[数据驱动的产品设计]基于功能模型和层次分析法的智能产品服务系统概念方案构建

为研究智能产品服务系统概念方案的构建，解决系统的复杂特性和功能耦合特性，提出应用发明问题解决理论（TRIZ）功能模型和层次分析法(AHP)两种工具，在概念设计阶段利用TRIZ功能模型定性地对其进行分析建模，并借助层次分析法对不同服务供应商所提供的服务功能模块进行定量的决策分析，通过择优集成相关功能模块，形成智能产品服务系统概念方案的构建方法。最后以3家服务供应商的服务功能模块构建为例，验证该方法的有效性。     

Does interior color contrast enhance spatial memory?

This study investigated the effect of contrast in neutral-, warm-, and cool-colored spaces on spatial memory. Spatial memory was measured in terms of architectural scale and recollection of architectural elements and furniture. Participants (N = 114) viewed a short virtual simulation video of a residential studio and were asked to sketch a map of the architectural elements on distributed grid paper. Spatial memory was measured in terms of scale, and item recall rate. Contrast and hue had no significant effect on the memorization of proportional scale. However, high-contrast schemes allowed for a significantly higher recollection of architectural elements than low-contrast schemes. In comparing the effect of hues, a significant difference was seen in recalling detailed furniture and lighting items. Participants reported significantly better spatial memory of neutral and warm color schemes than of cool color schemes. There was no interaction effect between contrast and hue in the color combinations. These results can be applied in the design of color schemes for architectural spaces requiring enhanced spatial cognition and memory.     

单相并联型有源电力滤波器主电路参数耦合关系研究

单相并联型有源电力滤波器(SAPF)主电路参数之间存在一定的耦合关系,这对各参数值的合理选择有较大的影响。通过分析现有单/三相SAPF主电路交流侧电感以及直流侧电压、电容值等参数的计算方法,得到了具体的单相SAPF电路参数解析表达式。针对所得表达式各变量之间的耦合关系,在MATLAB中进行建模优化分析,得出一套完整的参数设计方案。保证在特定负载下补偿后谐波含量低于2%的综合优化目标。仿真和实验过程验证了所选参数的正确性。     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

基于网络数据统计的食品欺诈研究分析

目的 建立符合我国国情的食品欺诈数据库, 补充国际上已建立的经济利益驱动型掺假(economically motivated adulteration, EMA)数据库空白。方法 搜集2001~2019年发生的食品欺诈行为, 初步建立具有中国国情的食品欺诈数据库。对数据库中信息完备的454条欺诈数据进行分析。结果 媒体报道数据占食品欺诈信息总数的71.6%; 食用农产品、酒类、乳制品、肉制品等11类产品是欺诈事件发生较多的食品类别; 产品欺诈(72.2%)高居食品欺诈类型的首位; 2001~2019年食品欺诈事件数量呈现出先上升后降低, 再上升再降低的“M”状趋势; 目前食品欺诈检测技术主要以理化分析技术为主, 针对的食品类别还有限; 食品欺诈信息以中国为主(89.0%), 涉及到世界各个地区。结论 食品欺诈是广泛存在的全球性问题, 本研究建立的食品欺诈数据库为预防食品安全风险起到了重要的技术支撑作用。     

某800 t/d级浮法薄玻璃生产线项目建设的得失分析

总结了某800 t/d浮法薄玻璃生产线项目建设的教训与经验,通过项目过程中发生的真实案例,对项目建设中存在的不足进行了深入剖析,并就项目的方案制定、材料与供方选择、建设工期与质量控制等工作提出了改进建议。     

某铅锌矿的三维地质模型及储量估算

针对矿山现有的地质信息数据等，建立了以利用Surpac软件的三维地表模型、矿体模型及地质数据库，对矿山资源储量进行计算。基于地质统计学的理论，建立某铅锌矿地表模型、钻孔数据库、矿体模型、块体模型，对矿体内样品进行组合分析统计，采用幂次距离反比法对块体品位进行估值，最后根据国内对地质矿产资源的分类方法，按照不同边界品位、工业品位等分类依据，得出资源储量核实报告，为铅锌矿的后续生产，提供了可靠保证。结果表明：通过构建该矿地质数据库，建立的三维模型，可对地质工程、采矿工程、储量估算、矿石品位动态管理等提供技术支持。     

Model recovery anti-windup for output saturated SISO linear closed loops

We define model recovery anti-windup for SISO linear control systems with output saturation. We address the problem by relying on a hybrid modification of the linear closed loop which employs a suitable logic variable to activate/deactivate various components of a control scheme. The scheme relies on a finite-time observation law, an open-loop observer and an open-loop input generator which is capable of driving the plant output within the saturation limits. Then the control scheme is based on suitable (hybrid) resetting laws allowing the controller to operate on the artificial output signal generated by the open-loop observer when the actual plant output is outside the saturation limits. Unlike existing results, not only we prove uniform global asymptotic stability of the closed loop, but we also prove the local preservation and global recovery properties, typical of model recovery anti-windup paradigms. We also illustrate the proposed technique on an example study.     

An efficient unstructured MUSCL scheme for solving the 2D shallow water equations

The aim of this paper is to present a novel monotone upstream scheme for conservation law (MUSCL) on unstructured grids. The novel edge-based MUSCL scheme is devised to construct the required values at the midpoint of cell edges in a more straightforward and effective way compared to other conventional approaches, by making better use of the geometrical property of the triangular grids. The scheme is incorporated into a two-dimensional (2D) cell-centered Godunov-type finite volume model as proposed in Hou et al. (2013a,c) to solve the shallow water equations (SWEs). The MUSCL scheme renders the model to preserve the well-balanced property and achieve high accuracy and efficiency for shallow flow simulations over uneven terrains. Furthermore, the scheme is directly applicable to all triangular grids. Application to several numerical experiments verifies the efficiency and robustness of the current new MUSCL scheme.     

Random-valued impulse noise removal using adaptive dual threshold median filter

Noise detection and its removal is very important in the image processing. Detection of noise is very crucial and significant in random valued impulse noise because it does not hamper the image pixels uniformly. This paper presents a novel and unique concept of adaptive dual threshold for the detection of random valued impulse noise along with simple median filter at noise removal stage. Simulation results shows that an efficient noise detection leads to a superior quality of de-noised image as compared to existing adaptive threshold based image de-noising techniques. Proposed threshold computation is based on averaging of pixel values of window which enhances the PSNR of our system as compared to existing median filter based image de-noising methods.