Connecting parameters optimization on unsymmetrical twin-tower structure linked by sky-bridge

Based on a simplified 3-DOF model of twin-tower structure linked by a sky-bridge, the frequency response functions, the displacement power spectral density （PSD） functions, and the time-averaged total vibration energy were derived, by assuming the white noise as the earthquake excitation. The effects of connecting parameters, such as linking stiffness ratio and linking damping ratio, on the structural vibration responses were then studied, and the optimal connecting parameters were obtained to minimize the vibration energy of either the independent monomer tower or the integral structure. The influences of sky-bridge elevation position on the optimal connecting parameters were also discussed. Finally, the distribution characteristics of the top displacement PSD and the structural responses, excited by El Centro, Taft and artificial waves, were compared in both frequency and time domain. It is found that the connecting parameters at either end of connection interactively affect the responses of the towers. The optimal connecting parameters can greatly improve the damping connections on their seismic reduction effectiveness, but are unable to reduce the seismic responses of the towers to the best extent simultaneously. It is also indicated that the optimal connecting parameters derived from the simplified 3-DOF model are applicable for two multi-story structures linked by a sky-bridge with dampers. The seismic reduction effectiveness obtained varies from 0.3 to 1.0 with different sky-bridge mass ratio. The displacement responses of the example structures are reduced by approximately 22% with sky-bridge connections.     

新颖的绕线拉紧装置

本文介绍一种新型适用的线圈绕制中的线材拉紧装置，并将其与传统的拉紧装置进行比较，得出各自的优缺点。     

Ehrenfeucht-Fraïssé games in finite set theory

In this article, with Ehrenfeucht-Fraïssé games we prove that Δ₁≠Δ₀ on BFR, which implies Δ≠Δ₀ on BFR, and thus solve an open problem raised by Albert Atserias in his dissertation (Δ₀,Δ₁,Δ are fragments of first order logic and BFR is a class of finite sets which in essence is equivalent to a class of finite pure arithmetic structures with built-in BIT predicate).     

Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems

If the production process, production equipment, or material changes, it becomes necessary to execute pilot runs before mass production in manufacturing systems. Using the limited data obtained from pilot runs to shorten the lead time to predict future production is this worthy of study. Although, artificial neural networks are widely utilized to extract management knowledge from acquired data, sufficient training data is the fundamental assumption. Unfortunately, this is often not achievable for pilot runs because there are few data obtained during trial stages and theoretically this means that the knowledge obtained is fragile. The purpose of this research is to utilize bootstrap to generate virtual samples to fill the information gaps of sparse data. The results of this research indicate that the prediction error rate can be significantly decreased by applying the proposed method to a very small data set.     

REMARKS ON JOHN DISKS

Let D■R2 be a Jordan domain,D*=R2\D,the exterior of D.In this article,the authors obtained the following results:(1)If D is a John disk,then D is an outer linearly locally connected domain;(2)If D* is a John disk,then D is an inner linearly locally connected domain;(3)A homeomorphism f:R 2 →R 2 is a quasiconformal mapping if and only if f(D)is a John disk for any John disk D■R 2 ;and(4)If D is a bounded quasidisk,then D is a John disk,and there exists an unbounded quasidisk which is not a John disk.     

Chinese-based research on subject-covered information retrieval supervised by textual semantic domain

By means of analysis of artificial intervention in ready-retrieved text, training set used to compare with new texts from large-scale real texts corpus is provided. It is based on the data-originated presentation of training set that a special formula to calculate semantic cohesion between new texts and training set is devised. The semantic cohesion of new text is the average value of semantic evaluation of all elements involved, and semantic evaluation of an element depends on its semantic relevance with the training set and on the semantic ratio of its domain to synonymous domain. In terms of empirical verification a conclusion is drawn that semantic cohesion is the key measurement standard of textual retrieval. Despite the advantages of textual retrieval, limitations of formula-raised condition and analyst＇s accomplishments make the analysis involved in this paper imperfect.     

基于动态贝叶斯网络的社交圈归属匹配模型

为了帮助社交网中新成员寻找与之最为合适的社交圈,尝试采用动态贝叶斯网（DBN）理论解决社交网分析应用中成员（节点）与社交圈（集合）的匹配问题。将圈内成员个人的多项兴趣爱好程度作为描述社交圈基本属性的特征向量,对每一类圈子建立了带有辅助信息形式的DBN模型,求解最大输出概率即为最佳匹配对象。结果表明,在客观测试和主观评价两方面,该模型都收到了较为满意的结果。     

A level set method based on the Bayesian risk for medical image segmentation

This paper proposes an alternative criterion derived from the Bayesian risk classification error for image segmentation. The proposed model introduces a region-based force determined through the difference of the posterior image densities for the different classes, a term based on the prior probability derived from Kullback-Leibler information number, and a regularity term adopted to avoid the generation of excessively irregular and small segmented regions. Compared with other level set methods, the proposed approach relies on the optimum decision of pixel classification and the estimates of prior probabilities; thus the approach has more reliability in theory and practice. Experiments show that the proposed approach is able to extract the complicated shapes of targets and robust for various types of medical images. Moreover, the algorithm can be easily extendable for multiphase segmentation.     

基于C—V模型的目标检测与提取

在目标检测与提取中,传统的蛇模型和基于活动轮廓的局部区域检测方法受到初始条件或者自身的收敛性约束的影响,不仅时间花费多,而且不具备鲁棒性。本文提出一种基于C V模型的变分水平集的目标检测与提取方法,通过大量实验验证,在花费时间和鲁棒性上得到了显著的改善。