2,814 research outputs found

    n+1 Dimensional Gravity duals to quantum criticalities with spontaneous symmetry breaking

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    We reexamine the charged AdS domain wall solution to the Einstein-Abelian-Higgs model proposed by Gubser et al as holographic superconductors at quantum critical points and comment on their statement about the uniqueness of gravity solutions. We generalize their explorations from 3+1 dimensions to arbitrary n+1n+1Ds and find that the n+1⩾5n+1\geqslant5D charged AdS domain walls are unstable against electric perturbations.Comment: version to appear in commun. theor. phy

    Early Accurate Results for Advanced Analytics on MapReduce

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    Approximate results based on samples often provide the only way in which advanced analytical applications on very massive data sets can satisfy their time and resource constraints. Unfortunately, methods and tools for the computation of accurate early results are currently not supported in MapReduce-oriented systems although these are intended for `big data'. Therefore, we proposed and implemented a non-parametric extension of Hadoop which allows the incremental computation of early results for arbitrary work-flows, along with reliable on-line estimates of the degree of accuracy achieved so far in the computation. These estimates are based on a technique called bootstrapping that has been widely employed in statistics and can be applied to arbitrary functions and data distributions. In this paper, we describe our Early Accurate Result Library (EARL) for Hadoop that was designed to minimize the changes required to the MapReduce framework. Various tests of EARL of Hadoop are presented to characterize the frequent situations where EARL can provide major speed-ups over the current version of Hadoop.Comment: VLDB201

    Optimization of support structures for selective laser melting.

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    Additive Manufacturing (AM) users rely on experiments and experience to predict the performance of AM processes. This trial and error approach for qualifying AM parts takes significant time and money. Simulation tools are an urgent need for today’s AM industry. One area of need is the automatic generation of optimized support structures based upon the scan patterns used to produce those structures. This research seeks to develop support structure generation tools based on real scan pattern and thermo-mechanical simulation tools for Selective Laser Melting (SLM) developed at the University of Louisville and being commercialized by 3DSIM, LLC. In order to benchmark the 3DSIM thermo-mechanical simulation tool, a thermal finite element model has been developed in ANSYS which uses the similar multi-scale meshing strategies as 3DSIM. The use of the sub-modeling approach for dynamic meshing was verified by comparing it against a uniform fine mesh model. The results of the two models match within an acceptable tolerance. Also, a mesh sensitivity analysis was carried out in order to show solution convergence as a function of increasing mesh density. The results of this analysis were also validated using experiments to show a match between experimental and simulated melt pools. Finally, the ANSYS solution was compared with 3DSIM results. The result of 3DSIM for a simple represented model is validated compared against the ANSYS model. What is more, it was significantly faster than their ANSYS counterparts for solving problems using a dynamic mesh. A scan pattern generation tool has been implemented to enable the input of real scan patterns as it is used in fabrication. The scan pattern is arbitrarily varied using user-defined parameters including hatching space, orientation angle, scanning start point, etc. Several types of scan patterns such as traditional S and chessboard are included in the tool. A simplified representation of the thermomechanical properties of support structures in order to accelerate the simulation of supports has been formulated. The effective thermal properties of support structures are represented using thermal homogenization. The effective thermal properties of the support structures have been found to be a function of their geometry, anisotropy and constituent independent thermal properties. The results from this study have been compared against standard models and a good match has been found. A novel framework for a support structure generation and optimization tool has been developed to overcome the difficulty of dealing with support structures in SLM. Supports are optimized and designed based on the thermal stress accumulated in parts as they are made as well as geometrical rules. The support structure is designed to be withstand the thermal stress at locations where it could cause damage to the part and support structure, while minimizing the overall need for support structure materials. The support structure is designed with non-uniform parameters so as to make it flexible to alter based upon thermal stress. Experiments were conducted to explore the threshold for block support structure parameters and results were applied to adjust and verify the tool

    Preference Mining Using Neighborhood Rough Set Model on Two Universes

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    Preference mining plays an important role in e-commerce and video websites for enhancing user satisfaction and loyalty. Some classical methods are not available for the cold-start problem when the user or the item is new. In this paper, we propose a new model, called parametric neighborhood rough set on two universes (NRSTU), to describe the user and item data structures. Furthermore, the neighborhood lower approximation operator is used for defining the preference rules. Then, we provide the means for recommending items to users by using these rules. Finally, we give an experimental example to show the details of NRSTU-based preference mining for cold-start problem. The parameters of the model are also discussed. The experimental results show that the proposed method presents an effective solution for preference mining. In particular, NRSTU improves the recommendation accuracy by about 19% compared to the traditional method

    Opportunistic Routing in Multihop Wireless Networks: Capacity, Energy Efficiency, and Security

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    Opportunistic routing (OR) takes advantages of the spatial diversity and broadcast nature of wireless networks to combat the time-varying links by involving multiple neighboring nodes (forwarding candidates) for each packet relay. This dissertation studies the properties, energy efficiency, capacity, throughput, protocol design and security issues about OR in multihop wireless networks. Firstly, we study geographic opportunistic routing (GOR), a variant of OR which makes use of nodes\u27 location information. We identify and prove three important properties of GOR. The first one is on prioritizing the forwarding candidates according to their geographic advancements to the destination. The second one is on choosing the forwarding candidates based on their advancements and link qualities in order to maximize the expected packet advancement (EPA) with different number of forwarding candidates. The third one is on the concavity of the maximum EPA in respect to the number of forwarding candidates. We further propose a local metric, EPA per unit energy consumption, to tradeoff the routing performance and energy efficiency for GOR. Leveraging the proved properties of GOR, we propose two efficient algorithms to select and prioritize forwarding candidates to maximize the local metric. Secondly, capacity is a fundamental issue in multihop wireless networks. We propose a framework to compute the end-to-end throughput bound or capacity of OR in single/multirate systems given OR strategies (candidate selection and prioritization). Taking into account wireless interference and unique properties of OR, we propose a new method of constructing transmission conflict graphs, and we introduce the concept of concurrent transmission sets to allow the proper formulation of the maximum end-to-end throughput problem as a maximum-flow linear programming problem subject to the transmission conflict constraints. We also propose two OR metrics: expected medium time (EMT) and expected advancement rate (EAR), and the corresponding distributed and local rate and candidate set selection schemes, the Least Medium Time OR (LMTOR) and the Multirate Geographic OR (MGOR). We further extend our framework to compute the capacity of OR in multi-radio multi-channel systems with dynamic OR strategies. We study the necessary and sufficient conditions for the schedulability of a traffic demand vector associated with a transmitter to its forwarding candidates in a concurrent transmission set. We further propose an LP approach and a heuristic algorithm to obtain an opportunistic forwarding strategy scheduling that satisfies a traffic demand vector. Our methodology can be used to calculate the end-to-end throughput bound of OR in multi-radio/channel/rate multihop wireless networks, as well as to study the OR behaviors (such as candidate selection and prioritization) under different network configurations. Thirdly, protocol design of OR in a contention-based medium access environment is an important and challenging issue. In order to avoid duplication, we should ensure only the best receiver of each packet to forward it in an efficient way. We investigate the existing candidate coordination schemes and propose a fast slotted acknowledgment (FSA) to further improve the performance of OR by using a single ACK to coordinate the forwarding candidates with the help of the channel sensing technique. Furthermore, we study the throughput of GOR in multi-rate and single-rate systems. We introduce a framework to analyze the one-hop throughput of GOR, and provide a deeper insight on the trade-off between the benefit (packet advancement, bandwidth, and transmission reliability) and cost (medium time delay) associated with the node collaboration. We propose a local metric named expected one-hop throughput (EOT) to balance the benefit and cost. Finally, packet reception ratio (PRR) has been widely used as an indicator of the link quality in multihop wireless networks. Many routing protocols including OR in wireless networks depend on the PRR information to make routing decision. Providing accurate link quality measurement (LQM) is essential to ensure the right operation of these routing protocols. However, the existing LQM mechanisms are subject to malicious attacks, thus can not guarantee to provide correct link quality information. We analyze the security vulnerabilities in the existing link quality measurement (LQM) mechanisms and propose an efficient broadcast-based secure LQM (SLQM) mechanism, which prevents the malicious attackers from reporting a higher PRR than the actual one. We analyze the security strength and the cost of the proposed mechanism

    Numerical and experimental investigations of self-piercing riveting

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    Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. With increasing application of SPR in different industrial fields, the demand for a better understanding of the knowledge of static and dynamic characteristics of the SPR joints is required. In this paper, the SPR process has been numerically simulated using the commercial finite element (FE) software LS-Dyna. For validating the numerical simulation of the SPR process, experimental tests on specimens made of aluminium alloy have been carried out. The online window monitoring technique was introdu introdu ced in the tests for evaluating the quality of SPR joints. Good agreements between the simulations and the tests have been found, both with respect to the force-travel (time) curves as well as the deformed shape on the cross-section of SPR joint. Monotonic tensile tests were carried out to measure the ultimate tensile strengths for SPR joints with different material combinations. Deformation and failure of the SPR joints under monotonic tensile loading were studied. The normal hypothesis tests were performed to examine the rationality of the test data. This work was also aimed at evaluating experimentally and comparing the strength and energy absorption of SPR joints and SPR-bonded hybrid joints

    Estimating Selection Intensity on Synonymous Codon Usage in a Nonequilibrium Population

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    Codon usage bias is the nonrandom use of synonymous codons for the same amino acid. Most population genetic models of codon usage evolution assume that the population is at mutation–selection–drift equilibrium. Natural populations, however, frequently deviate from equilibrium, often because of recent demographic changes. Here, we construct a matrix model that includes the effects of a recent change in population size on estimates of selection on preferred vs. unpreferred codons. Our results suggest that patterns of synonymous polymorphisms affecting codon usage can be quite erratic after such a change; statistical methods that fail to take demographic effects into account can then give incorrect estimates of important parameters. We propose a new method that can accurately estimate both demographic and codon usage parameters. The method also provides a simple way of testing for the effects of covariates such as gene length and level of gene expression on the intensity of selection, which we apply to a large Drosophila melanogaster polymorphism data set. Our analyses of twofold degenerate codons reveal that (i) selection acts in favor of preferred codons, (ii) there is mutational bias in favor of unpreferred codons, (iii) shorter genes and genes with higher expression levels are under stronger selection, and (iv) there is little evidence for a recent change in population size in the Zimbabwe population of D. melanogaster
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