1,721,021 research outputs found
Bayesian fuzzy hypothesis test in wireless sensor networks with noise uncertainty
No full textReliable event detection is an essential task of wireless sensor networks (WSNs) in which there are different types of uncertainty. In this paper, we consider a decentralized detection problem for a WSN and use fuzzy hypothesis test (FHT) in the Bayesian perspective to model the noise power uncertainty. FHT employs membership functions as hypotheses for modeling and analyzing the uncertainty. Using Bayesian FHT (BFHT), a local detector scheme is proposed at each sensor node in which the threshold depends on the noise power uncertainty bound. Local decisions of sensors are sent to the fusion center (FC) and combined to make a final decision about the absence/presence of the event. The proposed algorithm is evaluated in terms of probabilities of detection and false alarm. Simulations show that the proposed BFHT detector considerably outperforms the Anderson–Darling method as well as the conventional energy detector in the presence of the noise power uncertainty
Fusion of Local Decisions based on Rao test in Resource-constrained Sensor Networks
No full textDetection is a basic task of a wireless sensor network (WSN). To meet severe bandwidth and energy limitations of WSNs, network nodes are usually programmed to decide locally about a desired event occurrence and send just one bit to a fusion center (FC) wherein an optimum decision must be taken. In this paper, we employ the Rao test for fusing local decisions of nodes. The Rao test is well-known for its much lower computational complexity than the more common (but computationally heavier) generalized likelihood ratio test (GLRT). We obtain the closed forms of the Rao-test-based fusion rules in both homogeneous and heterogeneous WSNs in the presence of imperfect communication channels. The importance of the presented formulations lies in their simplicity while taking practical issues into account. We show that the Rao-test-based decision fusion in homogeneous WSNs coincides with the counting rule (CR). Moreover, simple methods of adjusting local detection thresholds are proposed. The effectiveness of RAPID in the improvement of the overall network performance is shown through simulations in different scenarios
Modelling a successful performance measurement system
No full textThe performance measurement system (PMS) is one of the complex but most important systems in an organisation. Adopting a PMS is not a simple tecnical procedure and takes a lot of time, effort and resources. But could an organisation really have a successful PMS without an understanding of its requirements and critical success factors (CSF) and what are the enablers and barriers to the achievment of a successful PMS? This paper develops a successful PMS model, laying down a path for how to effectively operate a PMS successfully within an organisation. In particular the BSc is scrutinise
Bandwidth-constrained Decentralized Detection of an Unknown Vector Signal via Multisensor Fusion
No full textDecentralized detection is one of the key tasks that a wireless sensor network (WSN) is faced to accomplish. Among several decision criteria, the Rao test is able to cope with an unknown (but parametrically-specified) sensing model, while keeping computational simplicity. To this end, the Rao test is employed in this paper to fuse multivariate data measured by a set of sensor nodes, each observing the target (or the desired) event via a non-linear mapping function. In order to meet stringent energy/bandwidth requirements, sensors quantize their vector-valued observations into one or few bits and send them over error-prone (to model low-power communications) reporting channels to a fusion center (FC). Therein, a global (better) decision is taken via the proposed test. Its closed form and asymptotic (large-size WSN) performance are obtained, and the latter leveraged to optimize quantizers. The appeal of the proposed approach is confirmed via simulations
Learning Wireless Sensor Networks for Source Localization
No full textSource localization and target tracking are among the most challenging problems in wireless sensor networks (WSN). Most of the state-of-the-art solutions are complicated and do not meet the processing and memory limitations of the existing low-cost sensor nodes. In this paper, we propose computationally-cheap solutions based on the support vector machine (SVM) and twin SVM (TWSVM) learning algorithms in which network nodes firstly detect the desired signal. Then, the network is trained to specify the nodes in the vicinity of the source (or target); hence, the region of event is detected. Finally, the centroid of the event region is considered as an estimation of the source location. The efficiency of the proposed methods is shown by simulations
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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