十二烷基－二甲基（2－羟基）乙基氯化铵系列季铵盐的缓蚀性能

通过失重法和极化曲线、线性极化两种电化学方法，研究了十二烷基二甲基（２－羟基）乙基氯化铵（１２２）、十四烷基二甲基（２－羟基）乙基氯化铵（１４２）和十六烷基二甲基（２－羟基）乙基氯化铵（１６２）对２０＃碳钢在５％盐酸中的缓蚀作用。并与新洁尔灭（十二烷基二甲基苄基溴化铵）进行了比较。结果表明，它们在酸性介质中具有很好的缓蚀作用。     

孔雀绿分光光度法测定炭素制品中微量铅的研究

采用分光光度法来测定炭素制品中微量铅的含量。经比较实验确定了该方法最佳的实验奈件。该方法操作简便、快速、检出限低、灵敏度高，是检测微量铅含量一种较理想的方法。     

A visual study on flame behavior in tone-excited non-premixed jet flames

A visualization study on the effect of forcing amplitude in tone-excited jet diffusion flames has been conducted. Visualization techniques are employed using optical schemes, which are a light scattering photography. Flame stability curve is attained according to Reynolds number and forcing amplitude at a fuel tube resonant frequency. Flame behavior is globally grouped into two from attached flame to blown-out flame according to forcing amplitude; one sticks the tradition flame behavior which has been observed in general jet diffusion flames and the other shows a variety of flame modes such as the flame of a feeble forcing amplitude where traditionally well-organized vortex motion evolves, a fat flame, an elongated flame, and an in-burning flame. Particular attention is focused on an elongation flame, which is associated with a turnabout phenomenon of vortex motion, and on a reversal of the direction of vortex roll-up. It is found that the flame length with forcing amplitude is the direct outcome of the evolution process of the formed inner flow structure. Especially the negative part of the acoustic cycle under the influence of a strong positive pressure gradient causes the shapes of the fuel stem and fuel branch part and even the direction of vortex roll-up to dramatically change.     

双活性基活性染料真丝绸染色工艺研究

双活性基活性染料用于真丝绸染色有诸多影响因素：缚酸剂用碳酸氢钠比碳酸钠的固色率高用量在2％～4％，pH为8～9时最为合适：染色温度从60℃升到85℃时固色率提高3％～8％，超过85℃时易造成“灰伤”．当元明粉的用量从30g／l升到60g／l时上染率和固色率提高10％。随着浴比的增加，其固色率会有不同程度的降低，在实验条件下，浴比为1：40最好。通过上染曲线，讨论了染色过程的控制。     

工业PTA氧化过程4-CBA浓度的模糊神经网络模型

A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.     

Visual Analysis of Trajectories in Multi‐Dimensional State Spaces

Multi‐dimensional data originate from many different sources and are relevant for many applications. One specific sub‐type of such data is continuous trajectory data in multi‐dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous‐time scatterplots and continuous‐time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration. We demonstrate the usefulness of our visualization approach for three case studies that cover examples of complex dynamic systems: cyber‐physical systems consisting of heterogeneous sensors and actuators networks (the collection of time‐dependent sensor network data of an exemplary smart home environment), the dynamics of robot arm movement and motion characteristics of humanoids.     

Adaptive multi‐scale analysis for point‐based surface editing

This paper presents a tool that enables the direct editing of surface features in large point‐clouds or meshes. This is made possible by a novel multi‐scale analysis of unstructured point‐clouds that automatically extracts the number of relevant features together with their respective scale all over the surface. Then, combining this ingredient with an adequate multi‐scale decomposition allows us to directly enhance or reduce each feature in an independent manner. Our feature extraction is based on the analysis of the scale‐variations of locally fitted surface primitives combined with unsupervised learning techniques. Our tool may be applied either globally or locally, and millions of points are handled in real‐time. The resulting system enables users to accurately edit complex geometries with minimal interaction.     

Hierarchical opacity optimization for sets of 3D line fields

The selection of meaningful lines for 3D line data visualization has been intensively researched in recent years. Most approaches focus on single line fields where one line passes through each domain point. This paper presents a selection approach for sets of line fields which is based on a global optimization of the opacity of candidate lines. For this, existing approaches for single line fields are modified such that significantly larger amounts of line representatives are handled. Furthermore, time coherence is addressed for animations, making this the first approach that solves the line selection problem for 3D time‐dependent flow. We apply our technique to visualize dense sets of pathlines, sets of magnetic field lines, and animated sets of pathlines, streaklines and masslines.     

Spline multiresolution and wavelet-like decompositions

Splines are useful tools to represent, modify and analyze curves and they play an important role in various practical applications. We present a multiresolution approach to spline curves with arbitrary knots that provides good feature detection and localization properties for non-equally distributed geometric data. In addition, we show how equidistributed data and knot sequences can be efficiently handled using signal processing techniques.