11,828 research outputs found

    On the Scalability of Ad Hoc Wireless Networks

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    ... considers the problem of scaling ad hoc wireless networks now being applied to urban mesh and sensor networks scenarios. Ad hoc networks involve multi-hop communication which has inherent scaling problems in that throughput per node drops as the square root of the number of nodes in the network. We investigate mechanisms for improving performance and scalability of multi-hop wireless networks, with focus on system architecture and routing protocol aspects. First we propose a generalized multi-tier hierarchical hybrid network with three tiers of radio nodes: low-power end-user mobile nodes (MN) at the lowest tier, higher power radio forwarding nodes (FN) that support multi-hop routing at intermediate level, and wired access points (AP) at the highest level. We present an analytical model for the capacity of the proposed network and identify conditions on transmission range and node density for scalability to be maintained. From the derived upper and lower bounds, it is shown that the low-tier capacity increase linearly with the number of FN’s, and the high-tier capacity grows linearly with the number of AP’s in the scaling region. The analytically obtained capacity results are validated with detailed system simulations for dense network scenarios. The simulation study also examines the allocation of separate channels t

    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

    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

    Raw data of Zhao et al., 2022, Geoderma

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    Raw data associated with Zhao et al., 2022, Geoderma. Any use of the data set should be approved by the corresponding author Kai Yue at "[email protected]".</p

    Chao Yuen Ren (1892–1982)

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    Y. R. Chao is easily the most famous linguist to have come out of China. Born before the end of the last dynasty in China, he received a traditional Confucian education, but was also one of the first Chinese people to be sent to the West for training in modern Western science (under the Boxer Indemnity Fund). The remarkable breadth and scope of his studies included physics, mathematics, linguistics, musical and literary composition, and translation, and he was a pioneer in many of these fields

    Gated relational stacked denoising autoencoder with localized author embedding for global citation recommendation

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    Citation recommendation is an effective and efficient way to facilitate authors finding desired references. This paper presents a novel neural network based model, called gated relational probabilistic stacked denoising autoencoder with localized author (GRSLA) embedding, for global citation recommendation task. Our model is comprised of two modules with different neural network architecture. For each citing and cited papers, we use a gated paper embedding module, which is extended from probabilistic stacked denoising autoencoder (PSDAE) by adding gated units, to obtain their paper vectors. The added gated units are able to utilize text information of cited paper to refine the vector representation of citing paper in multiple semantic levels. For an author in papers, we first apply topic model to obtain his/her semantic neighbors, and then use a localized author embedding (LAE) module to excavate author vector representation from semantic and explicit neighbors. Unlike most graph convolutional network (GCN) based methods, the LAE module is able to avoid computing global Laplacian in whole graph by taking limited neighbors. Moreover, the LAE module can also be stacked to absorb more neighbors, which makes our model have high extendibility. Based on the generation process of GRSLA, we also derive a learning algorithm of our model by maximum a posteriori (MAP) estimation. We conduct experiments on the AAN, DBLP and CORD-19 datasets, and the results show that GRSLA model works well than previous global citation recommendation methods

    Modeling nitrogen nutrient loss and ammonia emissions from animal farms

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    Author institution (Zhao): Department of Food, Agricultural, and Biological Engineering, The Ohio State Universit

    Creating a versatile toolkit for transgene expression using BACS and for dissecting large-scale chromatin organization

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    In eukaryotes, the genetic material, DNA, is highly compacted with histone proteins to form chromatin in interphase nuclei. Both the higher levels of chromatin folding and the spatial organization of the chromatin, referred to as large-scale chromatin organization, have been shown to correlate with transcriptional activity. One example suggesting transcriptional regulation by large-scale chromatin organization is position effects and position effect variegations observed in transgene expressions, which, as well as other epigenetic silencing mechanisms, have been obstacles to achieving predictable and stable transgene expression. Molecular dissections of the determinants regulating large-scale chromatin organization would help to elucidate the real relationship between large-scale chromatin organization and transcriptional regulation, yet are difficult due to the complexity of the mammalian genome. Bacterial artificial chromosomes (BACs), containing 100-300 kb mammalian genomic regions have been shown to recapitulate the expression level and nuclear localization of the corresponding genomic regions, and to protect embedded reporter mini-genes from epigenetic silencing. Here in Chapter 2 we show that BACs could provide a versatile platform for achieving reproducible, stable simultaneous expression of multiple transgenes maintained either as episomes or stably integrated copies. Moreover, in Chapter 3 we show that BACs could be used as a powerful model system for dissecting mechanisms regulating large-scale chromatin organization, by demonstrating distinctive large-scale chromatin conformations formed by BAC transgene arrays and results indicating separation of large-scale chromatin compaction, nuclear localization and transcriptional activities.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-08-01The student, Binhui Zhao, accepted the attached license on 2019-07-08 at 10:18.The student, Binhui Zhao, submitted this Dissertation for approval on 2019-07-08 at 10:21.This Dissertation was approved for publication on 2019-07-09 at 11:09.DSpace SAF Submission Ingestion Package generated from Vireo submission #14187 on 2019-11-26 at 14:01:40Made available in DSpace on 2019-11-26T20:59:34Z (GMT). No. of bitstreams: 6 ZHAO-DISSERTATION-2019.pdf: 26618993 bytes, checksum: a723c4768be1bc6b7689280fee7a7fdd (MD5) Data_A.1.xlsx: 20241 bytes, checksum: c091c32881710eb6fce15319f827a38e (MD5) Data_C.1.gb: 7789 bytes, checksum: 7fa320989f4ec55546f060e2e151c6f4 (MD5) Data_D.1.txt: 3631746 bytes, checksum: 6377916d412e8e32279b56baf9b584cf (MD5) Data_D.2.txt: 4050 bytes, checksum: c15c51153258ad1657a476992327f5cb (MD5) LICENSE.txt: 4208 bytes, checksum: b56be6e5b1b12f5701f578371a4e65ce (MD5) Previous issue date: 2019-07-09Embargo set by: Seth Robbins for item 113056 Lift date: 2021-11-26T20:59:54Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 113056 on 2021-11-27T10:15:09Z
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