Process of friction-stir welding high-strength aluminum alloy and mechanical properties of joint

The process of friction-stir welding 2A12CZ alloy has been studied. And strength and elongation tests have been performed, which demonstrated that the opportunity existed to manipulate friction-stir welding parameters in order to improve a range of material properties. The results showed that the joint strength and elongation arrived at their maximums ( 331 MPa and 4% ) at 37. 5 mm/min and 300 rpm. As welding parameters changing, joint tensile strength and elongation had similar development. Hardness measurement indicated that the weld was softened. However, there was considerable difference in softening degree for different joint zone. The weld top had lower hardness and wider softening zone than other zone of the weld. And softening zone at advancing side was wider than that at retreating side.     

Stochastic consensus control with finite frequency specification for Markov jump networks

A stochastic finite frequency consensus protocol for directed networks with Markov jump topologies and external disturbances is proposed in this paper. By introducing the frequency band information into consensus control design, the disagreement dynamics of interconnected networks asymptotically converge to zero with an improved level of disturbance attenuation in the specific frequency band. In addition, the new model transformation approach is presented by exploring certain features of Laplacian matrix in real Jordan form, which leads to more generality of the designed protocol. A numerical example validates the potential of the developed results. Copyright © 2015 John Wiley & Sons, Ltd.     

A Train Dispatching Model Under a Stochastic Environment: Stable Train Routing Constraints and Reformulation

After major capacity breakdown(s) on a railway network, train dispatchers need to generate appropriate dispatching plans to recover the impacted train schedule from perturbations and minimize the expected total train delay time under stochastic scenarios. In this paper, we propose a cumulative flow variables-based integer programming model for dispatching trains under a stochastic environment on a general railway network. Stable Train Routing (STR) constraints are introduced to ensure that trains traverse on the same route across different capacity breakdown scenarios, which are further reformulated to equivalent linear inequality constraints. Track occupancy and safety headways are modelled as side constraints which are dualized through a proposed Lagrangian relaxation solution framework. The original complex train dispatching problem is then decomposed to a set of single-train and single-scenario optimization subproblems. For each subproblem, a standard label correcting algorithm is embedded for finding the time dependent least cost path on a space-time network. The resulting dual solutions can be transformed to feasible solutions through priority rules. Numerical experiments are conducted to demonstrate the efficiency and effectiveness of the proposed solution approach.     

智能手机的无线身份认证系统应用研究

在现有身份认证技术的基础上,研究了一种利用智能手机作为身份认证载体、结合了二维条码和蓝牙技术、具有较高安全性和易用性的身份认证系统,并对系统实现的关键技术进行了研究。     

网络信息技术在高中体育教学中的应用

随着信息时代的到来,网络信息技术的应用范围越来越广,在学校教学不断改革的过程中,教学中对信息技术的使用越来越普遍。本文主要对网络信息技术在高中体育教学中的应用进行了讨论,首先分析了在高中体育教学中运用网络信息技术的作用,然后介绍了网络信息技术在高中体育教学中具体的应用方式。     

CAN总线到1553B总线的网关设计

1553B和CAN总线已经得到广泛的应用,但是这两种总线标准在性能和造价上各有所长。作为一种折中的设计,在系统中的不同部分按照其需求分别采用不同总线的方案成为一种理想的选择。因此两种总线之间的网关设计成为一个栾守廷＊重点,设计一种可行的CAN总线到1553B总线的网关,以满足实际应用系统的需求。     

人脸像素画生成算法

为了让普通用户方便地得到像素画卡通头像,提出一种自动从人脸照片生成像素画的算法.首先通过对脸部特征定位找到关键特征,然后在低分辨率下对特征的形状和位置进行优化调整;在调整后的各个区域采用"画家调色盘"色彩校正方法对其颜色进行校正,生成像素画.实验结果表明,该算法能够生成结构清晰、色彩明快的像素画.     

扫描仪的常见故障及排除方法

介绍了扫描仪的常见故障及其排除方法.     

Accelerating approximate matrix multiplication for near-sparse matrices on GPUs

The Journal of Supercomputing - Although the matrix multiplication plays a vital role in computational linear algebra, there are few efficient solutions for matrix multiplication of the near-sparse...     

Data augmentation for low-resource languages NMT guided by constrained sampling

Data augmentation (DA) is a ubiquitous approach for several text generation tasks. Intuitively, in the machine translation paradigm, especially in low-resource languages scenario, many DA methods have appeared. The most commonly used methods are building pseudocorpus by randomly sampling, omitting, or replacing some words in the text. However, previous approaches hardly guarantee the quality of augmented data. In this study, we try to augment the corpus by introducing a constrained sampling method. Additionally, we also build the evaluation framework to select higher quality data after augmentation. Namely, we use the discriminator submodel to mitigate syntactic and semantic errors to some extent. Experimental results show that our augmentation method consistently outperforms all the previous state-of-the-art methods on both small and large-scale corpora in eight language pairs from four corpora by 2.38–4.18 bilingual evaluation understudy points.