用于近场集成光学头微透镜器件的灰度掩模技术

讨论了制作适用于近场集成光学头中的凸形、凹形微透镜和折衍射复合微透镜的灰度掩模技术。定性地给出了与几种典型的凸形、凹形微透镜和折衍射复合微透镜对应的灰度掩模版的设计实例 ,以及将它应用于光刻操作的情况 ,为采用灰度掩模技术制作适用于近场集成光学头中的微透镜器件奠定了基础。灰度掩模技术在微透镜器件的制作方面具有重要的应用前景 ,有助于简化制备工艺 ,降低制作成本 ,优化微透镜阵列的结构参数。     

神经网络量子态及其应用

神经网络量子态是由人工神经网络所表示的量子态。得益于机器学习,尤其是深度学习近年来取得的突破性进展,神经网络量子态的研究得到了广泛的关注,成为当前的热点前沿方向。文章将介绍不同的神经网络量子态,其物理性质与典型应用场景,最新进展,以及面临的挑战。     

An improved progressive preconditioning method for steady non‐cavitating and sheet‐cavitating flows

An improved progressive preconditioning method for analyzing steady inviscid and laminar flows around fully wetted and sheet‐cavitating hydrofoils is presented. The preconditioning matrix is adapted automatically from the pressure and/or velocity flow‐field by a power‐law relation. The cavitating calculations are based on a single fluid approach. In this approach, the liquid/vapour mixture is treated as a homogeneous fluid whose density is controlled by a barotropic state law. This physical model is integrated with a numerical resolution derived from the cell‐centered Jameson's finite volume algorithm. The stabilization is achieved via the second‐and fourth‐order artificial dissipation scheme. Explicit four‐step Runge–Kutta time integration is applied to achieve the steady‐state condition. Results presented in the paper focus on the pressure distribution on hydrofoils wall, velocity profiles, lift and drag forces, length of sheet cavitation, and effect of the power‐law preconditioning method on convergence speed. The results show satisfactory agreement with numerical and experimental works of others. The scheme has a progressive effect on the convergence speed. The results indicate that using the power‐law preconditioner improves the convergence rate, significantly. Copyright © 2010 John Wiley & Sons, Ltd.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

一种自适应人工蜂群算法求解U型顺序相依拆卸线平衡问题

产品拆卸过程中零部件之间会相互干扰影响任务作业时间,基于该情形构建了多目标U型SDDLBP优化模型,并提出一种自适应ABC算法。所提算法设计了自适应动态邻域搜索方法,以提高局部开发能力;采用了轮盘赌与锦标赛法结合的分段选择法,以有效评价并选择蜜源进行深度开发;建立了基于当前最优解的变异操作,以提高全局探索能力快速跳出局部最优。最后,通过算例测试和实例分析验证算法的高效性。     

Neural network modeling of hydrological systems: A review of implementation techniques

This paper presents a review of procedural steps and implementation techniques used in the development of artificial intelligence models, generally referred to as artificial neural networks (ANNs), within the water resources domain. It focusses on identifying different areas wherein ANNs have found application thereby elucidating its advantages and disadvantages as well as various challenges encountered in its use. Results from this review provide useful insights into how the performance of ANNs can be improved and potential areas of application that are yet to be explored in hydrological modeling. Recommendations for Resource Managers

• Development of integrated and hybrid artificial intelligent tools is critical to achieving improved forecasts in hydrological modeling studies.

• Further research into comprehending the internal mechanisms of neural networks is required to obtain a practical meaning of each network component deployed to solve real‐world problems.

• More robust optimization techniques and tools like differential evolution, particle swarm optimization and deep neural nets, are yet to be fully explored in the water resources analysis, and should be given more attention to enhance neural networks aptitude for modeling complex and nonlinear hydrological processes.

     

Molecular Hydrogels with Esterase-like Activity

The development of molecular hydrogels that can be applied for mimicking bioactive molecules attracts extensive interests of researchers in fields of self‐assembly. In this study, we reported on several molecular hydrogels based on naphthylacetic acid‐peptides containing L‐histidine formed by the heating‐cooling process. All hydrogels exhibited higher activity to hydrolyze 4‐nitrophenyl acetate (4‐NPA) than the free L‐histidine probably due the high density of L‐histidine residue at the surface of self‐assembled nanofibers. To calculate the 4‐NPA hydrolysis rates, the Michaelis‐Menten enzyme kinetics model was made. Among these gels, the gel of Nap‐GFFYGHY possesses the highest enzyme activity of making the ester bond cleavage, which is approximately 25 times higher than that of the control (free L‐histidine and Nap‐GFFYGYY). These results indicate that molecular hydrogels with self‐assembled nanofibers have great potential for the generation of self‐assembled multivalent materials.     

文化框架下多群智能优化算法的云作业调度

作业调度是一种云计算核心技术,为了获得更优的云计算作业调度方案,提出一种文化框架下多群智能优化算法的云作业调度方法。首先构建云作业调度问题的数学模型,然后借助文化算法模型,粒子群算法组成信仰空间,人工鱼群算法组成群体空间,两者之间并行演化,相互促进,对云计算作业调度数学模型进行求解,最后通过仿真实验测试算法的性能。结果表明,本文加快了算法的收敛速度,获得了更优的云计算作业调度方案,大幅度缩短少云计算作业完成时间,具有一定的实用价值。