Selected physical characteristics of polystyrene/high density polyethylene composites prepared from virgin and recycled materials

Mixtures of polystyrene and high density polyethylene were injection molded from recycled and virgin polymers to generate cocontinuous structures. The mechanical properties of these blends were evaluated to assess their conformance to rule of mixtures behavior in general and to identify areas of synergy or incompatibility in specific. Flexural and tensile data for recycled blends showed that generally the properties are not additive, except in a cocontinuous region of composition near 35/65 PS/HDPE that has been identified previously for recycled materials. Analysis of crystallinity in the HDPE phase of these blends by differential scanning calorimetry indicates a marked reduction in the level of HDPE crystallinity at the 35/65 PS/HDPE composition. Similar blends of virgin PS/HDPE polymer do not show the differing regions of incompatibility and synergy illustrated by the recycled materials, but rather show approximate conformance to the rule of mixtures. Furthermore, the virgin blends show virtually no crystallinity suppression and a more pronounced T_g shift in the polystyrene compared to recycled materials. Detailed characterization of the recycled materials in terms of polymer and particulate impurities should improve understanding of these differences and perhaps provide direction for obtaining enhanced synergistic behavior in virgin polymer blends. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

EGIS'92

Announcement

EGIS'92 Third European Conference on Geographical Information Systems at the Park Hilton in Munich Germany, March 23–26, 1992     

A Biologically-Inspired Micro Aerial Vehicle

This paper introduces a novel framework for the design, modeling and control of a Micro Aerial Vehicle (MAV). The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). We have taken inspiration from the flight mechanism features of the dragonfly and have developed indigenous designs in creating a novel version of a Flapping Wing MAV (FWMAV). The MAV design incorporates a complex mechanical construction and a sophisticated multi-layered, hybrid, linear/non-linear controller to achieve extended flight times and improved agility compared to other rotary wing and FWMAV Vertical Take Off and Landing (VTOL) designs. The first MAV prototype will have a ballpark weight including sensor payload of around 30 g. The targeted lifting capability is about twice the weight. The MAV features state of the art sensing and instrumentation payload, which includes integrated high-power on-board processors, 6DoF inertial sensors, 3DoF compasses, GPS, embedded camera and long-range telemetry capability. A 3-layer control mechanism has been developed to harness the dynamics and attain complete navigational control of the MAV. The inner-layer is composed of a ‘quad hybrid-energy controller’ and two higher layers are at present, implementing a linear controller; the latter will be replaced eventually with a dynamic adaptive non-linear controller. The advantages of the proposed design compared to other similar ones include higher energy efficiency and extended flight endurance. The design features elastic storage and re-use of propulsion energy favoring energy conservation during flight. The design/modeling of the MAV and its kinematics & dynamics have been tested under simulation to achieve desired performance. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance and reconnaissance in cluster and swarm formations. The efficacy of the design is demonstrated through a simulation environment. The dynamics are verified through simulations and a general linear controller coupled with an energy based non-linear controller is shown to operate the vehicle in a stable regime. In accordance with specified objectives a prototype is being developed for flight-testing and demonstration purposes.     

Common-input models for multiple neural spike-train data

Recent developments in multi-electrode recordings enable the simultaneous measurement of the spiking activity of many neurons. Analysis of such multineuronal data is one of the key challenge in computational neuroscience today. In this work, we develop a multivariate point-process model in which the observed activity of a network of neurons depends on three terms: (1) the experimentally-controlled stimulus; (2) the spiking history of the observed neurons; and (3) a hidden term that corresponds, for example, to common input from an unobserved population of neurons that is presynaptic to two or more cells in the observed population. We consider two models for the network firing-rates, one of which is computationally and analytically tractable but can lead to unrealistically high firing-rates, while the other with reasonable firing-rates imposes a greater computational burden. We develop an expectation-maximization algorithm for fitting the parameters of both the models. For the analytically tractable model the expectation step is based on a continuous-time implementation of the extended Kalman smoother, and the maximization step involves two concave maximization problems which may be solved in parallel. The other model that we consider necessitates the use of Monte Carlo methods for the expectation as well as maximization step. We discuss the trade-off involved in choosing between the two models and the associated methods. The techniques developed allow us to solve a variety of inference problems in a straightforward, computationally efficient fashion; for example, we may use the model to predict network activity given an arbitrary stimulus, infer a neuron's ring rate given the stimulus and the activity of the other observed neurons, and perform optimal stimulus decoding and prediction. We present several detailed simulation studies which explore the strengths and limitations of our approach.     

Multi-stage deep probabilistic prediction for travel demand

Applied Intelligence - Accurate demand prediction is an essential component of any decision support system for smart vehicle dispatching. However, predicting real time demand at the...     

Climate change country studies

Over the past three years, country studies have improved country-specific, and hence global, estimates of: (i) greenhouse gas (GHG) emissions and sequestration, and (ii) costs and benefits of mitigation options, and (iii) the vulnerability of natural habitats and human systems. The technical and financial support provided by the US and other country-study programs has enhanced the contribution of experts from developing and transition countries to their global scientific assessment. This paper presents a brief overview of work conducted in the context of the US Country Studies Program in the development of national GHG inventories, assessment of GHG mitigation options, and assessment of vulnerability to climate change and options for adaptation.     

Dynamic and transparent binary translation

High-frequency design and instruction-level parallelism (ILP) are important for high-performance microprocessor implementations. The Binary-translation Optimized Architecture (BOA), an implementation of the IBM PowerPC family, combines binary translation with dynamic optimization. The authors use these techniques to simplify the hardware by bridging a semantic gap between the PowerPC's reduced instruction set and even simpler hardware primitives. Processors like the Pentium Pro and Power4 have tried to achieve high frequency and ILP by implementing a cracking scheme in hardware: an instruction decoder in the pipeline generates multiple micro-operations that can then be scheduled out of order. BOA relies on an alternative software approach to decompose complex operations and to generate schedules, and thus offers significant advantages over purely static compilation approaches. This article explains BOA's translation strategy, detailing system issues and architecture implementation     

High quality networking of audio-visual information

An overview of low bit rate coding and the interaction between source coding and channel coding is presented. The interaction of coding with networking in a multiuser environment, including algorithms for robust coding which anticipate imperfect network performance, and techniques of decoding a signal that has traversed an imperfect network are described. The performances of such algorithms are illustrated with examples from speech, audio, and video transmission in the presence of packet losses. The challenges in measuring the quality of service (QOS) in the context of new algorithms for coding and networking and the difficulty of measuring QOS in the networking of multimedia information are discussed     

Adaptive postprocessing algorithms for low bit rate video signals

A new adaptive postprocessing algorithm to enhance the quality of a noisy video sequence is presented. The algorithm recognizes that the visibility of noise depends on local signal characteristics. It therefore classifies the video signal into different classes and uses separate nonlinear filters matched to each class. The most general version of the algorithm employs motion-compensated frame averaging to improve picture quality in a first stage. A classification algorithm subsequently divides subblocks of pixels in the averaged frame into four classes: edge, smooth, nonsmooth with motion and nonsmooth without motion. Spatial algorithms that perform multilevel median filtering, double median filtering, and median filtering are used for pixels belonging to edge, smooth, and nonsmooth with motion categories. Pixels in the nonsmooth, unmoving category are left unfiltered to preserve corresponding image texture. In a simpler version of this four-class system, the motion cues and motion-compensated frame averaging are eliminated, and the purely spatial filtering is based on a three-class algorithm. When used at the output of a 3-D subband coder at 384 kbps, the spatial postfilter was shown to provide a consistent gain in subjectively evaluated picture quality. Twenty-five viewers participated in an experiment involving three coded sequences. In a pairwise comparison of postfiltered and unfiltered sequences, the postfiltered version was judged to be better in 63 out of 75 instances.