基于LP与小波包的复杂机电系统监测序列混沌降噪方法

针对流程工业生产系统监测数据存在强噪声和混沌性的特点,提出了一种局部投影方法(Local Projection Method)与小波包方法相结合的信号降噪方法。该方法先利用局部投影方法从动力学系统嵌入流形的角度进行多次迭代降噪,并根据关联维数来判定迭代终止;再利用小波包方法从频率的角度进行降噪,抑制高频噪声的干扰,取得了较好的降噪效果。用Lorenz时间序列进行仿真验证,对仿真时间序列加入不同程度的噪声,对比分析小波包、局部投影与该方法降噪后的相空间、SNR值和最大Lyapunov指数,证明了该方法对于中高强度噪声具有更好的降噪效果。并将该方法用于某压缩机组的实际监测数据降噪,评估三种方法的降噪效果,进一步验证了该方法的优越性。     

基于三维投影矩阵的生产流水线对接系统平台构建

针对工作台扭摆会导致机械加工对接产生误差,提出基于三维投影矩阵构建生产流水线对接系统平台,以降低对接误差。三维运动平台采用脉冲信号控制的步进电机进行驱动,达到机床限位控制;通过控制激光器开关和控制激光器的输出功率实现系统的激光控制;通过多普勒频差测量位移技术,采用交流前置放大器替换常规直流放大器等,获取精准实时测量数据;根据三维立体视觉校对原理提取对接区域图像特征点,依据特征点校验机械加工平台三维对接图像时,采用Powell方法求解三维阶段投影矩阵对接目标函数最小值,实现机械加工的高精准度对接。结果表明:机械加工对接的最大相对误差为1.50%,精准度高,进行机械加工耗时18～23min,花费时间较短。     

Automatic brain tissue segmentation in MR images using hybrid atlas forest based on confidence-weighted probability matrix

The segmentation of specific tissues in an MR brain image for quantitative analysis can assist the disease diagnosis and medical research. Therefore, a robust and accurate method for automatic segmentation is necessary. Atlas-based-method is a common and effective method of automatic segmentation where an atlas refers to a pair of image consist of an intensity image and its corresponding label image. Apart from the general multi-atlas-based methods, which propagate labels through the single atlas then fuse them, we proposed a hybrid atlas forest based on confidence-weighted probability matrix to consider the atlases set as a whole and treat each voxel differently. In the framework, we first register the atlas to the image space of target and calculate the confidence of voxels in the registered atlas. Then, a confidence-weighted probability matrix is generated and it augments to the intensity image of the atlas or target for providing spatial information of the target tissue. Third, a hybrid atlas forest is trained to gather the features and correlation information among the atlases in the dataset. Finally, the segmentation of the target tissues is predicted by the trained hybrid atlas forest. The segment performance and the components efficiency of the proposed method are evaluated on the two public datasets. Based on the experiment results and quantitative comparisons, our method can gather spatial information and correlation among the atlases to obtain an accurate segmentation.     

Application of a Technofunctional Caseinate Hydrolysate to Replace Surfactants in Ice Cream

There is a demand for a clean label of ice cream in the food industry. To meet this requirement, alternative surfactants and hydrocolloids without an additive number have to be found. Here, a caseinate hydrolysate with improved interfacial properties was investigated as such an additive. Replacing only the surfactant resulted in ice cream characteristics, comparable to using a commercial emulsifier (INS 472b). Thus, a clean labeling of the surfactant using this hydrolysate is possible. By contrast, replacing the hydrocolloid additionally led to an unfavorable ice cream texture and stability.     

An enhanced data-driven polynomial chaos method for uncertainty propagation

As a novel type of polynomial chaos expansion (PCE), the data-driven PCE (DD-PCE) approach has been developed to have a wide range of potential applications for uncertainty propagation. While the research on DD-PCE is still ongoing, its merits compared with the existing PCE approaches have yet to be understood and explored, and its limitations also need to be addressed. In this article, the Galerkin projection technique in conjunction with the moment-matching equations is employed in DD-PCE for higher-dimensional uncertainty propagation. The enhanced DD-PCE method is then compared with current PCE methods to fully investigate its relative merits through four numerical examples considering different cases of information for random inputs. It is found that the proposed method could improve the accuracy, or in some cases leads to comparable results, demonstrating its effectiveness and advantages. Its application in dealing with a Mars entry trajectory optimization problem further verifies its effectiveness.     

Effects of different nutrition labels on visual attention and accuracy of nutritional quality perception – Results of an experimental eye-tracking study

Front-of-Pack (FoP) nutrition labels are emerging as a prominent public policy tool for promoting healthy eating. In this study, we question how different FoP nutrition labels ranging from more directive (Nutriscore, NS), to semi-directive (monochromatic Guided Daily Amount, GDA) and non-directive (multiple-traffic lights, MTL), affect perceived visual attention and nutritional quality perception. The visual attention was measured by eye-tracing measures, and nutritional quality by healthiness perception and recommended frequency of consumption. Seventy-six participants (N = 76) were randomly assigned in one of three experimental conditions, where they were asked to give estimates on eight different chocolate snack bars. To test whether participants estimates were accurate, we surveyed fifty-six (N = 56) nutritionists and asked for their assessments of the same group of products. The results showed that Nutriscore required least visual attention in terms of dwell-time, number of fixations, and average fixation duration, followed by MTL and GDA. Participants in NS and MTL condition gave significantly higher estimates of nutritional quality compared to experts' estimates. Most accurate estimates came from products with GDA label. Color-coded fields (MTL) required less visual attention, compared to GDA, without adding to visual efficiency. More directive FoP nutrition labels require less visual attention but lead to inflated estimates of products' nutrition quality in the category of less healthy products. In creating public policies, removing the possibility for consumers to process nutritional information and absolute estimates of products' nutrition quality should not be disregarded.     

Thermodynamic description of the Cu-Ge-Pb system: Experiment and modeling

Decades of scientific work dedicated to the investigation of phase diagrams gave significant benefit to industry and science. After all those years of phase diagram investigation still there is missing information about phase diagram of some ternary systems. One of those systems is Cu-Ge-Pb. It is known importance of Cu-based alloys and Ge-based alloys in electro industry. Since such combination is not tested before this work will provide information about phase diagram of ternary Cu-Ge-Pb system. In this work ternary Cu-Ge-Pb system has been tested experimentally and analytically by using Calphad model. Two isothermal sections at 600 and 400 °C and three vertical sections are experimentally tested and results were compared with calculated corresponding phase diagrams. None of the ternary compound and large solubility of third element in binary compound is not confirmed. Liquidus projection, invariant reaction and scheme of invariant reaction are presented. Scheil and Lever simulation of solid phases for Cu₈₀Ge₁₀Pb₁₀ alloy were calculated.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.