1,720,972 research outputs found

    Fragmented Huffman-Based Compression Methodology for CNN Targeting Resource-Constrained Edge Devices

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    In this paper, we introduce a fragmented Huffman compression methodology for compressing convolution neural networks executing on edge devices. Present scenario demands deployment of deep networks on edge devices, since application needs to adhere to low latency, enhanced security and long-term cost effectiveness. However, the primary bottleneck lies in the expanded memory footprint on account of the large size of the neural net models. Existing software implementation of deep compression strategies do exist, where Huffman compression is applied on the quantized weights, reducing the deep neural network model size. However, there is a further possibility of compression in memory footprint from a hardware design perspective in edge devices, where our proposed methodology can be complementary to the existing strategies. With this motivation, we proposed a fragmented Huffman coding methodology, that can be applied to the binary equivalent of the numeric weights of a neural network model stored in device memory. Subsequently, we also introduced the static and dynamic storage methodology on device memory space which is left behind even after storing the compressed file, that led to a big reduction in area and energy consumption of approximately 38% in case of dynamic storage methodology in comparison with static one. To the best of our knowledge, this is the first study where Huffman compression technique has been revisited by applying it to compress binary files, from a hardware design perspective, based on multiple bit pattern sequences, to achieve a maximum compression rate of 64%. A compressed hardware memory architecture and a decompression module design has also been undertaken, being synthesized at 500 MHz, using GF 40-nm low-power cell library with a nominal voltage of 1.1 V achieving a reduction of 62% dynamic power consumption with a decompression time of about 63 microseconds (μ s) without trading-off accuracy. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

    Fragmented Huffman-Based Compression Methodology for CNN Targeting Resource-Constrained Edge Devices

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    Authors would like to acknowledge the support extended by the Defence Research and Development Organization, Ministry of Defence, Government of India with the Grant reference: ERIPR/ER/202009001/M/01/1781 dated 8 February 2021 for the research project entitled "Reconfigurable Machine Learning Accelerator Design and Development for Avionics Applications." Authors would also like to acknowledge the support received by the Ministry of the Electronics and Information Technology (MEITY), Government of India toward the usage of the CAD tools as part of the Special Manpower Development (SMDP) program. The authors would also like to thank Ceremorphic Technologies Private Limited for funding and extending the tool support for carrying out few experiments

    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

    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

    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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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