Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Profiling engineered data with robust mining methods continues attracting attention in knowledge engineering systems. The purpose of this article is to propose a simple technique that deals with non-linear multi-factorial multi-characteristic screening suitable for knowledge discovery studies. The method is designed to proactively seek and quantify significant information content in engineered mini-datasets. This is achieved by deploying replicated fractional-factorial sampling schemes. Compiled multi-response data are converted to a single master-response effectuated by a series of distribution-free transformations and multi-compressed data fusions. The resulting amalgamated master response is deciphered by non-linear multi-factorial stealth stochastics intended for saturated schemes. The stealth properties of our method target processing datasets which might be overwhelmed by a lack of knowledge about the nature of reference distributions at play. Stealth features are triggered to overcome restrictions regarding the data normality conformance, the effect sparsity assumption and the inherent collapse of the ‘unexplainable error’ connotation in saturated arrays. The technique is showcased by profiling four ordinary controlling factors that influence webpage content performance by collecting data from a commercial browser monitoring service on a large scale web host. The examined effects are: (1) the number of Cascading Style Sheets files, (2) the number of JavaScript files, (3) the number of Image files, and (4) the Domain Name System Aliasing. The webpage performance level was screened against three popular characteristics: (1) the time to first visual, (2) the total loading time, and (3) the customer satisfaction. Our robust multi-response data mining technique is elucidated for a ten-replicate run study dictated by an L₉(3⁴) orthogonal array scheme where any uncontrolled noise embedded contribution has not been necessarily excluded.     

SIMS as a subnanometer probe: A new tool for chemical profile analysis of grafted molecules

The complexity of modern engineered surfaces requires the development of very powerful methods to analyze and characterize them. We demonstrate that it is possible to obtain chemical information about the skeleton of organic molecules constituting SAMs grafted on a silicon surface by using a new type of SIMS method. A profile can be achieved by the investigation of the temporal variation of secondary ion intensities that correspond to the fractional parts of the molecule constituting the SAMs. The equivalent ablation rate is less than 0.5 nm/min.     

Au-Au2S复合纳米球壳微粒的空腔谐振及参量讨论

Au-Au2S复合纳米球壳微粒（金纳米球壳），是一种新型复合结构的纳米微粒，其结构为纳米级的Au2S介质球外包裹了一层几个纳米厚的黄金球壳。这种复合纳米球壳微粒可以被抽象为球型谐振腔。报道了它的空腔谐振吸收的实验结果，并且运用经典理论结合介观结构特征，讨论了有关Au-Au2S复合纳米球壳微粒空腔谐振吸收的一些重要参量，其中包括谐振吸收波长、品质因数、谐振能量等。另外，还讨论了金球壳的厚度对这些重要参量的影响。     

机载海洋激光测深系统参量设计与最大探测深度能力分析

详细讨论了机载海洋激光测深系统最大测量深度与相关因子之间的关系，并利用最小可探测信噪比为判据，对机载海洋激光测深系统在白天和晚上工作进行了数值模拟，通过比较最大测量深度与激光脉冲峰值功率、接收视场角、接收口径和光谱接收带宽等关系，确定了系统的主要参量。以确定的参量建立的系统具有白天49m和晚上65m的最大测深能力，可完全满足在沿岸带以及岛礁的测量要求。     

放射性9C束流不同贯穿深度上的线能谱测量

为阐述放射性⁹C束流应用于治癌的物理基础, 运用一个球形生物组织等效正比计数器测量了⁹C束流不同贯穿深度上的线能谱, 得到了沿束流贯穿深度上的剂量平均线能分布. 将实验测量得到的线能谱转换成为不同传能线密度在吸收剂量中所占份额的分布, 得到了该⁹C束流在不同贯穿深度上的剂量平均传能线密度分布. 将生物组织等效正比计数器测量得到的与先前通过平行板正比计数器测量得到的该⁹C束流的剂量平均传能线密度分布进行比较, 发现: 在束流入射通道上, 两者测量数据符合很好, 而在束流Bragg峰附近⁹C离子的沉积区域, 由组织等效正比计数器测量得到的剂量平均传能线密度值大于由平行板正比计数器测量得到的值.     

Quantitative Depth Profiling of K-Doped Fullerene Films Using XPS and SIMS

 Phenomena accompanying electrochemical doping of solid fullerene films with potassium were studied by sputter ion depth profiling (XPS and SIMS). The potassium distribution was determined, and artifacts associated with possible damage of the layer composition caused by ion impact were investigated and discussed. To compare the charge transfer while reductive doping is taking place at fullerene/solution interface with doping from gas phase, model layers were prepared and doped by potassium under UHV conditions. It was found that sputtering by Ar⁺ primary ions yields both accurate information on the alkaline metal distribution and on its concentration. Sputtering by O⁺ ions led to an enrichment of potassium, apparently due to the reactivity of oxygen with the fullerene matrix. It is shown that the reductive doping starts at the fullerene/solution interface. The concentration of potassium in the doped films was found to be lower than expected from the charge transferred during the electrochemical reduction. Other phase transformations such as hydrogenation are discussed. Received March 4, 2002; accepted July 26, 2002     

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研制出了用于计算氚投料量在FEB聚变堆各个子系统中的分布及其随时间变化的数值模拟程序包SWITRIM。通过近5年的使用，表明其运行良好、计算结果可靠。用SWITRIM数值模拟研究了聚变堆起动过程中的“氚坑深度和氚坑时间”新现象。简单介绍了SWITRIM程序包的组成和用户使用说明以及最新的运用等。     

~2样本深度的基本性质

本文讨论由L2深度修正得到的L2深度相应的样本深度的性质,得到了样本深度的相合性和渐近正态性,并证明了它在任意紧集上的一致相合性．最后,基于上述性质简要讨论了样本深度等高的一些性质．     

Optical characteristics of semiconductor saturable absorber mirrors investigated by the reflection Z-scan technique

Recently, the semiconductor saturable absorber mirror (SESAM) has become a key component of passive mode-locked solid-state lasers. Here we present a simple method based on the reflection Z-scan technique to measure the key optical parameters of SESAM such as saturation fluence and modulation depth. The experimental results demonstrate that our method is able to perform with a high accuracy of 10⁻⁴ and a dynamic range of over four orders of magnitude.     

Extension of multivariate regression trees to interval data. Application to electricity load profiling

Summary  Several data can be presented as interval curves where intervals reflect a within variability. In particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load profiling consists in assigning a daily load curve to a customer based on their characteristics such as energy requirement. Within the load profiling scope, this paper investigates the extension of multivariate regression trees to the case of interval dependent (or response) variables. The tree method aims at setting up simultaneously load profiles and their assignment rules based on independent variables. The extension of multivariate regression trees to interval responses is detailed and a global approach is defined. It consists in a first stage of a dimension reduction of the interval response variables. Thereafter, the extension of the tree method is applied to the first principal interval components. Outputs are the classes of the interval curves where each class is characterized both by an interval load profile (e.g. the class prototype) and an assignment rule based on the independent variables.