稳恒磁场下Ni-W合金镀膜的制备与耐蚀性

研究了施加稳恒磁场(0~1 T)对电镀Ni-W合金的影响。测定不同方向、不同强度稳恒磁场下的电流效率、合金组成及镀层的耐蚀性,并用扫描电镜和X射线衍射对镀层的微观形貌及结构进行了观察和分析。对实验结果进行了分析讨论,找出稳恒磁场对这些性能指标的影响规律。结果表明:与不施加磁场相比,施加磁场后镀层的表面更均匀、细致、平整;镀层的含钨量上升:当B⊥J,B=1.0 T时,含钨量上升了约7%;当B∥J,B=1.0 T时,含钨量上升了约9%;镀膜的非晶化程度增强;镀膜的耐蚀性提高;但Ni-W合金电镀的电流效率降低。     

埋地管道开挖边坡有限元法优化设计

在埋地管道输水方案中,沟槽开挖坡比的大小直接影响施工安全、管材安装质量及工程投资与经济效益,因此,合理设计开挖坡比具有重大意义。以阜城—景县输水管道工程为工程背景,根据给定工程地质,基于有限元强度折减法,以ANSYS软件为计算工具,对沟槽开挖边坡进行安全稳定性计算。通过计算假定开挖坡比的边坡稳定性,获得不同开挖坡比下的沟槽边坡达到破坏时的安全系数,再根据选取的最优安全系数,确定最优开挖边坡。同时,基于上述方法,计算分析了开挖坡比与边坡安全系数的非线性关系,根据计算结果得出了有益结论与意见。     

卡拉贝利水利枢纽工程坝体填筑优化设计

新疆卡拉贝利水利枢纽工程因泄洪排沙放空洞工程工期滞后一年多,对工程截流及后续坝体施工项目进度产生了重大影响。通过坝体填筑方案的优化设计,不仅使坝体度汛、坝体填筑及蓄水目标能够按照原定进度实现,还节省了工程投资,得到了建设单位、设计单位的一致认可,为土石坝工程施工积累了经验。     

无线移动感知网络上的数据聚集传输规划

随着城市交通日益增多,智能交通系统研究受到工业界和学术界的极大关注.智能交通系统上的实时导航、交通监控等应用都需要大量实时车辆速度、位置等信息.由智能车组成的无线移动感知网络的链路变化频繁并且无线干扰严重,现有的车辆网络上的数据聚集算法没有考虑无线链路变化的具体情况,就进行数据聚集和传输的规划.文中分析并求解了移动感知网络上的无冲突数据聚集传输规划问题,将该问题形式化为移动通信拓扑图上的单传聚集传输规划问题,并证明了该问题是NP完全的;提出了移动聚集路由树,将无线冲突分为树内冲突和树间冲突,首先构建树间冲突图描述树间冲突,过滤节点的传输候选时刻集以消除树间冲突,然后利用动态规划思想进行聚集路由树上的数据聚集传输时刻规划来消除树内冲突.并且在真实出租车移动轨迹数据集上进行了实验,实验结果表明文中的算法比现有的算法在数据收集率上提高了1/4左右,并且收集上来的数据的平均延迟也更小.     

红外球形摄像机补光系统的设计与实现

为解决目前红外球形摄像机普遍存在的红外灯板发热严重、近距离采集图像容易出现中心过曝等问题,搭建了以STM32F103为主控芯片、以PT4115为红外灯调光芯片的硬件电路,设计了一种基于红外灯亮度与镜头倍率匹配算法的新型红外球形摄像机补光系统,实现了在红外灯板上对多个串联红外灯的PWM智能调光。通过实验证明,该设计可以有效节约功耗、降低发热,提高了红外灯板的稳定性,从而提高红外球形摄像机的夜视监控效果。     

基于SystemVerilog可重用测试平台的实现

对于中小型设计,传统的验证效率低、可重用性差,而基于方法学的高级验证测试平台搭建较繁琐,验证流程不太灵活。以ARINC429收发器IP核为验证对象,采用System Verilog语言,通过层次化设计,改善工程组织架构,运用虚接口与回调等关键技术,实现了一种可重用测试平台。将不同的测试案例在测试平台上运行,结合断言与覆盖率驱动等验证技术完成了对ARINC429收发器IP核的功能验证,代码覆盖率和功能覆盖率均达到100%。实践表明,该测试平台具有良好的可重用性、易操作性,验证效率较高。     

基于ZigBee的矿用应力监测系统的研究

提出了一种新的煤矿巷道监测方法 ,即采用测力锚杆对巷道顶部深处的应力变化进行定时监测。系统主要分为三部分:传感器节点、通信主站和上位机。传感器节点负责采集和上传数据,数据主站负责管理各传感器节点并存储和上传数据,上位机负责汇总各传感器数据并对其进行分析处理。     

Some Results for Pythagorean Fuzzy Sets

Pythagorean fuzzy sets (PFSs), originally proposed by Yager (Yager, Abbasov. Int J Intell Syst 2013;28:436–452), are a new tool to deal with vagueness considering the membership grades are pairs satisfying the condition . As a generalized set, PFSs have close relationship with intuitionistic fuzzy sets (IFSs). PFSs can be reduced to IFSs satisfying the condition . However, the related operations of PFSs do not take different conditions into consideration. To better understand PFSs, we propose two operations: division and subtraction, and discuss their properties in detail. Then, based on Pythagorean fuzzy aggregation operators, their properties such as boundedness, idempotency, and monotonicity are investigated. Later, we develop a Pythagorean fuzzy superiority and inferiority ranking method to solve uncertainty multiple attribute group decision making problem. Finally, an illustrative example for evaluating the Internet stocks performance is given to verify the developed approach and to demonstrate its practicality and effectiveness.     

Incorporating Intra‐Query Term Dependencies in an Aspect Query Language Model

Query language modeling based on relevance feedback has been widely applied to improve the effectiveness of information retrieval. However, intra‐query term dependencies (i.e., the dependencies between different query terms and term combinations) have not yet been sufficiently addressed in the existing approaches. This article aims to investigate this issue within a comprehensive framework, namely the Aspect Query Language Model (AM). We propose to extend the AM with a hidden Markov model (HMM) structure to incorporate the intra‐query term dependencies and learn the structure of a novel aspect HMM (AHMM) for query language modeling. In the proposed AHMM, the combinations of query terms are viewed as latent variables representing query aspects. They further form an ergodic HMM, where the dependencies between latent variables (nodes) are modeled as the transitional probabilities. The segmented chunks from the feedback documents are considered as observables of the HMM. Then the AHMM structure is optimized by the HMM, which can estimate the prior of the latent variables and the probability distribution of the observed chunks. Our extensive experiments on three large‐scale text retrieval conference (TREC) collections have shown that our method not only significantly outperforms a number of strong baselines in terms of both effectiveness and robustness but also achieves better results than the AM and another state‐of‐the‐art approach, namely the latent concept expansion model. © 2014 Wiley Periodicals, Inc.