Modelling formation and growth of H2SO4-H2O aerosols: Uncertainty analysis and experimental evaluation

An aerosol dynamics model, AERO2, is presented, which describes the formation of H₂SO₄-H₂O aerosol in a smog chamber. The model is used to analyse how the uncertainties on four input parameters are propagated through an aerosol dynamics model. The input parameters are: the rate of the reaction between SO₂ and OH (k₁), the ratio between the nucleation rate used in AERO2 and that derived from classical nucleation theory (t_n), the H₂SO₄ mass accommodation coefficient () and a measure of the turbulence intensity in the reactor (k_e). Uncertainties for these parameters are taken from the literature. One of the results of the analysis is that AERO2 and aerosol dynamics models in general can only predict upper bounds for the total number (N_tot) and total volume (V_tot) concentrations of the particles. The uncertainties on N_tot and V_tot are mainly due to the uncertainties on k₁, and t_n. An uncertainty factor of 20–100 still remains when the uncertainty on k₁, is reduced to ±5%. Aerosol measurements from three smog chamber experiments have therefore been used, in an attempt to reduce the uncertainty on k₁ and t_n. Values for k₁ are obtained in the reduced range 7.8 × 10⁻¹³ to 1.0 × 10⁻¹² cm³ s⁻¹, which is within the range found in the literature. For t_n, values in the range 10⁴–10⁷ are obtained, which is close to the upper bound of the range in literature. These values for t_n are in marked contrast with a recent set of experiments on nucleation in H₂SO₄-H₂O mixtures, which suggests a value for t_n of at most 10⁻⁵.     

Engineering and molding properties of poly(vinyl chloride), acrylonitrile-butadiene-styrene and polyester blends

Polymer blends with varying amounts of poly(vinyl chloride) (PVC), acrylonitrile-butadiene-styrene (ABS) and polyester have been developed to produce parts with highly flexible, good impact strength, and flame retardant hinge properties. In the present work, the rheological and dynamic mechanical properties are balanced by changing the blend formulations. It is shown that blends morphology and rheology have greater impact on the dimensional stability and delamination at the surface of the molded hinge parts.     

A low-power,micromachined, double spiral hotplate for MEMS gas sensors

This paper presents the design, fabrication and reliability testing of a double spiral platinum-based MEMS hotplate for gas sensing applications. The structure of MEMS hotplate consists of a 0.7 µm-thick thermally grown SiO₂ membrane of size 120 µm × 120 µm over which a double spiral platinum resistor is laid out. The hotplate membrane is supported by its four arms connected to the Si-substrate. The design and simulation of the hotplate structure was carried out using MEMS-CAD Tool COVENTORWARE. Based on the design, a double spiral platinum resistor of 103 Ω is fabricated on SiO₂ membrane using lift-off technique. The platinum deposition is carried out using DC sputtering technique. Bulk micromachining of Si is done from front side of the structure to create the suspended SiO₂ membrane. The temperature coefficient of resistance (TCR) of platinum is measured and found to be 2.19 × 10^?3/ °C. The TCR value is used for temperature estimation of the hotplate. The test results show that the microhotplate consumes only 20 mW power when heated up to 500 °C. For reliability testing of fabricated structure, the hotplate is continuously operated at 300 °C for 1.8 h. Also, it can sustain at least 61 cycles pulse-mode operation at 530 °C with ultra-low resistance and temperature drifts. The structure can sustain a maximum temperature and current of 611 °C and 11.55 mA respectively without any damage.     

Real-Time Global Illumination for VR Applications

Real-time global illumination in VR systems enhances scene realism by incorporating soft shadows, reflections of objects in the scene, and color bleeding. The Virtual Light Field (VLF) method enables real-time global illumination rendering in VR. The VLF has been integrated with the Extreme VR system for real-time GPU-based rendering in a Cave Automatic Virtual Environment.     

On the design of multi‐rate tracking controllers: Application to rotorcraft guidance and control

This paper presents a new methodology for the design and implementation of gain‐scheduled controllers for multi‐rate systems. The proposed methodology provides a natural way to address the integrated guidance and control problem for autonomous vehicles when the outputs are sampled at different instants of time. A controller structure is first proposed for the regulation of non‐square multi‐rate systems with more measured outputs than inputs. Based on this structure, an implementation for a gain‐scheduled controller is obtained that satisfies an important property known as the linearization property. The implementation resembles the velocity implementation for single‐rate systems. The method is then applied to the problem of steering an autonomous rotorcraft along a predefined trajectory defined in terms of space and time coordinates. By considering a convenient error vector to describe the vehicle's dynamics, the trajectory tracking problem is reduced to that of regulating the error variables to zero. Because of the periodic multi‐rate nature of the onboard sensor suite, the controller synthesis is dealt with under the scope of linear periodic systems theory. Simulation results obtained with a full non‐linear rotorcraft dynamic model are presented and discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

The Network as a Storage Device: Dynamic Routing with Bounded Buffers

We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations. In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a natural distributed greedy algorithm, is -competitive, essentially matching a known lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root of the tree. For grid graphs, we show that NTG has a competitive ratio of while no greedy algorithm can achieve a ratio better than . Finally, for arbitrary network topologies, we show that NTG is -competitive, improving upon an earlier bound of O(mn). An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin. S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1. S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science Foundation Grant. K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836.     

Vision-based control for rigid body stabilization

This paper addresses the problem of stabilizing to a desired equilibrium point an eye-in-hand system, which consists of a single camera mounted on a rigid body free to move on . It is assumed that there is a collection of landmarks fixed in the environment and that the image coordinates of those landmarks are provided to the system by an on-board CCD camera. The proposed method addresses not only the problem of stabilization but also that of maintaining feature visibility along the system’s trajectory. The resulting solution consists of a feedback control law based on the current and desired image coordinates and reconstructed attitude and depth ratio information, which guarantees that (i) the desired equilibrium point is an almost global attractor; (ii) a set of necessary conditions for feature visibility holds throughout the system’s trajectories; and (iii) the image of a predefined feature point is kept inside the camera’s field of view.     

Hybrid assessment method for software engineering decisions

During software development, many decisions need to be made to guarantee the satisfaction of the stakeholders' requirements and goals. The full satisfaction of all of these requirements and goals may not be possible, requiring decisions over conflicting human interests as well as technological alternatives, with an impact on the quality and cost of the final solution. This work aims at assessing the suitability of multi-criteria decision making (MCDM) methods to support software engineers' decisions. To fulfil this aim, a HAM (Hybrid Assessment Method) is proposed, which gives its user the ability to perceive the influence different decisions may have on the final result. HAM is a simple and efficient method that combines one single pairwise comparison decision matrix (to determine the weights of criteria) with one classical weighted decision matrix (to prioritize the alternatives). To avoid consistency problems regarding the scale and the prioritization method, HAM uses a geometric scale for assessing the criteria and the geometric mean for determining the alternative ratings.     

A framework for dynamic multiple-criteria decision making

The classic multiple-criteria decision making (MCDM) model assumes that, when taking a decision, the decision maker has defined a fixed set of criteria and is presented with a clear picture of all available alternatives. The task then reduces to computing the score of each alternative, thus producing a ranking, and choosing the one that maximizes this value.However, most real-world decisions take place in a dynamic environment, where the final decision is only taken at the end of some exploratory process. Exploration of the problem is often beneficial, in that it may unveil previously unconsidered alternatives or criteria, as well as render some of them unnecessary.In this paper we introduce a flexible framework for dynamic MCDM, based on the classic model, that can be applied to any dynamic decision process and which is illustrated by means of a small helicopter landing example. In addition, we outline a number of possible applications in very diverse fields, to highlight its versatility.