A novel polarizer‐free dye‐doped polymer‐dispersed liquid crystal for reflective TFT displays

Abstract— A novel preparation method for dichroic dye‐doped polymer‐dispersed liquid crystals has been developed. This was achieved by creating a porous polymer matrix first by washing out the liquid crystal from a polymer‐dispersed liquid crystal (PDLC), which is then refilled with dye‐doped liquid crystal. Optimizing the liquid crystal used in the refilling results in decreased turn‐on voltage and faster response time. Poster‐standard reflectivity and newspaper‐standard contrast was demonstrated with a 3.8‐in. QVGA reflective TFT display with a drive voltage of 10 V.     

Scale Selection Properties of Generalized Scale-Space Interest Point Detectors

Scale-invariant interest points have found several highly successful applications in computer vision, in particular for image-based matching and recognition. This paper presents a theoretical analysis of the scale selection properties of a generalized framework for detecting interest points from scale-space features presented in Lindeberg (Int. J. Comput. Vis. 2010, under revision) and comprising:

an enriched set of differential interest operators at a fixed scale including the Laplacian operator, the determinant of the Hessian, the new Hessian feature strength measures I and II and the rescaled level curve curvature operator, as well as

an enriched set of scale selection mechanisms including scale selection based on local extrema over scale, complementary post-smoothing after the computation of non-linear differential invariants and scale selection based on weighted averaging of scale values along feature trajectories over scale.

It is shown how the selected scales of different linear and non-linear interest point detectors can be analyzed for Gaussian blob models. Specifically it is shown that for a rotationally symmetric Gaussian blob model, the scale estimates obtained by weighted scale selection will be similar to the scale estimates obtained from local extrema over scale of scale normalized derivatives for each one of the pure second-order operators. In this respect, no scale compensation is needed between the two types of scale selection approaches. When using post-smoothing, the scale estimates may, however, be different between different types of interest point operators, and it is shown how relative calibration factors can be derived to enable comparable scale estimates for each purely second-order operator and for different amounts of self-similar post-smoothing. A theoretical analysis of the sensitivity to affine image deformations is presented, and it is shown that the scale estimates obtained from the determinant of the Hessian operator are affine covariant for an anisotropic Gaussian blob model. Among the other purely second-order operators, the Hessian feature strength measure I has the lowest sensitivity to non-uniform scaling transformations, followed by the Laplacian operator and the Hessian feature strength measure II. The predictions from this theoretical analysis agree with experimental results of the repeatability properties of the different interest point detectors under affine and perspective transformations of real image data. A number of less complete results are derived for the level curve curvature operator.     

Less cyber,more café: Enhancing existing small businesses across the digital divide with ICTs

About 10% of the world has access to information and communication technologies (ICTs). Telecenters and cyber cafés are one prevalent way to increase access. This paper suggests increasing access through currently existing, local businesses where people already gather and where proprietors already posses existing business relationships with suppliers and customers. This paper questions the prevailing emphasis on the “cyber'' characteristics of access, e.g., computing and internet access as is currently known, and attempts to refocus the conversation by considering computing and access in the context of the “café,” e.g., as public life in the sense of Habermas, which permits an in situ evolution of relevant access. This analysis is based on extant literature and direct ethnographic research in several public places in six countries. We offer example design perspectives based on a reflection of “third places” as inspiration for appropriate innovation in the provision of computing and communications. © 2005 Wiley Periodicals, Inc.     

Design of acoustic beam aperture modifier using gradient-index phononic crystals

This article reports the design concept of a novel acoustic beam aperture modifier using butt-jointed gradient-index phononic crystals (GRIN PCs) consisting of steel cylinders embedded in a homogeneous epoxy background. By gradually tuning the period of a GRIN PC, the propagating direction of acoustic waves can be continuously bent to follow a sinusoidal trajectory in the structure. The aperture of an acoustic beam can therefore be shrunk or expanded through change of the gradient refractive index profiles of the butt-jointed GRIN PCs. Our computational results elucidate the effectiveness of the proposed acoustic beam aperture modifier. Such an acoustic device can be fabricated through a simple process and will be valuable in applications, such as biomedical imaging and surgery, nondestructive evaluation, communication, and acoustic absorbers.     

Adhesion,plasticity and other peculiar properties of solid methane

Adhesion and plasticity of polycrystalline solid methane have been studied in the temperature range 10–90 K. It was shown that adhesion is very strong in the 50–90 K temperature range where the solid methane is soft and sticky. Closer to the melting point (at 90.6 K) the solid methane behaves as extremely viscous non-Newtonian liquid. Below 30 K solid methane loses its stickiness and ductility and acts like ordinary glass. Methane adhesion remains similar for very different materials. We have also made some video observations which reveal unexpected and mostly inexplicable properties of solid methane which could be of some interest for designing new methane moderators for neutron sources and planetary physics particularly the study of the environment of Titan.     

Effect of wobbling mass modeling on joint dynamics during human movements with impacts

In automated mechanical transmissions, engaging sleeve with clutch gear causes the switches of mechanical coupling modes of engaging-related parts, and impacts may happen to make the part speeds have discrete transitions during the engaging. The two characters make the engaging process exhibit both continuity and discreteness. The aim of the paper is to develop a high-fidelity model to capture the trajectories of the parts in the transmission. We treat the engaging as a two-phase process—sleeve first interacting with synchro ring and then with clutch gear. The part movements under a certain constraint are governed by multibody dynamics, and the speed jumps caused by impacts are described using the Poisson coefficient of restitution. To couple the continuous evolutions and discrete transitions of the states, a hybrid automaton model is developed. This model allows for the characteristic analysis of the engaging process with multiple interaction cases between the engaging-related parts, and it is validated by bench tests. The effects of two key factors—the relative tooth position of sleeve and clutch gear and the shifting force—on engaging duration and impact are studied through numerical simulations.     

Hardware architecture of the Protein Processing Associative Memory and the effects of dimensionality and quantisation on performance

The Protein Processor Associative Memory (PPAM) is a novel hardware architecture for a distributed, decentralised, robust and scalable, bidirectional, hetero-associative memory, that can adapt online to changes in the training data. The PPAM uses the location of data in memory to identify relationships and is therefore fundamentally different from traditional processing methods that tend to use arithmetic operations to perform computation. This paper presents the hardware architecture and details a sample digital logic implementation with an analysis of the implications of using existing techniques for such hardware architectures. It also presents the results of implementing the PPAM for a robotic application that involves learning the forward and inverse kinematics. The results show that, contrary to most other techniques, the PPAM benefits from higher dimensionality of data, and that quantisation intervals are crucial to the performance of the PPAM.