11,751 research outputs found

    Adaptive imputation of missing values for incomplete pattern classification

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    In classification of incomplete pattern, the missing values can either play a crucial role in the class determination, or have only little influence (or eventually none) on the classification results according to the context. We propose a credal classification method for incomplete pattern with adaptive imputation of missing values based on belief function theory. At first, we try to classify the object (incomplete pattern) based only on the available attribute values. As underlying principle, we assume that the missing information is not crucial for the classification if a specific class for the object can be found using only the available information. In this case, the object is committed to this particular class. However, if the object cannot be classified without ambiguity, it means that the missing values play a main role for achieving an accurate classification. In this case, the missing values will be imputed based on the K-nearest neighbor (K-NN) and self-organizing map (SOM) techniques, and the edited pattern with the imputation is then classified. The (original or edited) pattern is respectively classified according to each training class, and the classification results represented by basic belief assignments are fused with proper combination rules for making the credal classification. The object is allowed to belong with different masses of belief to the specific classes and meta-classes (which are particular disjunctions of several single classes). The credal classification captures well the uncertainty and imprecision of classification, and reduces effectively the rate of misclassifications thanks to the introduction of meta-classes. The effectiveness of the proposed method with respect to other classical methods is demonstrated based on several experiments using artificial and real data sets

    Median evidential c-means algorithm and its application to community detection

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    Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed. The median variant relaxes the restriction of a metric space embedding for the objects but constrains the prototypes to be in the original data set. Due to these properties, MECM could be applied to graph clustering problems. A community detection scheme for social networks based on MECM is investigated and the obtained credal partitions of graphs, which are more refined than crisp and fuzzy ones, enable us to have a better understanding of the graph structures. An initial prototype-selection scheme based on evidential semi-centrality is presented to avoid local premature convergence and an evidential modularity function is defined to choose the optimal number of communities. Finally, experiments in synthetic and real data sets illustrate the performance of MECM and show its difference to other methods

    Evidential Label Propagation Algorithm for Graphs

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    Community detection has attracted considerable attention crossing many areas as it can be used for discovering the structure and features of complex networks. With the increasing size of social networks in real world, community detection approaches should be fast and accurate. The Label Propagation Algorithm (LPA) is known to be one of the near-linear solutions and benefits of easy implementation, thus it forms a good basis for efficient community detection methods. In this paper, we extend the update rule and propagation criterion of LPA in the framework of belief functions. A new community detection approach, called Evidential Label Propagation (ELP), is proposed as an enhanced version of conventional LPA. The node influence is first defined to guide the propagation process. The plausibility is used to determine the domain label of each node. The update order of nodes is discussed to improve the robustness of the method. ELP algorithm will converge after the domain labels of all the nodes become unchanged. The mass assignments are calculated finally as memberships of nodes. The overlapping nodes and outliers can be detected simultaneously through the proposed method. The experimental results demonstrate the effectiveness of ELP.Comment: 19th International Conference on Information Fusion, Jul 2016, Heidelber, Franc

    Evidential relational clustering using medoids

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    In real clustering applications, proximity data, in which only pairwise similarities or dissimilarities are known, is more general than object data, in which each pattern is described explicitly by a list of attributes. Medoid-based clustering algorithms, which assume the prototypes of classes are objects, are of great value for partitioning relational data sets. In this paper a new prototype-based clustering method, named Evidential C-Medoids (ECMdd), which is an extension of Fuzzy C-Medoids (FCMdd) on the theoretical framework of belief functions is proposed. In ECMdd, medoids are utilized as the prototypes to represent the detected classes, including specific classes and imprecise classes. Specific classes are for the data which are distinctly far from the prototypes of other classes, while imprecise classes accept the objects that may be close to the prototypes of more than one class. This soft decision mechanism could make the clustering results more cautious and reduce the misclassification rates. Experiments in synthetic and real data sets are used to illustrate the performance of ECMdd. The results show that ECMdd could capture well the uncertainty in the internal data structure. Moreover, it is more robust to the initializations compared with FCMdd.Comment: in The 18th International Conference on Information Fusion, July 2015, Washington, DC, USA , Jul 2015, Washington, United State

    Erneley Close passive house retrofit : resident experiences and building performance in retrofit to passive house standard

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    In May 2015, Eastlands Housing (now One Manchester) completed work on its retrofit to PassivHaus equivalent (EnerPHit) standard of 32 social housing flats in two blocks in Erneley Close, in the Manchester area Gorton. With a budget of £3.1 million, it was intended that the development would reduce energy bills, create new community greenspace and make the area a destination of choice (PassivHaus Trust 2015). Over the period December 2015 to February 2016, researchers at the Sustainable Housing and Urban Studies Unit (SHUSU) and the Applied Buildings and Energy Research Group (ABERG) monitored the thermal performance of the buildings and interviewed residents to understand their experiences of both the retrofit process and living in their retrofitted-flats. The research contributes to a nascent literature on retrofit of social housing to EnerPHit levels and to a broader literature base on processes and outcomes of retrofit across the UK housing stock. It finds broadly positive outcomes from the Erneley Close improvements, with monitoring indicating high expected comfort levels and the majority of tenants expressing satisfaction with the thermal performance of the flats and the heating systems. As with any major development, there are lessons that can be learnt, and opportunities to enhance the work: these relate primarily to ensuring residents, including vulnerable groups, understand fully how to get the best out of their retrofitted flats; and addressing some non-energy related tenant concerns. The report begins with an overview of the EnerPHit standard (Chapter 2), before outlining the methodology (Chapter 3). Chapters 4 and 5 present the findings from the qualitative interviews and the physical monitoring respectively. Finally, Chapter 6 offers a set of recommendations that relate to this and future social housing energy retrofit

    Search for Low-Scale Technicolor in ATLAS

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    The low scale technicolor is an appealing scenario of strong ewsb. It has a rich phenomenology which can be tested at the LHC. A very characteristic signal would involve the observation of a technipion in resonance with a Standard Model gauge boson. A fast simulation analysis of the process ppρT±πT±Zbjp p \to \rho_{T}^{\pm} \to \pi_{T}^{\pm} Z \to bj \ell\ell and ppaT±πT±Zbjp p \to a_{T}^{\pm} \to \pi_{T}^\pm Z \to bj \ell\ell for three representative sets of masses for the new particles suggests that the technirho and technipion could be observed with 15\sim 15 fb1^{-1}, and that the aTa_{T} could be observed simultaneously with the ρT\rho_{T} and πT\pi_{T} within a year or more of running at the LHC

    Evaluating Maintainability Prejudices with a Large-Scale Study of Open-Source Projects

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    Exaggeration or context changes can render maintainability experience into prejudice. For example, JavaScript is often seen as least elegant language and hence of lowest maintainability. Such prejudice should not guide decisions without prior empirical validation. We formulated 10 hypotheses about maintainability based on prejudices and test them in a large set of open-source projects (6,897 GitHub repositories, 402 million lines, 5 programming languages). We operationalize maintainability with five static analysis metrics. We found that JavaScript code is not worse than other code, Java code shows higher maintainability than C# code and C code has longer methods than other code. The quality of interface documentation is better in Java code than in other code. Code developed by teams is not of higher and large code bases not of lower maintainability. Projects with high maintainability are not more popular or more often forked. Overall, most hypotheses are not supported by open-source data.Comment: 20 page

    A Time Series Analysis of Air Pollution and Preterm Birth in Pennsylvania, 1997–2001

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    Preterm delivery can lead to serious infant health outcomes, including death and lifelong disability. Small increases in preterm delivery risk in relation to spatial gradients of air pollution have been reported, but previous studies may have controlled inadequately for individual factors. Using a time-series analysis, which eliminates potential confounding by individual risk factors that do not change over short periods of time, we investigated the effect of ambient outdoor particulate matter with diameter ≤10 μm (PM(10)) and sulfur dioxide on risk for preterm delivery. Daily counts of preterm births were obtained from birth records in four Pennsylvania counties from 1997 through 2001. We observed increased risk for preterm delivery with exposure to average PM(10) and SO(2) in the 6 weeks before birth [respectively, relative risk (RR) = 1.07; 95% confidence interval (CI), 0.98–1.18 per 50 μg/m(3) increase; RR = 1.15; 95% CI, 1.00–1. 32 per 15 ppb increase], adjusting for long-term preterm delivery trends, co-pollutants, and offsetting by the number of gestations at risk. We also examined lags up to 7 days before the birth and found an acute effect of exposure to PM(10) 2 days and 5 days before birth (respectively, RR = 1.10; 95% CI, 1.00–1.21; RR = 1.07; 95% CI, 0.98–1.18) and SO(2) 3 days before birth (RR = 1.07; 95% CI, 0.99–1.15), adjusting for covariates, including temperature, dew point temperature, and day of the week. The results from this time-series analysis, which provides evidence of an increase in preterm birth risk with exposure to PM(10) and SO(2), are consistent with prior investigations of spatial contrasts

    Theoretical Uncertainties in Electroweak Boson Production Cross Sections at 7, 10, and 14 TeV at the LHC

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    We present an updated study of the systematic errors in the measurements of the electroweak boson cross-sections at the LHC for various experimental cuts for a center of mass energy of 7, 10 and 14 TeV. The size of both electroweak and NNLO QCD contributions are estimated, together with the systematic error from the parton distributions. The effects of new versions of the MSTW, CTEQ, and NNPDF PDFs are considered.Comment: PDFLatex with JHEP3.cls. 22 pages, 43 figures. Version 2 adds the CT10W PDF set to analysis and updates the final systematic error table and conclusions, plus several citations and minor wording changes. Version 3 adds some references on electroweak and mixed QED/QCD corrections. Version 4 adds more references and acknowledgement
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