IGC study of surface properties of adsorbed styrene/methacrylic acid diblock polymers

An inverse gas chromatographic study has been carried out on a styrene/methacrylic acid diblock polymer adsorbed on particulates of varying acid/base interaction potential. Acid/base interactions between polymer and substrate were shown to result in the selective adsorption of copolymer moieties, leading to interphase surface compositions that varied with thickness. At higher interphase thicknesses, bulk and surface compositions became similar; however, depending on the interaction potential of the adsorbent, the interphase thicknesses at this point varied from 100 to 1000 Å. Adsorbed diblock interphases are to be considered nonisotropic in local composition and molecular conformation. These properties may make possible designing diblock interphases to meet specific compatibilization requirements in polymer composites. © 1994 John Wiley & Sons, Inc.     

Repeatability of redundant manipulators: mathematical solution ofthe problem

Consider a redundant manipulator whose hand is to trace a path in its workspace. A local control strategy that governs the manipulator is a law that assigns an infinitesimal change in the joint angles so that the hand will move infinitesimally in the direction designated by the path. Because of the redundancy, there can be many such control strategies. For some strategies it turns out that when the hand returns to its initial position, the joint angles do not always return to their initial values. To determine a priori whether a given local control strategy guarantees repeatability or not, it is necessary to deduce its global properties as well as its local properties. This is achieved by considering integral surfaces for a distribution in the joint space. This yields a necessary and sufficient condition, in terms of Lie brackets, for a control to be repeatable     

移动式小型X线机综合防护装置

本文介绍一种移动式小型 X 线机综合防护装置。该装置把便于运输的部件、防护隔屏及暗室融为一体,为 X 线工作者、被检者和被检者提供了较好的防护。本文介绍一种移动式小型 X 线机综合防护装置。现将其基本构造和防护效果简介如下:     

Quality enhancements of digital outline fonts

Digital fonts are easily available today and their use has become widespread. Nevertheless, the visual quality of printed and displayed text and the technical quality of digital typefaces are often unsatisfactory. The foremost reason for this situation is that font manufacturing systems manipulate font representations through low-level operations. In this paper we examine several aspects of font quality, and present a method for enhancing the quality of a typeface given in today's standard representation, the outline (boundary) representation. The method is based on the usage of high-level typographic features, and includes enhancements to both individual glyphs and complete fonts. Glyph enhancements include elimination of redundant points, insertion of essential points, corrections to contour orientations and inter-penetrations, and vertical and horizontal coherence. Font enhancements include regularization of font weights and sizes, serif unification, and feature extraction and discrimination. Our method is comprised of several algorithms that have been implemented in a commercial font manufacturing system, achieving enhanced quality of the fonts produced.     

The effects of mediation in computer assisted dynamic assessment

Abstract This study examined the effects of the computer-assisted dynamic assessment (DA) on cognitive performance as compared to DA with an examiner. The DA approach is based on Feuerstein's mediated learning experience theory and Tzuriel's DA approach with young children. A sample of kindergarden children ( n  = 60) were assigned to either a Computer Assisted (CA, n  = 30) or Examiner Only (EO, n  = 30) groups. The sample was randomly chosen from three kindergardens in a middle-SES area. Initial intelligence level of both groups was controlled by matching their frequency distribution on the Raven's Colored Progressive Matrices score. The CA group was administered the Think-in-Order program, which is a multimedia program designed specifically for this study and is based on the Children's Seriational Thinking Modifiability (CSTM) test. The EO group was administered the CSTM test by an examiner. The findings revealed that intervention involving mediation processes in a CA dynamic assessment procedure was more effective in bringing about significant cognitive changes than mediation with only an examiner.     

Application of serial- and parallel-projection methods to correlation-filter design

We describe generalized projection procedures for the design of arbitrary filter functions for correlators. More specifically, serial and parallel implementations of projection-based algorithms are employed. The novelty of this procedure lies in its generality and its ability to handle wide varieties of constraints by the same procedure. The procedure is demonstrated by the design of filters for the 4-? linear correlator, the phase-extraction correlator, and variants thereof. The filters are subject to a variety of constraints, including rotation-invariant pattern recognition and class discrimination. Examples are given to show the versatility, flexibility, and applicability of the design process to a variety of pattern-recognition tasks. Satisfactory results are also obtained because of the combination with the special nonlinear correlators proposed for pattern recognition.     

Learning Explicit Smoothing Kernels for Joint Image Filtering

Smoothing noises while preserving strong edges in images is an important problem in image processing. Image smoothing filters can be either explicit (based on local weighted average) or implicit (based on global optimization). Implicit methods are usually time‐consuming and cannot be applied to joint image filtering tasks, i.e., leveraging the structural information of a guidance image to filter a target image. Previous deep learning based image smoothing filters are all implicit and unavailable for joint filtering. In this paper, we propose to learn explicit guidance feature maps as well as offset maps from the guidance image and smoothing parameter that can be utilized to smooth the input itself or to filter images in other target domains. We design a deep convolutional neural network consisting of a fully‐convolution block for guidance and offset maps extraction together with a stacked spatially varying deformable convolution block for joint image filtering. Our models can approximate several representative image smoothing filters with high accuracy comparable to state‐of‐the‐art methods, and serve as general tools for other joint image filtering tasks, such as color interpolation, depth map upsampling, saliency map upsampling, flash/non‐flash image denoising and RGB/NIR image denoising.     

Self‐similarity Analysis for Motion Capture Cleaning

Motion capture sequences may contain erroneous data, especially when the motion is complex or performers are interacting closely and occlusions are frequent. Common practice is to have specialists visually detect the abnormalities and fix them manually. In this paper, we present a method to automatically analyze and fix motion capture sequences by using self‐similarity analysis. The premise of this work is that human motion data has a high‐degree of self‐similarity. Therefore, given enough motion data, erroneous motions are distinct when compared to other motions. We utilize motion‐words that consist of short sequences of transformations of groups of joints around a given motion frame. We search for the K‐nearest neighbors (KNN) set of each word using dynamic time warping and use it to detect and fix erroneous motions automatically. We demonstrate the effectiveness of our method in various examples, and evaluate by comparing to alternative methods and to manual cleaning.