Equi-affine Invariant Geometry for Shape Analysis

Traditional models of bendable surfaces are based on the exact or approximate invariance to deformations that do not tear or stretch the shape, leaving intact an intrinsic geometry associated with it. These geometries are typically defined using either the shortest path length (geodesic distance), or properties of heat diffusion (diffusion distance) on the surface. Both measures are implicitly derived from the metric induced by the ambient Euclidean space. In this paper, we depart from this restrictive assumption by observing that a different choice of the metric results in a richer set of geometric invariants. We apply equi-affine geometry for analyzing arbitrary shapes with positive Gaussian curvature. The potential of the proposed framework is explored in a range of applications such as shape matching and retrieval, symmetry detection, and computation of Voroni tessellation. We show that in some shape analysis tasks, equi-affine-invariant intrinsic geometries often outperform their Euclidean-based counterparts. We further explore the potential of this metric in facial anthropometry of newborns. We show that intrinsic properties of this homogeneous group are better captured using the equi-affine metric.     

Combinatorial chemistry methods for coating development: VI. Correlation of high throughput screening methods with conventional measurement techniques

Combinatorial chemistry has proven to be a valuable tool for the development of new compounds. In the pharmaceutical industry, where combinatorial chemistry began, the approach has been instrumental in the high-speed development of new drugs. Due to the overwhelming success of the combinatorial methodology in the pharmaceutical industry, it has been recently applied to materials development. We have recently developed a combinatorial factory capable of preparing and evaluating on the order of 100 organic clear coatings in a day.

One of the most challenging aspects of the creation of the combinatorial factory was the development of the high throughput screening (HTS) methods for the primary coating properties of interest such as optical clarity, abrasion resistance, adhesion, and weatherability. For each property, an entirely new method was developed that allowed for rapid measurement of these properties on very small samples. This paper describes various aspects of the development of these novel measurement systems including the correlation of the HTS methods with conventional, industry standard measurement methods.     

Active fault tolerant control for nonlinear systems with simultaneous actuator and sensor faults

The goal of this paper is to describe a novel fault tolerant tracking control (FTTC) strategy based on robust fault estimation and compensation of simultaneous actuator and sensor faults. Within the framework of fault tolerant control (FTC) the challenge is to develop an FTTC design strategy for nonlinear systems to tolerate simultaneous actuator and sensor faults that have bounded first time derivatives. The main contribution of this paper is the proposal of a new architecture based on a combination of actuator and sensor Takagi-Sugeno (T-S) proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators together with a T-S dynamic output feedback control (TSDOFC) capable of time-varying reference tracking. Within this architecture the design freedom for each of the T-S estimators and the control system are available separately with an important consequence on robust L ₂ norm fault estimation and robust L ₂ norm closed-loop tracking performance. The FTTC strategy is illustrated using a nonlinear inverted pendulum example with time-varying tracking of a moving linear position reference.     

Analysis of Two-Dimensional Non-Rigid Shapes

Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes: similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally, we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem. As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the three problems addressed in this paper.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

Single Nanoparticle Magnetic Spin Memristor

There is an increasing demand for the development of a simple Si‐based universal memory device at the nanoscale that operates at high frequencies. Spin‐electronics (spintronics) can, in principle, increase the efficiency of devices and allow them to operate at high frequencies. A primary challenge for reducing the dimensions of spintronic devices is the requirement for high spin currents. To overcome this problem, a new approach is presented that uses helical chiral molecules exhibiting spin‐selective electron transport, which is called the chiral‐induced spin selectivity (CISS) effect. Using the CISS effect, the active memory device is miniaturized for the first time from the micrometer scale to 30 nm in size, and this device presents memristor‐like nonlinear logic operation at low voltages under ambient conditions and room temperature. A single nanoparticle, along with Au contacts and chiral molecules, is sufficient to function as a memory device. A single ferromagnetic nanoplatelet is used as a fixed hard magnet combined with Au contacts in which the gold contacts act as soft magnets due to the adsorbed chiral molecules.     

Common Knowledge and Update in Finite Environments

Logics of knowledge have been shown to provide a useful approach to the high level specification and analysis of distributed systems. It has been proposed that such systems can be developed using knowledge- based protocols, in which agents' actions have preconditions that test their state of knowledge. Both computer-assisted analysis of the knowledge properties of systems and automated compilation of knowledge-based protocols require the development of algorithms for the computation of states of knowledge. This paper studies one of the computational problems of interest, the model checking problem for knowledge formulae in the S5_nKripke structures generated by finite state environments in which states determine an observation for each agent. Agents are assumed to have perfect recall and may operate synchronously or asynchronously. It is shown that, in this setting, model checking of common knowledge formulae is intractable, but efficient incremental algorithms are developed for formulae containing only knowledge operators. Connections to knowledge updates and compilation of knowledge-based protocols are discussed.     

The first measurement of an absolute surface concentration of reaction intermediates in ethylene hydrogenation

The first measurement of a turnover rate with respect to surface intermediate concentration in a high pressure heterogeneous catalytic reaction is reported. By using infrared-visible sum frequency generation to study the hydrogenation of ethylene on Pt(111), it was found that the surface concentration of -bonded ethylene, the key reaction intermediate, represented approximately 4% of a monolayer. Thus the absolute turnover rate per surface adsorbed ethylene molecule is 25 times faster than the rate measured per platinum atom. To explain these results, we propose a model of weakly adsorbed ethylene intermediates reacting on atop sites.