1,720,988 research outputs found

    Mathematical and Simulation-Based Analysis of the Behavior of Admixed Taxa in the Neighbor-Joining Algorithm

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    The neighbor-joining algorithm for phylogenetic inference (NJ) has been seen to have three specific properties when applied to distance matrices that contain an admixed taxon: (1) antecedence of clustering, in which the admixed taxon agglomerates with one of its source taxa before the two source taxa agglomerate with each other; (2) intermediacy of distances, in which the distance on an inferred NJ tree between an admixed taxon and either of its source taxa is smaller than the distance between the two source taxa; and (3) intermediacy of path lengths, in which the number of edges separating the admixed taxon and either of its source taxa is less than or equal to the number of edges between the source taxa. We examine the behavior of neighbor-joining on distance matrices containing an admixed group, investigating the occurrence of antecedence of clustering, intermediacy of distances, and intermediacy of path lengths. We first mathematically predict the frequency with which the properties are satisfied for a labeled unrooted binary tree selected uniformly at random in the absence of admixture. We then introduce a taxon constructed by a linear admixture of distances from two source taxa, examining three admixture scenarios by simulation: a model in which distance matrices are chosen at random, a model in which an admixed taxon is added to a set of taxa that reflect treelike evolution, and a model that introduces a perturbation of the treelike scenario. In contrast to previous conjectures, we observe that the three properties are sometimes violated by distance matrices that include an admixed taxon. However, we also find that they are satisfied more often than is expected by chance when the distance matrix contains an admixed taxon, especially when evolution among the non-admixed taxa is treelike. The results contribute to a deeper understanding of the nature of evolutionary trees constructed from data that do not necessarily reflect a treelike evolutionary process

    Hybrid Ordered Statistics Decoding of Short-Length BCH Codes for URLLC Systems: Theoretical Analysis and Decoder Implementation

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    The ordered statistics decoding (OSD) algorithm has been gaining popularity for ultra-reliable and low-latency communication (URLLC) scenarios due to its near-maximum likelihood decoding performance, especially for short linear block codes. However, its substantial computational complexity hinders practical applications. In this paper, we introduce an advanced hybrid OSD algorithm that fully utilizes the hard-decision algebraic decoding results to selectively activate soft-decision OSD operations, significantly mitigating computational complexity. Through a rigorous analysis of error-correction characteristics, we derive a theoretical condition under which the hybrid OSD algorithm guarantees superior error-correction performance over the baseline OSD. To apply the proposed hybrid algorithm to the emerging URLLC systems, we also present a novel decoder architecture that efficiently integrates hard-and soft-decision operations. For (127, 64) BCH codes, the prototype decoder in a 28-nm process achieves an average processing latency of 773 ns at a target block error rate of 10(-5), improving information throughput by 4.2 x and energy-efficiency by 35 x and offering coding gain compared to previous OSD hardware designs.

    Gantt chart Simulation based Job Change Planning for LCD Industry

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    Minimizing job change leads maximizing utilization. To minimize job change, the efficient job change plan is needed. But the process of job change is very time-consuming and hard to consider various constraints such as job change crew, work in progress (WIP), tool and availability of equipment. In this paper, the simulation of constructing the Gantt chart for efficient job change planning in LCD industry is proposed as it is called Gantt chart simulation (GCS

    Energy-Efficient Intelligent EPTS Device using Novel DCNN-Based Dynamic Sensor Activation

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    The electronic performance and tracking system (EPTS) device is one of the wearable devices widely used to gather sports data of athletes in real-Time. This work demonstrates an adaptive sampling strategy controlled by the advanced on-device deep convolutional neural network (DCNN) operation, extending the lifetime of EPTS device even realized in a small form factor.1

    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
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