Uniformly high order accurate essentially non-oscillatory schemes 3

In this paper (a third in a series) the construction and the analysis of essentially non-oscillatory shock capturing methods for the approximation of hyperbolic conservation laws are presented. Also presented is a hierarchy of high order accurate schemes which generalizes Godunov's scheme and its second order accurate MUSCL extension to arbitrary order of accuracy. The design involves an essentially non-oscillatory piecewise polynomial reconstruction of the solution from its cell averages, time evolution through an approximate solution of the resulting initial value problem, and averaging of this approximate solution over each cell. The reconstruction algorithm is derived from a new interpolation technique that when applied to piecewise smooth data gives high-order accuracy whenever the function is smooth but avoids a Gibbs phenomenon at discontinuities. Unlike standard finite difference methods this procedure uses an adaptive stencil of grid points and consequently the resulting schemes are highly nonlinear

Two Parallel Finite Queues with Simultaneous Services and Markovian Arrivals

In this paper, we consider a finite capacity single server queueing model with two buffers, A and B, of sizes K and N respectively. Messages arrive one at a time according to a Markovian arrival process. Messages that arrive at buffer A are of a different type from the messages that arrive at buffer B. Messages are processed according to the following rules: 1. When buffer A(B) has a message and buffer B(A) is empty, then one message from A(B) is processed by the server. 2. When both buffers, A and B, have messages, then two messages, one from A and one from B, are processed simultaneously by the server. The service times are assumed to be exponentially distributed with parameters that may depend on the type of service. This queueing model is studied as a Markov process with a large state space and efficient algorithmic procedures for computing various system performance measures are given. Some numerical examples are discussed

Multiple bilateral submandibular gland sialolithiasis

Sialolithiasis accounts for the most common etiology of salivary gland obstruction which leads to recurrent painful swelling of the involved gland which often exacerbates while eating. Stones may be encountered in any of the salivary glands but most frequently in the submandibular gland and its duct. Simultaneous sialolithiasis in more than one salivary gland is rare, occurring in fewer than 3% of cases. Seventy to 80% of cases feature solitary stones; only about 5% of patients have three or more stones, the case report which we are presenting here had three submandibular sialoliths involving both the submandibular glands which were removed by intraoral approach and no post‑operative complications were noted.Key words: Bilateral, multiple, sialolithiasis, submandibula

An exponentially fitted finite difference scheme for a class of singularly perturbed delay differential equations with large delays

AbstractThis paper deals with singularly perturbed boundary value problem for a linear second order delay differential equation. It is known that the classical numerical methods are not satisfactory when applied to solve singularly perturbed problems in delay differential equations. In this paper we present an exponentially fitted finite difference scheme to overcome the drawbacks of the corresponding classical counter parts. The stability of the scheme is investigated. The proposed scheme is analyzed for convergence. Several linear singularly perturbed delay differential equations have been solved and the numerical results are presented to support the theory

Algorithmic analysis of the maximum level length in general-block two-dimensional Markov processes

Two-dimensional continuous-time Markov chains (CTMCs) are useful tools for studying stochastic models such as queueing, inventory, and production systems. Of particular interest in this paper is the distribution of the maximal level visited in a busy period because this descriptor provides an excellent measure of the system congestion. We present an algorithmic analysis for the computation of its distribution which is valid for Markov chains with general-block structure. For a multiserver batch arrival queue with retrials and negative arrivals, we exploit the underlying internal block structure and present numerical examples that reveal some interesting facts of the system

Consistent Anisotropic Repulsions for Simple Molecules

We extract atom-atom potentials from the effective spherical potentials that suc cessfully model Hugoniot experiments on molecular fluids, e.g., $O_2$ and $N_2$. In the case of $O_2$ the resulting potentials compare very well with the atom-atom potentials used in studies of solid-state propertie s, while for $N_2$ they are considerably softer at short distances. Ground state (T=0K) and room temperatu re calculations performed with the new $N-N$ potential resolve the previous discrepancy between experimental and theoretical results.Comment: RevTeX, 5 figure

Experimental and Numerical Determination of Interface Slip Coefficient of Fluid Stream Exiting a Partially Filled Porous Medium Channel

Stacks of parallel plates modeled as a standard fissure-type anisotropic porous medium are filled inside a rectangular channel up to half the cross section height. The interface slip coefficient a for the isothermal laminar incompressible flow exiting this partially filled porous-medium channel is then determined using particle image velocimetry (PIV) experiments and numerical simulations. Required measurements of the Darcy velocity u D on the porous-medium (PM) side, the local velocity u f , and its gradient @u f =@y on the clear-fluid (CF) side are performed across different length scales. The fissure-type porous-medium parameters are systematically varied in the porosity range 0:2 / 0:95 and flow direction permeability 10 À6 < K; m 2 < 10 À9 . From the exit-velocity profile, the empirical slip coefficient a is determined using a generalized relationship. When the measurements across the PM-CF interface are performed across a length scale equal to the representative elemental length (REL) of the porous media considered (i.e., equal to the sum of plate thickness (a) and gap (b)), the determined a value is found to remain invariant

Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

Fuzzy based clustering in CWPSN using machine learning model

90-94Cognitive wireless power sensor network (CWPSN) technology, widely used in almost all fields, has addressed various issues. The researchers have addressed the problems in the lack of radio spectrum availability and enabled the allocation of dynamic spectrum access in specific fields. The main challenge has been to support the radio spectrum allocation using intelligent adaptive learning and decision-making techniques so that various requirements of 5G wireless networks can be encountered. Machine learning (ML) is one of the most promising artificial intelligence tools conceived to support cognitive wireless networks. This paper aims to provide energy optimization and enhance security to cognitive wireless power sensor networks using a novel protocol during resource allocation. In addition to the existing methods, a novel protocol, fuzzy cluster-based greedy algorithms for attack prediction and energy harvesting using a machine-language model based on neural network techniques have been introduced. The simulation has been done using MATLAB software tools which gives efficient results