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  • Articles  (3,061)
  • Hindawi  (2,570)
  • American Institute of Physics (AIP)  (491)
  • Public Library of Science
  • 2020-2024
  • 2015-2019  (3,061)
  • International Journal of Distributed Sensor Networks  (1,339)
  • Chaos  (491)
  • Advances in High Energy Physics  (474)
  • 163708
  • 1757
  • 92585
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  • Articles  (3,061)
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  • 1
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    Study on the Weak Decays (2015)
    Hindawi
    Details
    Publication Date: 2015-08-11
    Description: Motivated by the prospects of the potential particle at high-luminosity heavy-flavor experiments, we studied the weak decays, where = , , . The nonfactorizable contributions to hadronic matrix elements are taken into consideration with the QCDF approach. It is found that the CKM-favored decay has branching ratio of , which might be measured promisingly by the future experiments.
    Print ISSN: 1687-7357
    Electronic ISSN: 1687-7365
    Topics: Physics
    Published by Hindawi
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  • 2
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    Mean field theory for biology inspired duplication-divergence network model (2015)
    American Institute of Physics (AIP)
    In: Chaos
    Details
    Publication Date: 2015-08-12
    Description: The duplication-divergence network model is generally thought to incorporate key ingredients underlying the growth and evolution of protein-protein interaction networks. Properties of the model have been elucidated through numerous simulation studies. However, a comprehensive theoretical study of the model is lacking. Here, we derived analytic expressions for quantities describing key characteristics of the network—the average degree, the degree distribution, the clustering coefficient, and the neighbor connectivity—in the mean-field, large- N limit of an extended version of the model, duplication-divergence complemented with heterodimerization and addition. We carried out extensive simulations and verified excellent agreement between simulation and theory except for one partial case. All four quantities obeyed power-laws even at moderate network size ( N ∼ 10 4 ), except the degree distribution, which had an additional exponential factor observed to obey power-law. It is shown that our network model can lead to the emergence of scale-free property and hierarchical modularity simultaneously, reproducing the important topological properties of real protein-protein interaction networks.
    Print ISSN: 1054-1500
    Electronic ISSN: 1089-7682
    Topics: Physics
    Published by American Institute of Physics (AIP)
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  • 3
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    UAV Recharging Opportunities and Policies for Sensor Networks (2015)
    Hindawi
    Details
    Publication Date: 2015-08-12
    Description: Recharging sensor networks using Unmanned Aerial Vehicles (UAVs) provides a possible method for increasing network lifetime. In this paper, we evaluate that approach, determining how much of a benefit it provides and under what conditions. We base our simulations and field experiments on data collected from charging with our UAV-based wireless power transfer system, which has similar transfer ranges and efficiencies as other such systems. We determine that a UAV can increase the network lifetime up to 290% compared to no recharging, that the UAV should recharge 30% of the sensor node battery capacity at one time for the maximum benefit, and that the UAV should recharge the lowest powered node until the network reaches a size of approximately 306 nodes at which point it should recharge the sink. We also examine how the sensor network can aid this through sink selection. The policy varies as network size increases, with a static approach working well until 200 nodes, and then either a perimeter or heuristic approach works best. These results inform future use of UAVs in recharging and working with sensor networks.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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  • 4
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    An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction (2015)
    Hindawi
    Details
    Publication Date: 2015-08-12
    Description: The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 5
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    Torsion Wave Solutions in Yang-Mielke Theory of Gravity (2015)
    Hindawi
    Details
    Publication Date: 2015-08-13
    Description: The approach of metric-affine gravity initially distinguishes it from Einstein’s general relativity. Using an independent affine connection produces a theory with 10 + 64 unknowns. We write down the Yang-Mills action for the affine connection and produce the Yang-Mills equation and the so-called complementary Yang-Mills equation by independently varying with respect to the connection and the metric, respectively. We call this theory the Yang-Mielke theory of gravity. We construct explicit spacetimes with pp-metric and purely axial torsion and show that they represent a solution of Yang-Mills theory. Finally we compare these spacetimes to existing solutions of metric-affine gravity and present future research possibilities.
    Print ISSN: 1687-7357
    Electronic ISSN: 1687-7365
    Topics: Physics
    Published by Hindawi
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  • 6
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    Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains (2015)
    Hindawi
    Details
    Publication Date: 2015-08-13
    Description: The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time-consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with low overhead. In this paper, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 7
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    A Grid-Based Linear Least Squares Self-Localization Algorithm in Wireless Sensor Network (2015)
    Hindawi
    Details
    Publication Date: 2015-08-14
    Description: Self-localization is one of the key technologies in the wireless sensor networks (WSN). Some traditional self-localization algorithms can provide a reasonable positioning accuracy only in a uniform and dense network, while for a nonuniform network the performance is not acceptable. In this paper, we presented a novel grid-based linear least squares (LLS) self-localization algorithm. The proposed algorithm uses the grid method to screen the anchors based on the distribution characteristic of a nonuniform network. Furthermore, by taking into consideration the quasi-uniform distribution of anchors in the area, we select suitable anchors to assist the localization. Simulation results demonstrate that the proposed algorithm can greatly enhance the localization accuracy of the anonymous nodes and impose less computation burden compared to traditional Trilateration and Multilateration.
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    Topics: Electrical Engineering, Measurement and Control Technology
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  • 8
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    CTLL: A Cell-Based Transfer Learning Method for Localization in Large Scale Wireless Sensor Networks (2015)
    Hindawi
    Details
    Publication Date: 2015-08-14
    Description: Localization is emerging as a fundamental component in wireless sensor network and is widely used in the field of environmental monitoring, national and military defense, transportation monitoring, and so on. Current localization methods, however, focus on how to improve accuracy without considering the robustness. Thus, the error will increase rapidly when nodes density and SNR (signal to noise ratio) have changed dramatically. This paper introduces CTLL, Cell-Based Transfer Learning Method for Localization in WSNs, a new way for localization which is robust to the variances of nodes density and SNR. The method combines samples transfer learning and SVR (Support Vector Regression) regression model to get a better performance of localization. Unlike past work, which considers that the nodes density and SNR are invariable, our design applies regional division and transfer learning to adapt to the variances of nodes density and SNR. We evaluate the performance of our method both on simulation and realistic deployment. The results show that our method increases accuracy and provides high robustness under a low cost.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 9
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    On Minimum-Latency Broadcast in Multichannel Duty-Cycled Wireless Sensor Networks (2015)
    Hindawi
    Details
    Publication Date: 2015-08-14
    Description: Broadcast has critical significance for wide application of wireless sensor networks (WSNs). Minimum-latency broadcast (MLB) studies how to devise a broadcast schedule, which can achieve minimum broadcast latency with no signal interference. In multichannel duty-cycled WSNs, nodes can exploit multiple channels to communicate and periodically fall asleep after working for some time. Nevertheless, most solutions to the MLB problem either focus on nonsleeping scenarios or only exploit one single channel. Therefore, we investigate the MLB problem in multichannel duty-cycled WSNs in this paper and call this problem as MLBCD problem. We prove that MLBCD problem is NP-hard. We propose a new concept of active interference graph (AIG). Based on AIG, we present one novel approximation broadcast algorithm called NAB to solve the MLBCD problem. We prove that our proposed NAB algorithm achieves provable performance guarantee. The results of our extensive evaluations show that NAB algorithm can significantly improve the broadcast latency.
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    Topics: Electrical Engineering, Measurement and Control Technology
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  • 10
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    A Group Mining Method for Big Data on Distributed Vehicle Trajectories in WAN (2015)
    Hindawi
    Details
    Publication Date: 2015-08-14
    Description: A distributed parallel clustering method MCR-ACA is proposed by integrating the ant colony algorithm with the computing framework Map-Combine-Reduce for mining groups with the same or similar features from big data on vehicle trajectories stored in Wide Area Network. The heaviest computing burden of clustering is conducted in parallel at local nodes, of which the results are merged to small size intermediates. The intermediates are sent to the central node and clusters are generated adaptively. The great overhead of transferring big volume data is avoided by MCR-ACA, which improves the computing efficiency and guarantees the correctness of clustering. MCR-ACA is compared with an existing parallel clustering algorithm on practical big data collected by the traffic monitoring system of Jiangsu province in China. Experimental results demonstrate that the proposed method is effective for group mining by clustering.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
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