Combustion noise

A review of the subject of combustion generated noise is presented. Combustion noise is an important noise source in industrial furnaces and process heaters, turbopropulsion and gas turbine systems, flaring operations, Diesel engines, and rocket engines. The state-of-the-art in combustion noise importance, understanding, prediction and scaling is presented for these systems. The fundamentals and available theories of combustion noise are given. Controversies in the field are discussed and recommendations for future research are made

Stochastic Flux-Freezing and Magnetic Dynamo

We argue that magnetic flux-conservation in turbulent plasmas at high magnetic Reynolds numbers neither holds in the conventional sense nor is entirely broken, but instead is valid in a novel statistical sense associated to the "spontaneous stochasticity" of Lagrangian particle tra jectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. We discuss empirical evidence for spontaneous stochasticity, including our own new numerical results. We then use a Lagrangian path-integral approach to establish stochastic flux-freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux-conservation must remain stochastic at infinite magnetic Reynolds number. As an important application of these results we consider the kinematic, fluctuation dynamo in non-helical, incompressible turbulence at unit magnetic Prandtl number. We present results on the Lagrangian dynamo mechanisms by a stochastic particle method which demonstrate a strong similarity between the Pr = 1 and Pr = 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. We finally consider briefly some consequences for nonlinear MHD turbulence, dynamo and reconnectionComment: 29 pages, 10 figure

A Pilot Study of Propofol as an Anti-emetic in Laparoscopic, Gynecologic Surgery Patients

The goal of this project was to use sub-hypnotic doses of propofol to decrease post operative nausea and vomiting (PONV) rates in the immediate post-operative period in females, ages 18-65, undergoing laparoscopic gynecologic surgery. PONV is one of the largest complications of anesthesia affecting 20-30% of all surgical patients. Risk factors associated with PONV are female gender, laparoscopy, general anesthesia, opioids, volatile agents, and post-operative pain; all of which are frequently encountered. The incidence of PONV can prolong recovery time, delay discharge, increase patient cost, decrease patient satisfaction, and can cause significant medical complications. Propofol has previously demonstrated anti-emetic properties; often being used in total intravenous anesthesia in patients with known PONV. This pilot study investigated if the administration of a sub-hypnotic dose of propofol, as an anti-emetic during emergence period of anesthesia, affects PONV rates during the immediate post-operative period. A randomized, blinded, controlled comparison group study was conducted to investigate the use of propofol as an antiemetic. A group of 10 (N=10) ASA I or II patients, ages 18-65, undergoing laparoscopic, gynecologic surgery were examined using a verbal analog scale. These patients were randomly assigned to a control group which received ZofranTM only, or a treatment group which received ZofranTM and propofol. A paired samples t-test failed to reveal a statistically reliable difference between the mean of the CX (M = 0, s = 0) and TX (M = 2.00, s = 4.472) group created during this pilot study, t(8) = 1.000, p = .0.174, α = .05. A chi-square test was performed and no relationship was found between the CX and TX groups in relation to vomiting, X2 (1, N = 10) = 1.111, p =0.146. Thus, the pilot study determined there was no statistical significance of preventing PONV with sub-hypnotic doses of propofol

Untraceable Blind Multisignature

Multisignature is a variant of digital signature which enables a document to be signed by multiple signers simultaneously in a collaboration. It ensures the fairness property of the signer. Blind signature is another variant of digital signature in which a message is signed without disclosing its content. Blindness is an important property of blind signature in which, the message and the signature are unlinkable after signature is attached to the message.In this Thesis, we designed a Blind Multisignature protocol with security features of blind signatures and multisignature. The security of the scheme lies in hard computational assumptions such as Integer Factorization problem (IFP), computational Diffie-Hellman problem (CDHP) and discrete logarithmic problem (DLP). The correctness of the scheme is tested mathematically and the scheme is also implemented in Java platform. The computational cost of the proposed scheme is low and the signature length (in byte) is nominal with the message size. The time of computation of each phase is computed and found to be low as compared to competent schemes. The security analysis of the scheme is done rigorously and the security features such as untraceability, blindness and unforgeability of the proposed scheme has been analysed and found secure under the attack. The scheme has properties of both blind signature and multi-signature. This scheme can be applied to real life applications such as electronic cash and electronic voting

Thin film memory matrix using amorphous and high resistive layers

Memory cells in a matrix are provided by a thin film of amorphous semiconductor material overlayed by a thin film of resistive material. An array of parallel conductors on one side perpendicular to an array of parallel conductors on the other side enable the amorphous semiconductor material to be switched in addressed areas to be switched from a high resistance state to a low resistance state with a predetermined level of electrical energy applied through selected conductors, and thereafter to be read out with a lower level of electrical energy. Each cell may be fabricated in the channel of an MIS field-effect transistor with a separate common gate over each section to enable the memory matrix to be selectively blanked in sections during storing or reading out of data. This allows for time sharing of addressing circuitry for storing and reading out data in a synaptic network, which may be under control of a microprocessor

Guide them through: an automatic crowd control framework using multi-objective genetic programming

We propose an automatic crowd control framework based on multi-objective optimisa- tion of strategy space using genetic programming. In particular, based on the sensed local crowd densities at different segments, our framework is capable of generating control strategies that guide the individuals on when and where to slow down for opti- mal overall crowd flow in realtime, quantitatively measured by multiple objectives such as shorter travel time and less congestion along the path. The resulting Pareto-front al- lows selection of resilient and efficient crowd control strategies in different situations. We first chose a benchmark scenario as used in [1] to test the proposed method. Results show that our method is capable of finding control strategies that are not only quanti- tatively measured better, but also well aligned with domain experts’ recommendations on effective crowd control such as “slower is faster” and “asymmetric control”. We further applied the proposed framework in actual event planning with approximately 400 participants navigating through a multi-story building. In comparison with the baseline crowd models that do no employ control strategies or just use some hard-coded rules, the proposed framework achieves a shorter travel time and a significantly lower (20%) congestion along critical segments of the path

Practice-driven solutions for inventory management problems in data-scarce environments

Many firms are challenged to make inventory decisions with limited data, and high customer service level requirements. This thesis focuses on heuristic solutions for inventory management problems in data-scarce environments, employing rigorous mathematical frameworks and taking advantage of the information that is available in practice but often ignored in literature. We define a class of inventory models and solutions with demonstrable value in helping firms solve these challenges