Ti-6Al-4V is a benchmark Ti alloy. Laser wire additive manufacturing(LWAM) offers advanced manufacturing capability to the alloy for applications possibly including exploration of outer space. As a typical multiple-va...
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Ti-6Al-4V is a benchmark Ti alloy. Laser wire additive manufacturing(LWAM) offers advanced manufacturing capability to the alloy for applications possibly including exploration of outer space. As a typical multiple-variable process, LWAM is complex, which, however, can be analyzed, predicated or even optimized by artificial intelligence(AI) methods such as machine learning(ML). In this study, printing parameters of the Ti-6Al-4V is firstly optimized using single-track-single-layer experiments, and then single-track-multiple-layer samples are printed, whose properties in terms of hardness and compressive strength are analyzed subsequently by both experiments and ML. The two ML approaches, artificial neural network(ANN) and support vector machine(SVM), are employed to predict the experimental results, whose coefficients of determination R2 show good values. Further optimized properties are realized by adopting genetic algorithm(GA) and simulated annealing(SA) approaches, which contribute to high mechanical properties achieved, for instance, an engineering compressive strength of about 1694 MPa. The results here indicate that important mechanical properties of the LWAM-prepared Ti alloys can be well predicted and enhanced using suitable ML approaches.
Existing learning-based hyperspectral reconstruction methods show limitations in fully exploiting the information among the hyperspectral bands. As such, we propose to investigate the chromatic inter-dependencies in t...
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Secure sum protocol is a significant secure multiparty computation protocol and it has various applications in privacy-preserving distributed multiparty computation. However, most existing secure sum protocols rarely ...
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Secure sum protocol is a significant secure multiparty computation protocol and it has various applications in privacy-preserving distributed multiparty computation. However, most existing secure sum protocols rarely considered how to resist underlying collusion which is a significant practical problem. Urabe et al. proposed a collusion-resistant secure sum protocol, but too much cost of communication and computation results in its low performance efficiency. In this paper, we propose security definitions to measure secure multiparty computation protocol's capability of resisting potential collusion. Then, we precisely analyze several previous secure sum protocols' capability of resisting collusion. In addition, considering realistic requirement to resist collusion and performance efficiency needs, we present a novel collusion-resisting secure sum protocol. Theoretical analysis and experimental results confirm that our secure sum protocol is efficient and has strong capability of resisting potential collusion such that it is much superior to previous ones. The communication overheads and computation complexity of our scheme both are linearity of the number of participants. Besides, our protocol's capability of resisting collusion is adjustable according to different security needs.
The Peaceman-Rachford splitting method is efficient for minimizing a convex optimization problem with a separable objective function and linear ***,its convergence was not guaranteed without extra *** et al.(SIAM ***....
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The Peaceman-Rachford splitting method is efficient for minimizing a convex optimization problem with a separable objective function and linear ***,its convergence was not guaranteed without extra *** et al.(SIAM ***.24:1011-1040,2014)proved the convergence of a strictly contractive Peaceman-Rachford splitting method by employing a suitable underdetermined relaxation *** this paper,we further extend the so-called strictly contractive Peaceman-Rachford splitting method by using two different relaxation ***,motivated by the recent advances on the ADMM type method with indefinite proximal terms,we employ the indefinite proximal term in the strictly contractive Peaceman-Rachford splitting *** show that the proposed indefinite-proximal strictly contractive Peaceman-Rachford splitting method is convergent and also prove the o(1/t)convergence rate in the nonergodic *** numerical tests on the l 1 regularized least square problem demonstrate the efficiency of the proposed method.
This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture...
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The role of correlations in self-organised critical (SOC) phenomena is investigated by studying the Abelian Manna Model (AMM) in two dimensions. Local correlations of the debris left behind after avalanches are destro...
The brief review shows the potential of machine learning to improve the accuracy of multimodal medical diagnostic methods to a new level. Various machine learning algorithms, modalities, and cases demonstrating this a...
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Excitonic Bose-Einstein condensation (EBEC) has drawn increasing attention recently with the emergence of 2D materials. A general criterion for EBEC, as expected in an excitonic insulator (EI) state, is to have negati...
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Excitonic Bose-Einstein condensation (EBEC) has drawn increasing attention recently with the emergence of 2D materials. A general criterion for EBEC, as expected in an excitonic insulator (EI) state, is to have negative exciton formation energies in a semiconductor. Here, using exact diagonalization of a multiexciton Hamiltonian modeled in a diatomic kagome lattice, we demonstrate that the negative exciton formation energies are only a prerequisite but insufficient condition for realizing an EI. By a comparative study between the cases of both conduction and valence flat bands (FBs) versus that of a parabolic conduction band, we further show that the presence and increased FB contribution to exciton formation provide an attractive avenue to stabilize the excitonic condensate, as confirmed by calculations and analyses of multiexciton energies, wave functions, and reduced density matrices. Our results warrant a similar many-exciton analysis for other known and/or new candidates of EIs and demonstrate the FBs of opposite parity as a unique platform for studying exciton physics, paving the way to material realization of spinor BEC and spin superfluidity.
In situ changes in the nanofriction and microstructures of ionic liquids(ILs)on uncharged and charged surfaces have been investigated using colloid probe atomic force microscopy(AFM)and molecular dynamic(MD)*** repres...
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In situ changes in the nanofriction and microstructures of ionic liquids(ILs)on uncharged and charged surfaces have been investigated using colloid probe atomic force microscopy(AFM)and molecular dynamic(MD)*** representative ILs,[BMIM][BF_(4)](BB)and[BMIM][PF_(6)](BP),containing a common cation,were selected for this *** torsional resonance frequency was captured simultaneously when the nanoscale friction force was measured at a specified normal load;and it was regarded as a measure of the contact stiffness,reflecting in situ changes in the IL microstructures.A higher nanoscale friction force was observed on uncharged mica and highly oriented pyrolytic graphite(HOPG)surfaces when the normal load increased;additionally,a higher torsional resonance frequency was detected,revealing a higher contact stiffness and a more ordered IL *** nanofriction of ILs increased at charged HOPG surfaces as the bias voltage varied from 0 to 8 V or from 0 to−8 *** simultaneously recorded torsional resonance frequency in the ILs increased with the positive or negative bias voltage,implying a stiffer IL layer and possibly more ordered ILs under these *** simulation reveals that the[BMIM]+imidazolium ring lies parallel to the uncharged surfaces preferentially,resulting in a compact and ordered IL *** parallel“sleeping”structure is more pronounced with the surface charging of either sign,indicating more ordered ILs,thereby substantiating the AFM-detected stiffer IL layering on the charged *** in situ observations of the changes in nanofriction and microstructures near the uncharged and charged surfaces may facilitate the development of IL-based applications,such as lubrication and electrochemical energy storage devices,including supercapacitors and batteries.
As a fundamental tool for graph analysis, random walk receives extensive attention in both industry and academia. For computing massive random walks, recent works show that GPUs provide a good option to accelerate the...
As a fundamental tool for graph analysis, random walk receives extensive attention in both industry and academia. For computing massive random walks, recent works show that GPUs provide a good option to accelerate the performance. However, due to the limited memory space of modern GPUs, it is infeasible to have both the graph data and walk index fully reside in GPU memory when running large-scale random walks. Thus, it necessitates an out-of-GPU-memory design, but this inevitably induces large amounts of CPU-GPU data transmission traffic and thus hinders the overall performance. In this paper, we develop LightTraffic, which optimizes the data transmission between CPU and GPU memory under the constraint of GPU memory capacity with various system designs, including a memory-efficient scheme for partition-based management and multiple scheduling techniques. LightTraffic is a fully out-of-GPU-memory design, so it supports running large-scale random walks on GPUs. Experiments on our prototype show that LightTraffic outperforms various state-of-the-art CPU-based in-memory systems which also support large-scale random walks. For example, compared to the CPU-based systems FlashMob and ThunderRW, which are highly optimized for random walks, LightTraffic achieves 1.7−5.0× and 1.4 − 12.8× performance speedup, respectively. It also achieves up to an order of magnitude speedup when compared to the GPU-based system Subway which also supports large-scale random walks with an out-of-GPU-memory design for graph data.
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