Functional Features and Layouts of Yangzhou Residential Gardens in the Late Qing Dynasty and the Early Republic of China: A Case Study of Residential Gardens of Officials, Merchants and Literati

On the basis of analyzing socio-economic structures, social classes and their relations in the late Qing Dynasty and the early Republic of China, this paper took residential gardens of three principal groups(officials, merchants and literati) for example, analyzed functional features and layouts of the gardens, explored artistic characteristics and cultural connotations of the local residential gardens, so as to provide references for the conservation and construction of historic and cultural cities, design and expression of modern urban livable spaces.

Introducing the nth-Order Features Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (nth-FASAM-N): II. Illustrative Example

This work highlights the unparalleled efficiency of the “nth-Order Function/ Feature Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-FASAM-N) by considering the well-known Nordheim-Fuchs reactor dynamics/safety model. This model describes a short-time self-limiting power excursion in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This nonlinear paradigm model is sufficiently complex to model realistically self-limiting power excursions for short times yet admits closed-form exact expressions for the time-dependent neutron flux, temperature distribution and energy released during the transient power burst. The nth-FASAM-N methodology is compared to the extant “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-CASAM-N) showing that: (i) the 1st-FASAM-N and the 1st-CASAM-N methodologies are equally efficient for computing the first-order sensitivities;each methodology requires a single large-scale computation for solving the “First-Level Adjoint Sensitivity System” (1st-LASS);(ii) the 2nd-FASAM-N methodology is considerably more efficient than the 2nd-CASAM-N methodology for computing the second-order sensitivities since the number of feature-functions is much smaller than the number of primary parameters;specifically for the Nordheim-Fuchs model, the 2nd-FASAM-N methodology requires 2 large-scale computations to obtain all of the exact expressions of the 28 distinct second-order response sensitivities with respect to the model parameters while the 2nd-CASAM-N methodology requires 7 large-scale computations for obtaining these 28 second-order sensitivities;(iii) the 3rd-FASAM-N methodology is even more efficient than the 3rd-CASAM-N methodology: only 2 large-scale computations are needed to obtain the exact expressions of the 84 distinct third-order response sensitivities with respect to the Nordheim-Fuchs model’s parameters when applying the 3rd-FASAM-N methodology, while the application of the 3rd-CASAM-N methodology requires at least 22 large-scale computations for computing the same 84 distinct third-order sensitivities. Together, the nth-FASAM-N and the nth-CASAM-N methodologies are the most practical methodologies for computing response sensitivities of any order comprehensively and accurately, overcoming the curse of dimensionality in sensitivity analysis.

Global innovators to feature in Intertextile Shanghai's Functional Lab

Heading into the second half of the year,the global apparel fabrics and accessories industry’s attention has begun to focus on the 2016 Autumn Edition of Intertextile Shanghai Apparel Fabrics which will be held from 11–13 October.Over 5,000 exhibitors from more than 25 countries and regions will take part and showcase an all-encompassing range of products across 260,000 sqm.of exhibition space at the Nation Exhibition and Convention Center(Shanghai).To

An Exploratory Study of E-Business Success Factors

E-business success factors are Important for traditional enterprises to implement e-business. This topic is attracting more and more researchers to study. This paper makes an exploratory study on the factors influencing e-business success. Firstly, based on the literature review, 52 factors are suggested. Secondly, two rounds of survey with Delphi method are conducted. Qualitative and quantitative analysis are used to identify 57 factors. This is the foundation of empirical study.

Application of Particle Swarm Optimization to Fault Condition Recognition Based on Kernel Principal Component Analysis

Panicle swarm optimization （PSO） is an optimization algorithm based on the swarm intelligent principle. In this paper the modified PSO is applied to a kernel principal component analysis （ KPCA ） for an optimal kernel function parameter. We first comprehensively considered within-class scatter and between-class scatter of the sample features. Then, the fitness function of an optimized kernel function parameter is constructed, and the particle swarm optimization algorithm with adaptive acceleration （CPSO） is applied to optimizing it. It is used for gearbox condi- tion recognition, and the result is compared with the recognized results based on principal component analysis （PCA）. The results show that KPCA optimized by CPSO can effectively recognize fault conditions of the gearbox by reducing bind set-up of the kernel function parameter, and its results of fault recognition outperform those of PCA. We draw the conclusion that KPCA based on CPSO has an advantage in nonlinear feature extraction of mechanical failure, and is helpful for fault condition recognition of complicated machines.

TWO-STAGE OCCLUDED OBJECT RECOGNITION METHOD FOR MICROASSEMBLY

A two-stage object recognition algorithm with the presence of occlusion is presented for microassembly. Coarse localization determines whether template is in image or not and approximately where it is, and fine localization gives its accurate position. In coarse localization, local feature, which is invariant to translation, rotation and occlusion, is used to form signatures. By comparing signature of template with that of image, approximate transformation parameter from template to image is obtained, which is used as initial parameter value for fine localization. An objective function, which is a function of transformation parameter, is constructed in fine localization and minimized to realize sub-pixel localization accuracy. The occluded pixels are not taken into account in objective function, so the localization accuracy will not be influenced by the occlusion.

Cortical functional connectivity features between bipolar and unipolar depression patients

Objective To explore the differences of cortico-cortical functional connectivity features among patients with bipolar and unipolar depression in resting state.Methods Whole-head magnetoencephalography scan was performed in an resting state condition in 12 bipolar depression patients,27 unipolar depression patients and

Modular Design of Complex Product Based on the Triple Fusion of Function/Feature/Knowledge

The modular design technology is of importance increasingly,as product structure is more and more complex.Modular design systems face challenging problems as the design information tends to be dynamic,redundant,and very large.This paper describes a novel approach for handling them.In this approach,a partition is firstly performed for the complex structural components by mapping functions to the structures layer by layer.Based on this partition,a comprehensive design matrix is then developed to identify the key design mode which is driven by a special function.The design process is also programmed by analyzing the coupled information on both the functional and structural hierarchies.Then,the integrated knowledge model based on object-oriented method and hybrid inference method is constructed.In this model,knowledge can be organized at hierarchical classification and expressed with different forms.Finally,the methodology developed has been applied to a real application in automobile cylinder block design and the results are presented.