Metal-free catalyst fabrication by incorporating oxygen groups on the surface of the carbonaceous sample and efficient hydrogen production from NaBH4 methanolysis

In the present study, metal-free catalysts for efficient H₂ generation from NaBH₄ methanolysis was produced for the first time from apricot kernel shells with two-step activation. The first stage of the two-stage activation includes the production of activated carbon with the KOH agent (AKOH), and the second stage includes hydrothermally HNO₃ activation with oxygen doping (O doped AKOH + N). The hydrogen production rate (HGR) and the activation energy (Ea) of the reaction with the obtained metal-free catalyst (10 mg) were determined as 14,444 ml min^?1 g^?1 and 7.86 kJ mol^?1, respectively. The structural and physical-chemical properties of these catalysts were characterized by XRD (X-ray diffraction), SEM (scanning electron microscopy), elemental CHNS analysis, FT-IR (Fourier transform infrared spectroscopy), and nitrogen adsorption analysis. Also, the reusability results of this metal-free catalyst for H₂ production are promising.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Effects of apparent image velocity and complexity on the dynamic visual field using a high-speed train driving simulator

Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety.     

PSO优化多核RVM的模拟电路故障预测

针对模拟电路健康管理的特点，提出了一种基于PSO优化多核RVM的模拟电路故障预测方法。利用参数分析得到电路的输出频域响应作为特征，计算其与电路无故障标准响应的欧氏距离来表征电路元件健康值，将多个核函数线性组合，并用PSO优化多核RVM参数后的模型实现对各个时间点元件的健康值变化轨迹进行预测。仿真结果表明，该方法在小样本情况下，预测效果优于单一核函数的RVM模型，适用于健康管理中实时预测，具有较好的实用性。     

一种基于ECDSA的USB存储设备访问控制方案

文章针对使用USB存储设备造成的内部泄密问题,提出了一种USB存储设备访问控制方案,该方案对用户的身份认证基于安全强度很高的椭圆曲线数字签名算法,同时使用过滤器驱动程序实现了USB存储设备的读写控制,因而此方案具有较好的安全性、实用性和通用性。     

一种新的主动网络安全体系的设计

尽管主动网络原型系统中设计了一些安全措施，但是它们都不具通用性且主要集中在security方面，这在主动网络必须和传统网络相兼容的情况下，阻碍了主动网络的发展。本文在定义消极型错误和积极型错误的基础上，设计了主动网络资源控制核。然后提出了集security和safety保障为一体的基于资源控制核的一种通用的主动网络安全体系，探讨了该体系应具有的特点、设计目标和可行性，并设计了主动节点的安全机制。     

MCF5282的I2C总线在uClinux操作系统下的驱动程序设计

介绍了Freescale公司嵌入式微处理器MCF5282的原理、特点,给出了该处理器在嵌入式操作系统uClinux下通过I2C硬件扩展数字输入的原理,以及I2C总线的驱动程序设计流程.     

Windows2000环境下实时控制系统的软件实现

文章介绍了在windows2000环境下通过编写WDM（Windows Driver Model）设备驱动程序实现实时数据采集和控制的一种方法。采用研华数据采集卡PCL818L产生中断信号．通过编写WDM驱动程序实现了在windows2000环境下转台的位置控制。并在实验中调试通过。实验结果表明：在采样频率为1KHz的情况下。控制系统很好实现了输出对输入的跟踪，证明了采用方法的正确性。该方法解决了windows2000环境下的实时性问题，为在windows环境下实时控制系统的实现提供了有益的尝试。