A hybrid homogeneously weighted moving average control chart for process monitoring: Discussion

The sensitivity of a monitoring scheme depends on many factors including the variance of the charting statistic which is very important in the computation of the control limits. This paper discusses the computation of the variance of the recently proposed hybrid homogeneously weighted moving average (HHWMA) $\overline{X}$ scheme which was based on an incorrect assumption. The correct variance is used to evaluate the run-length characteristics of the HHWMA $\overline{X}$ scheme. It is observed that the incorrect variance has a significant impact on the sensitivity (or performance) of the HHWMA $\overline{X}$ scheme.     

Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

无线电综合测试仪校准装置的研究及其不确定度分析

This calibration device of radio comprehensive tester is studied and established in this paper. It solves the verification and calibration of a large number of general-purpose radio comprehensive testers. The calibration device consists of four calibration sub- systems and calibration software system, including RF generator, audio generator, audio analyzer and RF analyzer. It also researches on the configuration of standard equipment and analyzes the uncertainty of the calibration devices, ensuring accurate and reliable val- ue transfer.     

烟道流量计量标准装置

为了解决我国烟道流量计的量值溯源问题,中国计量科学研究院建立了烟道流量计量标准装置。装置使用可溯源至标准转盘的激光多普勒测速仪作为原级标准器,采用激光多普勒流速剖面扫描和超声流量计波动修正的方式测量标准流量,经校准的8声道超声流量计为工作级标准表,具备了908~104840m3/h的测量能力,扩展不确定度为0.62%(k=2),可对最大口径为1m的流量计进行校准。装置下游测试段包括圆形管段和矩形管段,能够开展烟道流量计测量性能的研究。     

广州市郊填埋场附近蔬菜重金属检测与讨论

蔬菜是人们餐桌上必不可少的食物,重金属在受污染的自然环境中又无处不在,而蔬菜中的重金属含量尤其令人担忧。本文使用原子吸收分光光度法(石墨炉)和原子荧光分光光度法检测了广州市郊某垃圾填埋场附近所种植蔬菜中重金属含量。结果:抽样由2013年10月至2014年9月共持续一年,共抽样检测12次,按平均每个月一次的频率,检测结果并未发现有蔬菜超出国家规定的限量值。     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

减少手术创伤始终是妇科肿瘤手术快速康复的决定性因素

减少手术创伤始终是快速康复的决定性因素,这一点在目前的加速康复外科研究尤其是复杂手术,如妇科肿瘤手术中尚未得到充分重视。尊重学习曲线、全面规划手术方案、总结失利经验、开展前瞻性研究是解决此问题的主要方案。本文着重讨论妇科肿瘤手术创伤对术后加速康复的影响及可能的改进措施。     

The World robot summit disaster robotics category – achievements of the 2018 preliminary competition

The World Robot Summit is a robot Olympics and aims to be held in a different country every four years from 2020. The concept of the Plant Disaster Prevention challenge is daily inspections, checks, and emergency response in industrial plants, and in this competition, robots must carry out these types of missions in a mock-up plant. The concept of the Tunnel Disaster Response and Recovery challenge is emergency response to tunnel disasters, and is a simulation competition whereby teams compete to show their ability to deal with disasters, by collecting information and removing debris. The Standard Disaster Robotics challenge assesses, in the form of a contest, the standard performance levels of a robot that are necessary for disaster prevention and emergency response. The World Robot Summit Preliminary Competition was held at Tokyo Big Sight in October 2018, and 36 teams participated in the Disaster Robotics Category. UGVs and UAVs contended the merits of new technology for solving complex problems, using core technologies such as mobility, sensing, recognition, performing operations, human interface, autonomous intelligence etc., as well as system integration and implementation of strategies for completing missions, gaining high-level results.     

无源光网络标准发展及关键技术研究

无源光网络(Passive Optical Network,PON)作为当今接入网的主要技术解决方案,具有带宽使用效率高、传输距离远、抗干扰能力强等特点.通过研究PON技术的发展动态,本文首先归纳了各种PON技术的产生背景和应用特点,整理出各技术间的连接关系及主要标准;其次介绍了PON技术的帧结构,并对带宽、波长、传输模式等PON技术的主要参数进行了汇总;然后将国内外研究热点进行划分,围绕媒体访问控制协议、帧结构、动态带宽分配算法、节能机制等关键技术,阐述了其研究现状及在PON中的重要作用;最后对PON技术的发展趋势进行了展望.     

Residual learning rates in lead-acid batteries: Effects on emerging technologies

The low price of lead-acid, the most popular battery, is often used in setting cost targets for emerging energy storage technologies. Future cost reductions in lead acid batteries could increase investment and time scales needed for emerging storage technologies to reach cost-parity. In this paper the first documented model of cost reductions for lead-acid batteries is developed. Regression to a standard experience curve using 1989–2012 data yield a poor fit, with R² values of 0.17 for small batteries and 0.05 for larger systems. To address this problem, battery costs are separated into material and residual costs, and experience curves developed for residual costs. Depending on the year, residual costs account for 41–86% of total battery cost. Using running-time averages to address volatility in material costs, a 4-year time average experience curve for residual costs yield much higher R², 0.78 for small and 0.74 for large lead-acid batteries. The learning rate for residual costs in lead-acid batteries is 20%, a discovery with policy implications. Neglecting to consider cost reductions in lead-acid batteries could result in failure of energy storage start-ups and public policy programs. Generalizing this result, learning in incumbent technologies must be understood to assess the potential of emerging ones.