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

Queuing-Inventory Models with MAP Demands and Random Replenishment Opportunities

Combining the study of queuing with inventory is very common and such systems are referred to as queuing-inventory systems in the literature. These systems occur naturally in practice and have been studied extensively in the literature. The inventory systems considered in the literature generally include (s, S)-type. However, in this paper we look at opportunistic-type inventory replenishment in which there is an independent point process that is used to model events that are called opportunistic for replenishing inventory. When an opportunity (to replenish) occurs, a probabilistic rule that depends on the inventory level is used to determine whether to avail it or not. Assuming that the customers arrive according to a Markovian arrival process, the demands for inventory occur in batches of varying size, the demands require random service times that are modeled using a continuous-time phase-type distribution, and the point process for the opportunistic replenishment is a Poisson process, we apply matrix-analytic methods to study two of such models. In one of the models, the customers are lost when at arrivals there is no inventory and in the other model, the customers can enter into the system even if the inventory is zero but the server has to be busy at that moment. However, the customers are lost at arrivals when the server is idle with zero inventory or at service completion epochs that leave the inventory to be zero. Illustrative numerical examples are presented, and some possible future work is highlighted

Prediction of Soakout Time Using Analytical Models

In precision manufacturing enterprises, machine parts at nonstandard temperatures are often soaked to standard temperature prior to making any dimensional measurements. The soakout times are usually determined using lumped heat-transfer models where the part temperatures are assumed to be uniform. This article discusses conditions under which lumped model assumptions are valid by comparing lumped analyses for various shapes and materials with the more general finite element results. In addition, the effect of ambient temperature cycling on part response is also studied

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

A batch-service queueing model with a discrete batch Markovian arrival process

Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of customers in system (system content) reaches or exceeds a threshold. Correlation is taken into account by assuming a discrete batch Markovian arrival process (D-BMAP), i.e. the distribution of the number of customer arrivals per slot depends on a background state which is determined by a first-order Markov chain. We deduce the probability generating function of the system content at random slot marks and we examine the influence of correlation in the arrival process on the behavior of the system. We show that correlation merely has a small impact on the threshold that minimizes the mean system content. In addition, we demonstrate that correlation might have a significant influence on the system content and therefore has to be included in the model

Early detection of neovascular age-related macular degeneration : an economic evaluation based on data from the EDNA study

Funding: The project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment Programme (grant number: 12/142/07) and will be published in full in Health Technology Assessment. The funder was not involved in the study design; in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication. The Health Services Research Unit (HSRU) and the Health Economics Research Unit (HERU) are core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorate (HSRU/2021-2024, HERU/2021-2024).Peer reviewedPostprin

Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data: Consensus on Neovascular Age-Related Macular Degeneration Nomenclature Study Group

© 2019 American Academy of Ophthalmology Purpose: To establish a process to evaluate and standardize a state-of-the-art nomenclature for reporting neovascular age-related macular degeneration (AMD) data. Design: Consensus meeting. Participants: An international panel of retina specialists, imaging and image reading center experts, and ocular pathologists. Methods: During several meetings organized under the auspices of the Macula Society, an international study group discussed and codified a set nomenclature framework for classifying the subtypes of neovascular AMD and associated lesion components. Main Outcome Measures: A consensus classification of neovascular AMD. Results: The study group created a standardized working definition of AMD. The components of neovascular AMD were defined and subclassified. Disease consequences of macular neovascularization were delineated. Conclusions: The framework of a consensus nomenclature system, a definition of AMD, and a delineation of the subtypes of neovascular AMD were developed. Establishing a uniform set of definitions will facilitate comparison of diverse patient groups and different studies. The framework presented is modified and updated readily, processes that are anticipated to occur on a periodic basis. The study group suggests that the consensus standards outlined in this article be used in future reported studies of neovascular AMD and clinical practice

Answering SPARQL queries over databases under OWL 2 QL entailment regime

We present an extension of the ontology-based data access platform Ontop that supports answering SPARQL queries under the OWL 2 QL direct semantics entailment regime for data instances stored in relational databases. On the theoretical side, we show how any input SPARQL query, OWL 2 QL ontology and R2RML mappings can be rewritten to an equivalent SQL query solely over the data. On the practical side, we present initial experimental results demonstrating that by applying the Ontop technologies—the tree-witness query rewriting, T-mappings compiling R2RML mappings with ontology hierarchies, and T-mapping optimisations using SQL expressivity and database integrity constraints—the system produces scalable SQL queries

Modeling Basal Ganglia for understanding Parkinsonian Reaching Movements

We present a computational model that highlights the role of basal ganglia (BG) in generating simple reaching movements. The model is cast within the reinforcement learning (RL) framework with the correspondence between RL components and neuroanatomy as follows: dopamine signal of substantia nigra pars compacta as the Temporal Difference error, striatum as the substrate for the Critic, and the motor cortex as the Actor. A key feature of this neurobiological interpretation is our hypothesis that the indirect pathway is the Explorer. Chaotic activity, originating from the indirect pathway part of the model, drives the wandering, exploratory movements of the arm. Thus the direct pathway subserves exploitation while the indirect pathway subserves exploration. The motor cortex becomes more and more independent of the corrective influence of BG, as training progresses. Reaching trajectories show diminishing variability with training. Reaching movements associated with Parkinson's disease (PD) are simulated by (a) reducing dopamine and (b) degrading the complexity of indirect pathway dynamics by switching it from chaotic to periodic behavior. Under the simulated PD conditions, the arm exhibits PD motor symptoms like tremor, bradykinesia and undershoot. The model echoes the notion that PD is a dynamical disease.Comment: Neural Computation, In Pres