TETHERED POLYMERS: KINETICS AND CONTROL

This dissertation describes a study of the kinetics of formation of tethered polymer layers. Polymer chains diffuse from dilute solution to the surface a solid, to which they become attached by one end. Kinetics profiles composed of three distinct regimes are displayed by all tethering reactions studied in the absence of segmental adsorption, regardless of solvent quality, temperature, chemistry of polymer, architecture of polymer, and type of reactive site on the surface. The first regime, fast and predicted previously by theory, is controlled by diffusion of the polymer chains through solution to the bare surface. The second regime, slow and also predicted by theory, is controlled by diffusion of the polymer chains through the already tethered layer. The third regime, relatively fast and not predicted by theory, appears to be the consequence of cooperative interaction between incoming chains and tethered chains. During the tethering process, each tethered polymer chain changes from a random-coil-like configuration to a vertically stretched configuration. The end of the first regime corresponds to completion of a layer of nonoverlapping, coil-like tethered chains, called a mushroom layer. Cessation of tethering corresponds to a layer of vertically stretched chains, called a polymer brush. Transition from mushroom to brush mainly takes place in the third regime and develops in spatially nonuniform manner. The understanding gained about the kinetics of tethering was used to construct simply tethered layers, bi-component tethered layers, bidisperse (two molecular weights) tethered layers, and tethered layers of mixed architecture (linear and star-branched)

2014-2015 Senior Recital - Heqing Huang (Piano)

El curso de PROSPECTIVA ESTRATEGICA brinda las herramientas para poder predecir y comprender el comportamiento futuro de las variables que afectan los procesos organizacionales.La prospectiva trata de ir adaptándose paulatinamente al cambio de los escenarios e ir creando ventajas competitivas con ciclos de vida predeterminado

Learning to Associate Words and Images Using a Large-scale Graph

We develop an approach for unsupervised learning of associations between co-occurring perceptual events using a large graph. We applied this approach to successfully solve the image captcha of China's railroad system. The approach is based on the principle of suspicious coincidence. In this particular problem, a user is presented with a deformed picture of a Chinese phrase and eight low-resolution images. They must quickly select the relevant images in order to purchase their train tickets. This problem presents several challenges: (1) the teaching labels for both the Chinese phrases and the images were not available for supervised learning, (2) no pre-trained deep convolutional neural networks are available for recognizing these Chinese phrases or the presented images, and (3) each captcha must be solved within a few seconds. We collected 2.6 million captchas, with 2.6 million deformed Chinese phrases and over 21 million images. From these data, we constructed an association graph, composed of over 6 million vertices, and linked these vertices based on co-occurrence information and feature similarity between pairs of images. We then trained a deep convolutional neural network to learn a projection of the Chinese phrases onto a 230-dimensional latent space. Using label propagation, we computed the likelihood of each of the eight images conditioned on the latent space projection of the deformed phrase for each captcha. The resulting system solved captchas with 77% accuracy in 2 seconds on average. Our work, in answering this practical challenge, illustrates the power of this class of unsupervised association learning techniques, which may be related to the brain's general strategy for associating language stimuli with visual objects on the principle of suspicious coincidence.Comment: 8 pages, 7 figures, 14th Conference on Computer and Robot Vision 201

Modelling Chinese Smart Grid: A Stochastic Model Checking Case Study

Cyber-physical systems integrate information and communication technology functions to the physical elements of a system for monitoring and controlling purposes. The conversion of traditional power grid into a smart grid, a fundamental example of a cyber-physical system, raises a number of issues that require novel methods and applications. In this context, an important issue is the verification of certain quantitative properties of the system. In this technical report, we consider a specific Chinese Smart Grid implementation and try to address the verification problem for certain quantitative properties including performance and battery consumption. We employ stochastic model checking approach and present our modelling and analysis study using PRISM model checker