不同声音偏好的游客声景观主观评价差异——以丽江大研古镇为例*

古镇作为集自然景观与人文景观一体的景区，具有丰富的声音类型。本研究以大研古镇为例，通过实地调研探究不同声音偏好的游客对古镇声景观的主观评价差异。基于游客的声音偏好，将游客分为偏爱自然声和偏爱人工声两大类。通过因子分析提取游客声景观主观评价的5个主因子：大小、音质、效价、偏好和唤醒。进一步分析发现，这5个因子具有一定的层级性，其中从大小到唤醒代表声景观评价从声音的物理属性向声音的联想评价逐级提升。其中在低层级评价(大小、音质)中，偏好自然声的游客和偏好人工声的游客无显著差异，低层级评价具有稳定性；而在高层级评价(效价、偏好和唤醒)中，偏好人工声的游客更关注古镇声景观的淳朴性和遗产性。因此，游客对声景观的主观评价可视为一种指标，判断景区声景所处的评价阶段，从而为景区声景观改善提供更有针对性的建议。     

An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.     

自旋-轨道耦合系统中的自旋流定义

通常的自旋流定义在描述自旋-轨道耦合系统中的自旋输运是不完整的与非物理的。文章作者提出在这类系统中自旋流的恰当定义。新定义的自旋流克服了通常定义下的本质缺点，可通过实验直接观测。     

可重构制造系统重组过程中设备选择模型的研究

根据生产任务选择加工设备进行制造资源重组是实现可重构制造系统的关键问题之一，由于设备的选择涉及到多种因素，既有定量指标，又有定性指标，传统的依靠人工经验的方法显得力不从心。本文首先结合实际情况，提出了一套设备选择评价体系，通过对模糊判断矩阵采用最小对数二乘法确定各评价因素的权重系数，针对定性指标和定量指标采用不同的方法确定其性能指标值，通过模糊积分对评判指标进行综合评判，最后进行了实例研究。所提出的方法有效地简化了决策过程，为可重构制造系统设备选择提供了一套行之有效的方法。     

93W合金有关力学参量的综合选评

 对93W合金材料进行了超声测量实验，并结合原有的超声测量结果进行了分析比较，提出了可以直接用冲击波速度关系式的三个系数c₀ 、λ和λ′来对钨合金的有关力学参量，如G₀、K₀、G₀′、K₀′等进行综合选评的方法。得到了一组对93W合金较为合理的力学参量推荐值。     

具有模糊数的模糊多目标群体决策优选模型与方法

多目标群体决策问题是运筹学的一个重要研究领域，目前已经提出了一些有效的决策方法。但对目标值和权重均为模糊数的模糊多目标群体决策问题却研究不多，本对此类模糊多目标群体决策问题进行了探讨，利用相对正理想方案与相对负理想方案概念定义了相对差异距离，进而建立了模糊多目标群体决策优选模型与方法，并通过战役决心方案的评价说明了该方法是可行、有效的，可作为军事决策与决策支持系统的备选方法。     

Patterns and Symmetries in the Visual Cortex and in Natural Images

As borders between different entities, lines are an important element of natural images. Indeed, the neurons of the mammalian visual cortex are tuned to respond best to lines of a given orientation. This preferred orientation varies continuously across most of the cortex, but also has vortex-like singularities known as pinwheels. In attempting to describe such patterns of orientation preference, we are led to consider underlying rotation symmetries: Oriented segments in natural images tend to be collinear; neurons are more likely to be connected if their preferred orientations are aligned to their topographic separation. These are indications of a reduced symmetry requiring joint rotations of both orientation preference and the underlying topography. This is verified by direct statistical tests in both natural images and in cortical maps. Using the statistics of natural scenes we construct filters that are best suited to extracting information from such images, and find qualitative similarities to mammalian vision. PACS84.35+i 89.70.+c 87.57.Nk     

A Genetic Search for Exploiting a Fuzzy Preference Model of Portfolio Problems with Public Projects

When an organization solves a portfolio problem with public projects evaluated by multiple criteria, in which the economic dimension is not essential or not well characterized, the classical methods are not useful. We propose a non-linear preference model developed from normative Value Theory and using fuzzy sets to model some sources of imprecision. This model can be considered as a generalization of the classical approaches. However, the optimization problem is very complex in order to be solved with non-linear programming techniques. Therefore, the model is exploited by an evolutionary algorithm, able to achieve a strong improvement of the quality of solution.     

Toward Fuzzy Optimization without Mathematical Ambiguity

Fuzzy programming has been discussed widely in literature and applied in such various disciplines as operations research, economic management, business administration, and engineering. The main purpose of this paper is to present a brief review on fuzzy programming models, and classify them into three broad classes: expected value model, chance-constrained programming and dependent-chance programming. In order to solve general fuzzy programming models, a hybrid intelligent algorithm is also documented. Finally, some related topics are discussed.     

基于MATLAB(SIMULINK)的电弧炉电极调节系统FUZZY-PD控制器的仿真

介绍了采用MATLAB V5.2提供的模糊逻辑工具箱来设计研究电孤纺电极调节系统中的模糊－－PD控制器，讨论了在SIMULINK环境下模糊－PD控制器的参数自调速原理、结构、建立模糊控制规则库和模糊推论方法，并给出仿真结果与结论。