1,720,968 research outputs found

    Simplified Log-MAP Algorithm for Very Low-Complexity Turbo Decoder Hardware Architectures

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    Motivated by the importance of hardware implementation in practical turbo decoders, a simplified, yet effective, n-input max∗ approximation algorithm is proposed with the aim being its efficient implementation for very low-complexity turbo decoder hardware architectures. The simplification is obtained using an appropriate digital circuit for finding the first two maximum values in a set of n data that embeds the computation of a correction term. Various implementation results show that the proposed architecture is simpler by 30%, on average, than the constant logarithmic-maximum a posteriori (Log-MAP) one, in terms of chip area with the same delay. This comes at the expense of very small performance degradation, in the order of 0.1 dB for up to moderate bit error rates, e.g., 10e−5, assuming binary turbo codes. However, when applying scaling to the extrinsic information, the proposed algorithm achieves almost identical Log-MAP turbo code performance for both binary and double-binary turbo codes, without increasing noticeably the implementation complexity

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

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    “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

    A Tight Lower Bound for the Symbol Error Performance of the Uplink Sparse Code Multiple Access

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    We derive a tight lower bound for symbol error rate (SER) performance of the sparse code multiple access (SCMA) uplink operated over Rayleigh fading channels. In particular, based on the working principle of message passing algorithm receiver and the special structure of the sparse binary matrix, which is used to control the collisions of SCMA system, the system can be simplified to a single user single input multiple output (SU-SIMO) system employing maximal ratio combining (MRC) reception. In this way, the average SER lower bound of SCMA is obtained by calculating the average SER of SU-SIMO system employing MRC reception. Our results show that the derived lower bound is not only an efficient means of analyzing the SER performance, but also is tight, especially in the high signal-to-noise ratio regime. © 2012 IEEE

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We 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

    A Novel Methodology for HYIP Operators' Bitcoin Addresses Identification

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    Bitcoin is one of the most popular decentralized cryptocurrencies to date. However, it has been widely reported that it can be used for investment scams, which are referred to as high yield investment programs (HYIP). Although from the security forensic point of view it is very important to identify the HYIP operators' Bitcoin addresses, so far in the open technical literature no systematic method which reliably collects and identifies such Bitcoin addresses has been proposed. In this paper, a novel methodology is introduced, which efficiently collects a large number of the HYIP operators' Bitcoin addresses and identifies them based upon a novel analysis of their transactions history. In particular, a scraping-based method is first proposed which is able to collect more than 2,000 HYIP operators' Bitcoin addresses from the Internet thus providing a large number of the HYIPs' samples. Second, a supervised machine learning technique, which classifies, whether or not, specific Bitcoin addresses belong to the HYIP operators, is introduced and its performance is evaluated. The proposed classification method is based upon two novel approaches, namely the rate conversion technique that mitigates the effect of Bitcoin price volatility and the sampling technique that reduces the computational amount without sacrificing the classification performance. By employing close to 30,000 real Bitcoin addresses, extensive performance evaluation results obtained by means of computer simulation experiments have shown that the proposed methodology achieves excellent performance, i.e., 95% of the HYIP addresses can be correctly classified, while maintaining a false positive rate less than 4.9%. In order to further validate the proposed classifier's ability to detect the HYIP operators' Bitcoin addresses, our designed classifier has been tested against a recently published list of the HYIP addresses maintaining its excellent detection accuracy by achieving a 93.75% success rate. © 2013 IEEE

    Dispelling the Myths Behind First-author Citation Counts

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    We 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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