

  7. Asset sustainability index : quick guide : proposed metrics for the long-term financial sustainability of highway networks.

    Science.gov (United States)

    2013-04-01

    "This report provides a Quick Guide to the concept of asset sustainability metrics. Such metrics address the long-term performance of highway assets based upon expected expenditure levels. : It examines how such metrics are used in Australia, Britain...

  8. Regge calculus from discontinuous metrics

    International Nuclear Information System (INIS)

    Khatsymovsky, V.M.

    2003-01-01

    Regge calculus is considered as a particular case of the more general system where the linklengths of any two neighbouring 4-tetrahedra do not necessarily coincide on their common face. This system is treated as that one described by metric discontinuous on the faces. In the superspace of all discontinuous metrics the Regge calculus metrics form some hypersurface defined by continuity conditions. Quantum theory of the discontinuous metric system is assumed to be fixed somehow in the form of quantum measure on (the space of functionals on) the superspace. The problem of reducing this measure to the Regge hypersurface is addressed. The quantum Regge calculus measure is defined from a discontinuous metric measure by inserting the δ-function-like phase factor. The requirement that continuity conditions be imposed in a 'face-independent' way fixes this factor uniquely. The term 'face-independent' means that this factor depends only on the (hyper)plane spanned by the face, not on it's form and size. This requirement seems to be natural from the viewpoint of existence of the well-defined continuum limit maximally free of lattice artefacts

  9. Metric-based method of software requirements correctness improvement

    Directory of Open Access Journals (Sweden)

    Yaremchuk Svitlana

    2017-01-01

    Full Text Available The work highlights the most important principles of software reliability management (SRM. The SRM concept construes a basis for developing a method of requirements correctness improvement. The method assumes that complicated requirements contain more actual and potential design faults/defects. The method applies a newer metric to evaluate the requirements complexity and double sorting technique evaluating the priority and complexity of a particular requirement. The method enables to improve requirements correctness due to identification of a higher number of defects with restricted resources. Practical application of the proposed method in the course of demands review assured a sensible technical and economic effect.

  10. Primer Control System Cyber Security Framework and Technical Metrics

    Energy Technology Data Exchange (ETDEWEB)

    Wayne F. Boyer; Miles A. McQueen

    2008-05-01

    The Department of Homeland Security National Cyber Security Division supported development of a control system cyber security framework and a set of technical metrics to aid owner-operators in tracking control systems security. The framework defines seven relevant cyber security dimensions and provides the foundation for thinking about control system security. Based on the developed security framework, a set of ten technical metrics are recommended that allow control systems owner-operators to track improvements or degradations in their individual control systems security posture.

  11. The Publications Tracking and Metrics Program at NOAO: Challenges and Opportunities

    Science.gov (United States)

    Hunt, Sharon

    2015-08-01

    The National Optical Astronomy Observatory (NOAO) is the U.S. national research and development center for ground-based nighttime astronomy. The NOAO librarian manages the organization’s publications tracking and metrics program, which consists of three components: identifying publications, organizing citation data, and disseminating publications information. We are developing methods to streamline these tasks, better organize our data, provide greater accessibility to publications data, and add value to our services.Our publications tracking process is complex, as we track refereed publications citing data from several sources: NOAO telescopes at two observatory sites, telescopes of consortia in which NOAO participates, the NOAO Science Archive, and NOAO-granted community-access time on non-NOAO telescopes. We also identify and document our scientific staff publications. In addition, several individuals contribute publications data.In the past year, we made several changes in our publications tracking and metrics program. To better organize our data and streamline the creation of reports and metrics, we created a MySQL publications database. When designing this relational database, we considered ease of use, the ability to incorporate data from various sources, efficiency in data inputting and sorting, and potential for growth. We also considered the types of metrics we wished to generate from our publications data based on our target audiences and the messages we wanted to convey. To increase accessibility and dissemination of publications information, we developed a publications section on the library’s website, with citation lists, acknowledgements guidelines, and metrics. We are now developing a searchable online database for our website using PHP.The publications tracking and metrics program has provided many opportunities for the library to market its services and contribute to the organization’s mission. As we make decisions on collecting, organizing

  12. Agent-oriented enterprise modeling based on business rules

    NARCIS (Netherlands)

    Taveter, K.; Wagner, G.R.; Kunii, H.S.; Jajodia, S.; Solvberg, A.

    2001-01-01

    Business rules are statements that express (certain parts of) a business policy, defining business terms and defining or constraining the operations of an enterprise, in a declarative manner. Since these rules define and constrain the interaction among business agents in the course of business

  13. Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

    Science.gov (United States)

    Schwabe, O.; Shehab, E.; Erkoyuncu, J.

    2015-08-01

    The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis

  14. Metrics for Evaluation of Student Models

    Science.gov (United States)

    Pelanek, Radek

    2015-01-01

    Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…

  15. Toward a better comprehension of Lean metrics for research and product development management

    DEFF Research Database (Denmark)

    da Costa, Janaina Mascarenhas Hornos; Oehmen, Josef; Rebentisch, Eric

    2014-01-01

    This paper presents a compilation and empirical survey-based evaluation of the metrics most commonly used by program managers during product development management. This work is part of a bigger project of MIT, PMI and INCOSE. Three methodological procedures were applied: systematic literature...... review, focus-group discussions, and survey. The survey results indicate the metrics considered to be the most and least useful for managing lean engineering programs, and reveals a shift of interest towards qualitative metrics, especially the ones that address the achievement of stakeholder values......, and the absence of useful metrics regarding the lean principles People and Pull....

  16. A composite efficiency metrics for evaluation of resource and energy utilization

    International Nuclear Information System (INIS)

    Yang, Siyu; Yang, Qingchun; Qian, Yu

    2013-01-01

    Polygeneration systems are commonly found in chemical and energy industry. These systems often involve chemical conversions and energy conversions. Studies of these systems are interdisciplinary, mainly involving fields of chemical engineering, energy engineering, environmental science, and economics. Each of these fields has developed an isolated index system different from the others. Analyses of polygeneration systems are therefore very likely to provide bias results with only the indexes from one field. This paper is motivated from this problem to develop a new composite efficiency metrics for polygeneration systems. This new metrics is based on the second law of thermodynamics, exergy theory. We introduce exergy cost for waste treatment as the energy penalty into conventional exergy efficiency. Using this new metrics could avoid the situation of spending too much energy for increasing production or paying production capacity for saving energy consumption. The composite metrics is studied on a simplified co-production process, syngas to methanol and electricity. The advantage of the new efficiency metrics is manifested by comparison with carbon element efficiency, energy efficiency, and exergy efficiency. Results show that the new metrics could give more rational analysis than the other indexes. - Highlights: • The composite efficiency metric gives the balanced evaluation of resource utilization and energy utilization. • This efficiency uses the exergy for waste treatment as the energy penalty. • This efficiency is applied on a simplified co-production process. • Results show that the composite metrics is better than energy efficiencies and resource efficiencies

  17. TRICARE revision to CHAMPUS DRG-based payment system, pricing of hospital claims. Final rule.

    Science.gov (United States)

    2014-05-21

    This Final rule changes TRICARE's current regulatory provision for inpatient hospital claims priced under the DRG-based payment system. Claims are currently priced by using the rates and weights that are in effect on a beneficiary's date of admission. This Final rule changes that provision to price such claims by using the rates and weights that are in effect on a beneficiary's date of discharge.

  18. Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

    Directory of Open Access Journals (Sweden)

    Abdurrahim Aydın

    2016-07-01

    Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

  19. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic...

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

    Science.gov (United States)

    Frigm, Ryan Clayton; Newman, Lauri K.

    2009-01-01

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

  1. Method Points: towards a metric for method complexity

    Directory of Open Access Journals (Sweden)

    Graham McLeod

    1998-11-01

    Full Text Available A metric for method complexity is proposed as an aid to choosing between competing methods, as well as in validating the effects of method integration or the products of method engineering work. It is based upon a generic method representation model previously developed by the author and adaptation of concepts used in the popular Function Point metric for system size. The proposed technique is illustrated by comparing two popular I.E. deliverables with counterparts in the object oriented Unified Modeling Language (UML. The paper recommends ways to improve the practical adoption of new methods.

  2. Regional emission metrics for short-lived climate forcers from multiple models

    Directory of Open Access Journals (Sweden)

    B. Aamaas

    2016-06-01

    Full Text Available For short-lived climate forcers (SLCFs, the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF values calculated in four different (chemical-transport or coupled chemistry–climate models. We distinguish between emissions during summer (May–October and winter (November–April for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3, as well as ozone precursors (NOx, CO, VOCs, which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP and global temperature change potential (GTP, based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation

  3. Developing an outcome-based biodiversity metric in support of the field to market project: Final report

    Science.gov (United States)

    Drew, C. Ashton; Alexander-Vaughn, Louise B.; Collazo, Jaime A.; McKerrow, Alexa; Anderson, John

    2013-01-01

    depends on that animal’s resource specialization, mobility, and life history strategies (Jeanneret et al. 2003a, b; Jennings & Pocock 2009). The knowledge necessary to define the biodiversity contribution of agricultural lands is specialized, dispersed, and nuanced, and thus not readily accessible. Given access to clearly defined biodiversity tradeoffs between alternative agricultural practices, landowners, land managers and farm operators could collectively enhance the conservation and economic value of agricultural landscapes. Therefore, Field to Market: The Keystone Alliance for Sustainable Agriculture and The Nature Conservancy jointly funded a pilot project to develop a biodiversity metric to integrate into Field to Market’s existing sustainability calculator, The Fieldprint Calculator (http://www. fieldtomarket.org/). Field to Market: The Keystone Alliance for Sustainable Agriculture is an alliance among producers, agribusinesses, food companies, and conservation organizations seeking to create sustainable outcomes for agriculture. The Fieldprint Calculator supports the Keystone Alliance’s vision to achieve safe, accessible, and nutritious food, fiber and fuel in thriving ecosystems to meet the needs of 9 billion people in 2050. In support of this same vision, our project provides proof-of-concept for an outcome-based biodiversity metric for Field to Market to quantify biodiversity impacts of commercial row crop production on terrestrial vertebrate richness. Little research exists examining the impacts of alternative commercial agricultural practices on overall terrestrial biodiversity (McLaughlin & Mineau 1995). Instead, most studies compare organic versus conventional practices (e.g. Freemark & Kirk 2001; Wickramasinghe et al. 2004), and most studies focus on flora, avian, or invertebrate communities (Jeanneret et al. 2003a; Maes et al. 2008; Pollard & Relton 1970). Therefore, we used an expert-knowledge-based approach to develop a metric that predicts

  4. US Rocket Propulsion Industrial Base Health Metrics

    Science.gov (United States)

    Doreswamy, Rajiv

    2013-01-01

    The number of active liquid rocket engine and solid rocket motor development programs has severely declined since the "space race" of the 1950s and 1960s center dot This downward trend has been exacerbated by the retirement of the Space Shuttle, transition from the Constellation Program to the Space launch System (SLS) and similar activity in DoD programs center dot In addition with consolidation in the industry, the rocket propulsion industrial base is under stress. To Improve the "health" of the RPIB, we need to understand - The current condition of the RPIB - How this compares to past history - The trend of RPIB health center dot This drives the need for a concise set of "metrics" - Analogous to the basic data a physician uses to determine the state of health of his patients - Easy to measure and collect - The trend is often more useful than the actual data point - Can be used to focus on problem areas and develop preventative measures The nation's capability to conceive, design, develop, manufacture, test, and support missions using liquid rocket engines and solid rocket motors that are critical to its national security, economic health and growth, and future scientific needs. center dot The RPIB encompasses US government, academic, and commercial (including industry primes and their supplier base) research, development, test, evaluation, and manufacturing capabilities and facilities. center dot The RPIB includes the skilled workforce, related intellectual property, engineering and support services, and supply chain operations and management. This definition touches the five main segments of the U.S. RPIB as categorized by the USG: defense, intelligence community, civil government, academia, and commercial sector. The nation's capability to conceive, design, develop, manufacture, test, and support missions using liquid rocket engines and solid rocket motors that are critical to its national security, economic health and growth, and future scientific needs

  5. Multi-arrhythmias detection with an XML rule-based system from 12-Lead Electrocardiogram.

    Science.gov (United States)

    Khelassi, Abdeldjalil; Yelles-Chaouche, Sarra-Nassira; Benais, Faiza

    2017-05-01

    The computer-aided detection of cardiac arrhythmias stills a crucial application in medical technologies. The rule based systems RBS ensure a high level of transparency and interpretability of the obtained results. To facilitate the diagnosis of the cardiologists and to reduce the uncertainty made in this diagnosis. In this research article, we have realized a classification and automatic recognition of cardiac arrhythmias, by using XML rules that represent the cardiologist knowledge. Thirteen experiments with different knowledge bases were realized for improving the performance of the used method in the detection of 13 cardiac arrhythmias. In the first 12 experiments, we have designed a specialized knowledge base for each cardiac arrhythmia, which contains just one arrhythmia detection rule. In the last experiment, we applied the knowledge base which contains rules of 12 arrhythmias. We used, for the experiments, an international data set with 279 features and 452 records characterizing 12 leads of ECG signal and social information of patients. The data sets were constructed and published at Bilkent University of Ankara, Turkey. In addition, the second version of the self-developed software "XMLRULE" was used; the software can infer more than one class and facilitate the interpretability of the obtained results. The 12 first experiments give 82.80% of correct detection as the mean of all experiments, the results were between 19% and 100% with a low rate in just one experiment. The last experiment in which all arrhythmias are considered, the results of correct detection was 38.33% with 90.55% of sensibility and 46.24% of specificity. It was clearly show that in these results the good choice of the classification model is very beneficial in terms of performance. The obtained results were better than the published results with other computational methods for the mono class detection, but it was less in multi-class detection. The RBS is the most transparent method for

  6. Timing Metrics of Joint Timing and Carrier-Frequency Offset Estimation Algorithms for TDD-based OFDM systems

    NARCIS (Netherlands)

    Hoeksema, F.W.; Srinivasan, R.; Schiphorst, Roelof; Slump, Cornelis H.

    2004-01-01

    In joint timing and carrier offset estimation algorithms for Time Division Duplexing (TDD) OFDM systems, different timing metrics are proposed to determine the beginning of a burst or symbol. In this contribution we investigated the different timing metrics in order to establish their impact on the

  7. Issues in Benchmark Metric Selection

    Science.gov (United States)

    Crolotte, Alain

    It is true that a metric can influence a benchmark but will esoteric metrics create more problems than they will solve? We answer this question affirmatively by examining the case of the TPC-D metric which used the much debated geometric mean for the single-stream test. We will show how a simple choice influenced the benchmark and its conduct and, to some extent, DBMS development. After examining other alternatives our conclusion is that the “real” measure for a decision-support benchmark is the arithmetic mean.

  8. About a definition of metric over an abelian linearly ordered group

    Directory of Open Access Journals (Sweden)

    Bice Cavallo

    2012-06-01

    Full Text Available A G-metric over an abelian linearly ordered group G = (G,⊙,≤ is a binary operation, d G , verifying suitable properties. We consider a particular G metric derived by the group operation ⊙ and the total weak order ≤, and show that it provides a base for the order topology associated to G.

  9. Mining association rule based on the diseases population for recommendation of medicine need

    Science.gov (United States)

    Harahap, M.; Husein, A. M.; Aisyah, S.; Lubis, F. R.; Wijaya, B. A.

    2018-04-01

    Selection of medicines that is inappropriate will lead to an empty result at medicines, this has an impact on medical services and economic value in hospital. The importance of an appropriate medicine selection process requires an automated way to select need based on the development of the patient's illness. In this study, we analyzed patient prescriptions to identify the relationship between the disease and the medicine used by the physician in treating the patient's illness. The analytical framework includes: (1) patient prescription data collection, (2) applying k-means clustering to classify the top 10 diseases, (3) applying Apriori algorithm to find association rules based on support, confidence and lift value. The results of the tests of patient prescription datasets in 2015-2016, the application of the k-means algorithm for the clustering of 10 dominant diseases significantly affects the value of trust and support of all association rules on the Apriori algorithm making it more consistent with finding association rules of disease and related medicine. The value of support, confidence and the lift value of disease and related medicine can be used as recommendations for appropriate medicine selection. Based on the conditions of disease progressions of the hospital, there is so more optimal medicine procurement.

  10. Robustness of climate metrics under climate policy ambiguity

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  11. Web metrics for library and information professionals

    CERN Document Server

    Stuart, David

    2014-01-01

    This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional.Th...

  12. An Enhanced Rule-Based Web Scanner Based on Similarity Score

    Directory of Open Access Journals (Sweden)

    LEE, M.

    2016-08-01

    Full Text Available This paper proposes an enhanced rule-based web scanner in order to get better accuracy in detecting web vulnerabilities than the existing tools, which have relatively high false alarm rate when the web pages are installed in unconventional directory paths. Using the proposed matching method based on similarity score, the proposed scheme can determine whether two pages have the same vulnerabilities or not. With this method, the proposed scheme is able to figure out the target web pages are vulnerable by comparing them to the web pages that are known to have vulnerabilities. We show the proposed scanner reduces 12% false alarm rate compared to the existing well-known scanner through the performance evaluation via various experiments. The proposed scheme is especially helpful in detecting vulnerabilities of the web applications which come from well-known open-source web applications after small customization, which happens frequently in many small-sized companies.

  13. Effects of Memorization of Rule Statements on Acquisition and Retention of Rule-Governed Behavior in a Computer-Based Learning Task.

    Science.gov (United States)

    Towle, Nelson J.

    One hundred and twenty-four high school students were randomly assigned to four groups: 33 subjects memorized the rule statement before, 29 subjects memorized the rule statement during, and 30 subjects memorized the rule statement after instruction in rule application skills. Thirty-two subjects were not required to memorize rule statements.…

  14. Partial rectangular metric spaces and fixed point theorems.

    Science.gov (United States)

    Shukla, Satish

    2014-01-01

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

  15. A Kerr-NUT metric

    International Nuclear Information System (INIS)

    Vaidya, P.C.; Patel, L.K.; Bhatt, P.V.

    1976-01-01

    Using Galilean time and retarded distance as coordinates the usual Kerr metric is expressed in form similar to the Newman-Unti-Tamburino (NUT) metric. The combined Kerr-NUT metric is then investigated. In addition to the Kerr and NUT solutions of Einstein's equations, three other types of solutions are derived. These are (i) the radiating Kerr solution, (ii) the radiating NUT solution satisfying Rsub(ik) = sigmaxisub(i)xisub(k), xisub(i)xisup(i) = 0, and (iii) the associated Kerr solution satisfying Rsub(ik) = 0. Solution (i) is distinct from and simpler than the one reported earlier by Vaidya and Patel (Phys. Rev.; D7:3590 (1973)). Solutions (ii) and (iii) gave line elements which have the axis of symmetry as a singular line. (author)

  16. Rule - based Fault Diagnosis Expert System for Wind Turbine

    Directory of Open Access Journals (Sweden)

    Deng Xiao-Wen

    2017-01-01

    Full Text Available Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.

  17. Computing the Gromov hyperbolicity of a discrete metric space

    KAUST Repository

    Fournier, Hervé

    2015-02-12

    We give exact and approximation algorithms for computing the Gromov hyperbolicity of an n-point discrete metric space. We observe that computing the Gromov hyperbolicity from a fixed base-point reduces to a (max,min) matrix product. Hence, using the (max,min) matrix product algorithm by Duan and Pettie, the fixed base-point hyperbolicity can be determined in O(n2.69) time. It follows that the Gromov hyperbolicity can be computed in O(n3.69) time, and a 2-approximation can be found in O(n2.69) time. We also give a (2log2⁡n)-approximation algorithm that runs in O(n2) time, based on a tree-metric embedding by Gromov. We also show that hyperbolicity at a fixed base-point cannot be computed in O(n2.05) time, unless there exists a faster algorithm for (max,min) matrix multiplication than currently known.

  18. Background metric in supergravity theories

    International Nuclear Information System (INIS)

    Yoneya, T.

    1978-01-01

    In supergravity theories, we investigate the conformal anomaly of the path-integral determinant and the problem of fermion zero modes in the presence of a nontrivial background metric. Except in SO(3) -invariant supergravity, there are nonvanishing conformal anomalies. As a consequence, amplitudes around the nontrivial background metric contain unpredictable arbitrariness. The fermion zero modes which are explicitly constructed for the Euclidean Schwarzschild metric are interpreted as an indication of the supersymmetric multiplet structure of a black hole. The degree of degeneracy of a black hole is 2/sup 4n/ in SO(n) supergravity

  19. Daylight metrics and energy savings

    Energy Technology Data Exchange (ETDEWEB)

    Mardaljevic, John; Heschong, Lisa; Lee, Eleanor

    2009-12-31

    The drive towards sustainable, low-energy buildings has increased the need for simple, yet accurate methods to evaluate whether a daylit building meets minimum standards for energy and human comfort performance. Current metrics do not account for the temporal and spatial aspects of daylight, nor of occupants comfort or interventions. This paper reviews the historical basis of current compliance methods for achieving daylit buildings, proposes a technical basis for development of better metrics, and provides two case study examples to stimulate dialogue on how metrics can be applied in a practical, real-world context.

  20. Verification of business rules programs

    CERN Document Server

    Silva, Bruno Berstel-Da

    2013-01-01

    Rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based programming to nonprogrammers, allowing them to map expert intent into code in applications such as fraud detection, financial transactions, healthcare, retail, and marketing. However, a remaining concern is the quality, safety, and reliability of the resulting programs.  This book is on business rules programs, that is, rule programs as handled in business rules management systems. Its

  1. Improved Personalized Recommendation Based on Causal Association Rule and Collaborative Filtering

    Science.gov (United States)

    Lei, Wu; Qing, Fang; Zhou, Jin

    2016-01-01

    There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

  2. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł; Marszał-Paszek, Barbara; Moshkov, Mikhail; Paszek, Piotr; Skowron, Andrzej; Suraj, Zbigniew

    2010-01-01

    the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory

  3. Comparison of Heuristics for Inhibitory Rule Optimization

    KAUST Repository

    Alsolami, Fawaz

    2014-09-13

    Knowledge representation and extraction are very important tasks in data mining. In this work, we proposed a variety of rule-based greedy algorithms that able to obtain knowledge contained in a given dataset as a series of inhibitory rules containing an expression “attribute ≠ value” on the right-hand side. The main goal of this paper is to determine based on rule characteristics, rule length and coverage, whether the proposed rule heuristics are statistically significantly different or not; if so, we aim to identify the best performing rule heuristics for minimization of rule length and maximization of rule coverage. Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.

  4. Proposal to modify Rule 6, Rule 10a, and Rule 12c of the International Code of Nomenclature of Prokaryotes.

    Science.gov (United States)

    Oren, Aharon; Garrity, George M; Schink, Bernhard

    2014-04-01

    According to the current versions of Rule 10a and Rule 12c of the International Code of Nomenclature of Prokaryotes, names of a genus or subgenus and specific epithets may be taken from any source and may even be composed in an arbitrary manner. Based on these rules, names may be composed of any word or any combination of elements derived from any language with a Latin ending. We propose modifying these rules by adding the text, currently part of Recommendation 6, according to which words from languages other than Latin or Greek should be avoided as long as equivalents exist in Latin or Greek or can be constructed by combining word elements from these two languages. We also propose modification of Rule 6 by adopting some of the current paragraphs of Recommendation 6 to become part of the Rule.

  5. Balanced metrics for vector bundles and polarised manifolds

    DEFF Research Database (Denmark)

    Garcia Fernandez, Mario; Ross, Julius

    2012-01-01

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

  6. Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

    Science.gov (United States)

    Grimm, Lisa R; Maddox, W Todd

    2013-11-01

    Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

  7. 77 FR 52977 - Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule; Market Risk Capital Rule

    Science.gov (United States)

    2012-08-30

    ...-weighted assets for residential mortgages, securitization exposures, and counterparty credit risk. The.... Risk-Weighted Assets--Proposed Modifications to the Advanced Approaches Rules A. Counterparty Credit... Margin Period of Risk 3. Changes to the Internal Models Methodology (IMM) 4. Credit Valuation Adjustments...

  8. Unsupervised classification of lidar-based vegetation structure metrics at Jean Lafitte National Historical Park and Preserve

    Science.gov (United States)

    Kranenburg, Christine J.; Palaseanu-Lovejoy, Monica; Nayegandhi, Amar; Brock, John; Woodman, Robert

    2012-01-01

    Traditional vegetation maps capture the horizontal distribution of various vegetation properties, for example, type, species and age/senescence, across a landscape. Ecologists have long known, however, that many important forest properties, for example, interior microclimate, carbon capacity, biomass and habitat suitability, are also dependent on the vertical arrangement of branches and leaves within tree canopies. The objective of this study was to use a digital elevation model (DEM) along with tree canopy-structure metrics derived from a lidar survey conducted using the Experimental Advanced Airborne Research Lidar (EAARL) to capture a three-dimensional view of vegetation communities in the Barataria Preserve unit of Jean Lafitte National Historical Park and Preserve, Louisiana. The EAARL instrument is a raster-scanning, full waveform-resolving, small-footprint, green-wavelength (532-nanometer) lidar system designed to map coastal bathymetry, topography and vegetation structure simultaneously. An unsupervised clustering procedure was then applied to the 3-dimensional-based metrics and DEM to produce a vegetation map based on the vertical structure of the park's vegetation, which includes a flotant marsh, scrub-shrub wetland, bottomland hardwood forest, and baldcypress-tupelo swamp forest. This study was completed in collaboration with the National Park Service Inventory and Monitoring Program's Gulf Coast Network. The methods presented herein are intended to be used as part of a cost-effective monitoring tool to capture change in park resources.

  9. Endogeneously arising network allocation rules

    NARCIS (Netherlands)

    Slikker, M.

    2006-01-01

    In this paper we study endogenously arising network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some balanced

  10. The metrics of science and technology

    CERN Document Server

    Geisler, Eliezer

    2000-01-01

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

  11. Extending cosmology: the metric approach

    OpenAIRE

    Mendoza, S.

    2012-01-01

    Comment: 2012, Extending Cosmology: The Metric Approach, Open Questions in Cosmology; Review article for an Intech "Open questions in cosmology" book chapter (19 pages, 3 figures). Available from: http://www.intechopen.com/books/open-questions-in-cosmology/extending-cosmology-the-metric-approach

  12. Metrics, Media and Advertisers: Discussing Relationship

    Directory of Open Access Journals (Sweden)

    Marco Aurelio de Souza Rodrigues

    2014-11-01

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

  13. A framework for quantification of groundwater dynamics - redundancy and transferability of hydro(geo-)logical metrics

    Science.gov (United States)

    Heudorfer, Benedikt; Haaf, Ezra; Barthel, Roland; Stahl, Kerstin

    2017-04-01

    A new framework for quantification of groundwater dynamics has been proposed in a companion study (Haaf et al., 2017). In this framework, a number of conceptual aspects of dynamics, such as seasonality, regularity, flashiness or inter-annual forcing, are described, which are then linked to quantitative metrics. Hereby, a large number of possible metrics are readily available from literature, such as Pardé Coefficients, Colwell's Predictability Indices or Base Flow Index. In the present work, we focus on finding multicollinearity and in consequence redundancy among the metrics representing different patterns of dynamics found in groundwater hydrographs. This is done also to verify the categories of dynamics aspects suggested by Haaf et al., 2017. To determine the optimal set of metrics we need to balance the desired minimum number of metrics and the desired maximum descriptive property of the metrics. To do this, a substantial number of candidate metrics are applied to a diverse set of groundwater hydrographs from France, Germany and Austria within the northern alpine and peri-alpine region. By applying Principle Component Analysis (PCA) to the correlation matrix of the metrics, we determine a limited number of relevant metrics that describe the majority of variation in the dataset. The resulting reduced set of metrics comprise an optimized set that can be used to describe the aspects of dynamics that were identified within the groundwater dynamics framework. For some aspects of dynamics a single significant metric could be attributed. Other aspects have a more fuzzy quality that can only be described by an ensemble of metrics and are re-evaluated. The PCA is furthermore applied to groups of groundwater hydrographs containing regimes of similar behaviour in order to explore transferability when applying the metric-based characterization framework to groups of hydrographs from diverse groundwater systems. In conclusion, we identify an optimal number of metrics

  14. Measuring Information Security: Guidelines to Build Metrics

    Science.gov (United States)

    von Faber, Eberhard

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

  15. A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

    Science.gov (United States)

    Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

    2016-01-01

    Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

  16. A rule-based backchannel prediction model using pitch and pause information

    NARCIS (Netherlands)

    Truong, Khiet Phuong; Poppe, Ronald Walter; Heylen, Dirk K.J.

    We manually designed rules for a backchannel (BC) prediction model based on pitch and pause information. In short, the model predicts a BC when there is a pause of a certain length that is preceded by a falling or rising pitch. This model was validated against the Dutch IFADV Corpus in a

  17. Active Metric Learning for Supervised Classification

    OpenAIRE

    Kumaran, Krishnan; Papageorgiou, Dimitri; Chang, Yutong; Li, Minhan; Takáč, Martin

    2018-01-01

    Clustering and classification critically rely on distance metrics that provide meaningful comparisons between data points. We present mixed-integer optimization approaches to find optimal distance metrics that generalize the Mahalanobis metric extensively studied in the literature. Additionally, we generalize and improve upon leading methods by removing reliance on pre-designated "target neighbors," "triplets," and "similarity pairs." Another salient feature of our method is its ability to en...

  18. Multimetric indices: How many metrics?

    Science.gov (United States)

    Multimetric indices (MMI’s) often include 5 to 15 metrics, each representing a different attribute of assemblage condition, such as species diversity, tolerant taxa, and nonnative taxa. Is there an optimal number of metrics for MMIs? To explore this question, I created 1000 9-met...

  19. Noisy EEG signals classification based on entropy metrics. Performance assessment using first and second generation statistics.

    Science.gov (United States)

    Cuesta-Frau, David; Miró-Martínez, Pau; Jordán Núñez, Jorge; Oltra-Crespo, Sandra; Molina Picó, Antonio

    2017-08-01

    This paper evaluates the performance of first generation entropy metrics, featured by the well known and widely used Approximate Entropy (ApEn) and Sample Entropy (SampEn) metrics, and what can be considered an evolution from these, Fuzzy Entropy (FuzzyEn), in the Electroencephalogram (EEG) signal classification context. The study uses the commonest artifacts found in real EEGs, such as white noise, and muscular, cardiac, and ocular artifacts. Using two different sets of publicly available EEG records, and a realistic range of amplitudes for interfering artifacts, this work optimises and assesses the robustness of these metrics against artifacts in class segmentation terms probability. The results show that the qualitative behaviour of the two datasets is similar, with SampEn and FuzzyEn performing the best, and the noise and muscular artifacts are the most confounding factors. On the contrary, there is a wide variability as regards initialization parameters. The poor performance achieved by ApEn suggests that this metric should not be used in these contexts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID

    Directory of Open Access Journals (Sweden)

    Ardhyanti Mita Nugraha Joanna

    2018-01-01

    Full Text Available Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP. This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.