3,006 research outputs found
Photoproduction of Pentaquark and Chiral Symmetry Restoration in Hot and Dense Medium
The photoproduction rate of pentaquark is calculated in a hot and
dense medium. At high temperature and density, due to the restoration of chiral
symmetry, photoproduction energy threshold is increased. Above the thresold the
production cross section is strongly enhanced.Comment: 5 pages, 3 figure
TasselNet: Counting maize tassels in the wild via local counts regression network
Accurately counting maize tassels is important for monitoring the growth
status of maize plants. This tedious task, however, is still mainly done by
manual efforts. In the context of modern plant phenotyping, automating this
task is required to meet the need of large-scale analysis of genotype and
phenotype. In recent years, computer vision technologies have experienced a
significant breakthrough due to the emergence of large-scale datasets and
increased computational resources. Naturally image-based approaches have also
received much attention in plant-related studies. Yet a fact is that most
image-based systems for plant phenotyping are deployed under controlled
laboratory environment. When transferring the application scenario to
unconstrained in-field conditions, intrinsic and extrinsic variations in the
wild pose great challenges for accurate counting of maize tassels, which goes
beyond the ability of conventional image processing techniques. This calls for
further robust computer vision approaches to address in-field variations. This
paper studies the in-field counting problem of maize tassels. To our knowledge,
this is the first time that a plant-related counting problem is considered
using computer vision technologies under unconstrained field-based environment.Comment: 14 page
Semitotal domination in trees
In this paper, we study a parameter that is squeezed between arguably the two
important domination parameters, namely the domination number, , and
the total domination number, . A set of vertices in is a
semitotal dominating set of if it is a dominating set of and every
vertex in S is within distance of another vertex of . The semitotal
domination number, , is the minimum cardinality of a semitotal
dominating set of . We observe that . In this paper, we give a lower bound for the semitotal domination
number of trees and we characterize the extremal trees. In addition, we
characterize trees with equal domination and semitotal domination numbers.Comment: revise
An Algorithmic Framework for Efficient Large-Scale Circuit Simulation Using Exponential Integrators
We propose an efficient algorithmic framework for time domain circuit
simulation using exponential integrator. This work addresses several critical
issues exposed by previous matrix exponential based circuit simulation
research, and makes it capable of simulating stiff nonlinear circuit system at
a large scale. In this framework, the system's nonlinearity is treated with
exponential Rosenbrock-Euler formulation. The matrix exponential and vector
product is computed using invert Krylov subspace method. Our proposed method
has several distinguished advantages over conventional formulations (e.g., the
well-known backward Euler with Newton-Raphson method). The matrix factorization
is performed only for the conductance/resistance matrix G, without being
performed for the combinations of the capacitance/inductance matrix C and
matrix G, which are used in traditional implicit formulations. Furthermore, due
to the explicit nature of our formulation, we do not need to repeat LU
decompositions when adjusting the length of time steps for error controls. Our
algorithm is better suited to solving tightly coupled post-layout circuits in
the pursuit for full-chip simulation. Our experimental results validate the
advantages of our framework.Comment: 6 pages; ACM/IEEE DAC 201
MATEX: A Distributed Framework for Transient Simulation of Power Distribution Networks
We proposed MATEX, a distributed framework for transient simulation of power
distribution networks (PDNs). MATEX utilizes matrix exponential kernel with
Krylov subspace approximations to solve differential equations of linear
circuit. First, the whole simulation task is divided into subtasks based on
decompositions of current sources, in order to reduce the computational
overheads. Then these subtasks are distributed to different computing nodes and
processed in parallel. Within each node, after the matrix factorization at the
beginning of simulation, the adaptive time stepping solver is performed without
extra matrix re-factorizations. MATEX overcomes the stiff-ness hinder of
previous matrix exponential-based circuit simulator by rational Krylov subspace
method, which leads to larger step sizes with smaller dimensions of Krylov
subspace bases and highly accelerates the whole computation. MATEX outperforms
both traditional fixed and adaptive time stepping methods, e.g., achieving
around 13X over the trapezoidal framework with fixed time step for the IBM
power grid benchmarks.Comment: ACM/IEEE DAC 2014. arXiv admin note: substantial text overlap with
arXiv:1505.0669
Asymmetric Fermi Superfluid With Two Types Of Pairings
We investigate the phase diagram in the plane of temperature and chemical
potential mismatch for an asymmetric fermion superfluid with double- and
single-species pairings. There is no mixing of these two types of pairings at
fixed chemical potential, but the introduction of the single species pairing
cures the magnetic instability at low temperature.Comment: 6 pages, 1 figure. Proceedings of Poster Session, Quark Matter 2006,
November 14-20, 2006, Shanghai, P.R.Chin
First-principles study, fabrication and characterization of (Zr0.25Nb0.25Ti0.25V0.25)C high-entropy ceramic
The formation possibility of a new (Zr0.25Nb0.25Ti0.25V0.25)C high-entropy
ceramic (ZHC-1) was first analyzed by the first-principles calculations and
thermodynamical analysis and then it was successfully fabricated by hot
pressing sintering technique. The first-principles calculation results showed
that the mixing enthalpy of ZHC-1 was 5.526 kJ/mol and the mixing entropy of
ZHC-1 was in the range of 0.693R-1.040R. The thermodynamical analysis results
showed that ZHC-1 was thermodynamically stable above 959 K owing to its
negative mixing Gibbs free energy. The experimental results showed that the
as-prepared ZHC-1 (95.1% relative density) possessed a single rock-salt crystal
structure, some interesting nanoplate-like structures and high compositional
uniformity from nanoscale to microscale. By taking advantage of these unique
features, compared with the initial metal carbides (ZrC, NbC, TiC and VC), it
showed a relatively low thermal conductivity of 15.3 + - 0.3 W/(m.K) at room
temperature, which was due to the presence of solid solution effects,
nanoplates and porosity. Meanwhile, it exhibited the relatively high
nanohardness of 30.3 + - 0.7 GPa and elastic modulus of 460.4 + - 19.2 GPa and
the higher fracture toughness of 4.7 + - 0.5 MPa.m1/2, which were attributed to
the solid solution strengthening mechanism and nanoplate pullout and microcrack
deflection toughening mechanism.Comment: 49 pages,6 figures, 4 table
Railway Safety Risk Assessment and Control Optimization Method Based on FTA-FPN: A Case Study of Chinese High-Speed Railway Station
In order to make safety risk assessment more accurately and more reasonably for high-speed railway station in China, this paper analyzes risk factors of fault tree and transfers the fault tree of risk accident into fuzzy petri net and then builds the FPN-FTA model by combining the dynamic weighting fuzzy petri net (FPN) and fault tree analysis (FTA) based on the latter. This paper simulates the FTA-FPN model with Stateflow of Matlab software. Then, it builds up a bi-objective risk control model, making the minimum safety risk level and minimum necessary cost as the objectives, and it designs discrete particle swarm optimization algorithm to solve the risk control model. Finally, this paper selects stampede accident of Shijiazhuang high-speed railway station as an example in case study for assessing stampede risk level and gets the risk control schemes for this station. The results verify the feasibility and validity of the model and algorithm.
Document type: Articl
Multicloud Resource Allocation:Cooperation, Optimization and Sharing
Nowadays our daily life is not only powered by water, electricity, gas and telephony but by "cloud" as well. Big cloud vendors such as Amazon, Microsoft and Google have built large-scale centralized data centers to achieve economies of scale, on-demand resource provisioning, high resource availability and elasticity. However, those massive data centers also bring about many other problems, e.g., bandwidth bottlenecks, privacy, security, huge energy consumption, legal and physical vulnerabilities. One of the possible solutions for those problems is to employ multicloud architectures. In this thesis, our work provides research contributions to multicloud resource allocation from three perspectives of cooperation, optimization and data sharing. We address the following problems in the multicloud: how resource providers cooperate in a multicloud, how to reduce information leakage in a multicloud storage system and how to share the big data in a cost-effective way. More specifically, we make the following contributions: Cooperation in the decentralized cloud. We propose a decentralized cloud model in which a group of SDCs can cooperate with each other to improve performance. Moreover, we design a general strategy function for SDCs to evaluate the performance of cooperation based on different dimensions of resource sharing. Through extensive simulations using a realistic data center model, we show that the strategies based on reciprocity are more effective than other strategies, e.g., those using prediction based on historical data. Our results show that the reciprocity-based strategy can thrive in a heterogeneous environment with competing strategies. Multicloud optimization on information leakage. In this work, we firstly study an important information leakage problem caused by unplanned data distribution in multicloud storage services. Then, we present StoreSim, an information leakage aware storage system in multicloud. StoreSim aims to store syntactically similar data on the same cloud, thereby minimizing the user's information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity-preserving signatures for data chunks based on MinHash and Bloom filter, and also design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluate our scheme using two real datasets from Wikipedia and GitHub. We show that our scheme can reduce the information leakage by up to 60% compared to unplanned placement. Furthermore, our analysis in terms of system attackability demonstrates that our scheme makes attacks on information much more complex. Smart data sharing. Moving large amounts of distributed data into the cloud or from one cloud to another can incur high costs in both time and bandwidth. The optimization on data sharing in the multicloud can be conducted from two different angles: inter-cloud scheduling and intra-cloud optimization. We first present CoShare, a P2P inspired decentralized cost effective sharing system for data replication to optimize network transfer among small data centers. Then we propose a data summarization method to reduce the total size of dataset, thereby reducing network transfer
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