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.     

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.     

A charge sharing–based switching scheme for SAR ADCs

This paper presents an energy-efficient switching scheme for successive approximation register (SAR) analogue-to-digital converter (ADC). The proposed scheme employs charge recycling method to keep the capacitor arrays free of transitional energy between bit generations except reset phase. In comparison with the conventional switching scheme, the proposed one achieves 100% transitional energy saving without considering reset phase. In addition, configuration of a 10-bit SAR ADC shows that the proposed switching scheme reduces the capacitor area by 25% compared with the conventional switching scheme.     

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。     

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.     

皮带秤秤架的响应特性曲线分析

介绍了皮带秤秤架响应特性曲线分析方法，对四种结构形式的秤架进行了响应特性曲线分析和比较，得出的结论是：悬浮式秤架的计量特性最好。     

茂金属线型低密度聚乙烯的加工性能

采用齐聚-共聚复合催化剂合成出了相对分子质量分布指数大于4的原位共聚线型低密度茂金属聚乙烯(mLLDPE)。流变实验结果表明,mLLDPE具有切敏性和非温敏性。改性实验结果表明,向100质量份mLLDPE中加入5质量份氟母粒,或10质量份LDPE,或2质量份氟母粒和5质量份LDPE,可使mLLDPE的加工流动性能获得改善,聚合物的机械性能不会发生明显降低,可用常规加工设备加工。加工成型实验结果表明,使用65型管材挤出机和TDL-12L中空成型机,以氟母粒-LDPE复合改性mLLDPE为原料,可生产出内、外表面均光滑的32管材和10L中空容器,挤出过程稳定。     

扬声器系统时域结构系数的仿真

从扬声器系统的等效类比线路出发,得出了阻抗特性Z(jω)的表达形式及其曲线。采用全面最小二乘法识别扬声器系统的时域函数的全套系数,从而测出扬声器系统的低频特性参数。以计算机仿真技术为基础,通过MATLAB和EWB软件进行系统模拟分析仿真,得到扬声器系统的阶跃响应、阻抗曲线等特性。     

一种基于Normal基椭圆曲线密码芯片的设计

文章设计了一款椭圆曲线密码芯片。实现了GF（2^233）域上normal基椭圆曲线数字签名和认证。并支持椭圆曲线参数的用户配置。在VLSI的实现上，提出了一种新的可支持GF（2^233）域和GF（p）域并行运算的normal基椭圆曲线VLSI架构。其架构解决了以往GF（p）CA算迟后于GF（2^233）域运算的问题，从而提高了整个芯片的运算吞吐率。基于SMIC 0．18μm最坏的工艺，综合后关键路径最大时延3．8ns，面积18mm^2；考虑布局布线的影响，芯片的典型的情况下，每秒可实现8000次签名或4500次认证。     

一种基于PWM的电压输出DAC电路设计

对实际应用中的脉宽调制(PWM)波形的频谱进行了理论分析．指出通过一个低通滤波器可以把PWM调制的数模转换信号解调出来．实现从PWM到DAC的转换。论文还对转换误差产生的因素进行了分析，指出了减少误差的方法，论文给出了两种从PWM到0～5V电压输出的电路实现方法，第2种电路具有很高的转换精度。