1,081 research outputs found

    Enhancing Grassland Productivity through Disease Management of Grass and Forage Species

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    The total area of grassland in China is about 400 million hectares, accounting for 41.7% of the country’s land area, which plays important role in ecological construction and food security assurance of the national. However, diseases of grass and forage limited the development of the pastoral agriculture. There are more than1500 new diseases were reported in the past 16 years with more and more new diseases were discovered. The damage to grassland is becoming more severe with the known diseases prevalent areas expanding

    Characterizing and Subsetting Big Data Workloads

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    Big data benchmark suites must include a diversity of data and workloads to be useful in fairly evaluating big data systems and architectures. However, using truly comprehensive benchmarks poses great challenges for the architecture community. First, we need to thoroughly understand the behaviors of a variety of workloads. Second, our usual simulation-based research methods become prohibitively expensive for big data. As big data is an emerging field, more and more software stacks are being proposed to facilitate the development of big data applications, which aggravates hese challenges. In this paper, we first use Principle Component Analysis (PCA) to identify the most important characteristics from 45 metrics to characterize big data workloads from BigDataBench, a comprehensive big data benchmark suite. Second, we apply a clustering technique to the principle components obtained from the PCA to investigate the similarity among big data workloads, and we verify the importance of including different software stacks for big data benchmarking. Third, we select seven representative big data workloads by removing redundant ones and release the BigDataBench simulation version, which is publicly available from http://prof.ict.ac.cn/BigDataBench/simulatorversion/.Comment: 11 pages, 6 figures, 2014 IEEE International Symposium on Workload Characterizatio

    Mechanical properties of magnesium-based wood-like material subjected to splitting tensile tests

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    To investigate the splitting tensile characteristics of a new building material, namely magnesium-based wood-like material (MWM), the cubic splitting tensile tests were carried out at a loading rate of 200 N/s. Full-field displacements and crack behaviors were measured using Digital Image Correlation, and the splitting tensile strength is 1.79 MPa. The elastic Young modulus, Poisson’s ratio, and axial compressive strength were measured as 2.21 GPa, 0.21, 8.76 MPa respectively. In the splitting tensile tests, primary cracks were observed to initiate from the geometric centre of the specimen and then extend to the loading ends where secondary cracks appeared. A new method for identifying cracking modes showed the secondary cracks were mainly caused by shear and tensile-shear failure, whereas the primary cracks were caused by tensile failure. An accurate method for estimating the elastic Young modulus, simultaneously with the determination of the splitting tensile strength of MWM cubes is proposed

    Stochastic spin-orbit-torque device as the STDP synapse for spiking neural networks

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    Neuromorphic hardware as a non-Von Neumann architecture has better energy efficiency and parallelism than the conventional computer. Here, with numerical modeling spin-orbit torque (SOT) device using current-induced SOT and Joule heating effects, we acquire its magnetization switching probability as a function of the input current pulses and use it to mimic the spike-timing-dependent plasticity learning behavior like actual brain working. We further demonstrate that the artificial spiking neural network (SNN) built by this SOT device can perform unsupervised handwritten digit recognition with the accuracy of 80% and logic operation learning. Our work provides a new clue to achieving SNN-based neuromorphic hardware using high-energy efficiency and nonvolatile spintronics nanodevicesComment: 8 pages, 5 figure
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