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基于数值仿真计算和微波网络理论,提出了一种多层介质中频率选择表面(FSS)等效电路的分析方法。该方法物理过程直观,计算量小,适用于二维任意形状FSS等效电路的精确求解。以方形贴片型FSS为例验证了等效电路模型的准确性,并分析了多层介质对其等效电路参数的影响规律。最后,基于滤波器理论与FSS等效电路模型设计了双层带通型FSS,计算结果表明全波仿真结果与理论计算结果基本一致,为多层FSS的综合设计提供了一种精确设计方法。 相似文献
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对基于高等师范学校古代汉语教学的语料库相关数据结果做了定量分析,阐述了语料库的用字概况,提出了字区划分的标准,研制了分区字频表。 相似文献
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《Enterprise Information Systems》2013,7(4):433-444
In today's business environment, enterprises are increasingly under pressure to process the vast amount of data produced everyday within enterprises. One method is to focus on the business intelligence (BI) applications and increasing the commercial added-value through such business analytics activities. Term weighting scheme, which has been used to convert the documents as vectors in the term space, is a vital task in enterprise Information Retrieval (IR), text categorisation, text analytics, etc. When determining term weight in a document, the traditional TF-IDF scheme sets weight value for the term considering only its occurrence frequency within the document and in the entire set of documents, which leads to some meaningful terms that cannot get the appropriate weight. In this article, we propose a new term weighting scheme called Term Frequency – Function of Document Frequency (TF-FDF) to address this issue. Instead of using monotonically decreasing function such as Inverse Document Frequency, FDF presents a convex function that dynamically adjusts weights according to the significance of the words in a document set. This function can be manually tuned based on the distribution of the most meaningful words which semantically represent the document set. Our experiments show that the TF-FDF can achieve higher value of Normalised Discounted Cumulative Gain in IR than that of TF-IDF and its variants, and improving the accuracy of relevance ranking of the IR results. 相似文献
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This research examines the important emerging area of online customer experience (OCE) using data collected from an online survey of frequent and infrequent online shoppers. The study examines a model of antecedents for cognitive and affective experiential states and their influence on outcomes, such as online shopping satisfaction and repurchase intentions. The model also examines the relationships between perceived risk, trust, satisfaction and repurchase intentions. Theoretically, the study provides a broader understanding of OCE, through insights into two shopper segments identified as being important in e-retailing. For managers, the study highlights areas of OCE and their implications for ongoing management of the online channel. 相似文献
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We provide a structural approach to identify instantaneous causality effects between durations and stock price volatility. So far, in the literature, instantaneous causality effects have either been excluded or cannot be identified separately from Granger type causality effects. By giving explicit moment conditions for observed returns over (random) duration intervals, we are able to identify an instantaneous causality effect. The documented causality effect has significant impact on inference for tick-by-tick data. We find that instantaneous volatility forecasts for, e.g., IBM stock returns must be decreased by as much as 40% when not having seen the next quote change before its (conditionally) median time. Also, instantaneous volatilities are found to be much higher than indicated by standard volatility assessment procedures using tick-by-tick data. For IBM, a naive assessment of spot volatility based on observed returns between quote changes would only account for 60% of the actual volatility. For less liquidly traded stocks at NYSE this effect is even stronger. 相似文献
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