9,676 research outputs found
Modeling server usage for online ticket sales
No full textThis article describes the use of a discrete event simulation model to estimate the server power required for the online sale of concert tickets to a required service standard. Data are available on the number of purchases made per hour and the percentage of tickets booked online for previous concerts and we describe how these are used to estimate the number of users in the system. We use bootstrapping to allow us to take account of the variability in this estimate when calculating the confidence intervals for the simulation model outputs. A queuing model is also introduced, which is useful to provide a quick calculation of how busy the server is before running the more computationally-intensive simulation model. A numerical example is used to describe the model and the methodology
Evaluation of the arrows method for classification of data
No full textWe evaluate the Arrows Classification Method (ACM) for grouping objects based onthe similarity of their data. This is a new method, which aims to achieve a balancebetween the conflicting objectives of maximizing internal cohesion and external isolationin the output groups. The method is widely applicable, especially in simulation input andoutput modelling, and has previously been used for grouping machines on an assemblyline, based on data on time-to-repair; and hospital procedures, based on length-of-staydata. The similarity of the data from a pair of objects is measured using the two-sampleCram´er-von-Mises goodness of fit statistic, with bootstrapping employed to find thesignificance or p-value of the calculated statistic. The p-values coming from the pairedcomparisons serve as inputs to the ACM, and allow the objects to be classified such thatno pair of objects that are grouped together have significantly different data. In thisarticle, we give the technical details of the method and evaluate its use through testingwith specially generated samples. We will also demonstrate its practical application withtwo real example
Optimal scheduling using length-of-stay data for diverse routine procedures
No full textThe paper describes the use of length-of-stay data to derive an optimal schedule for operating theatres. We consider situations where there are a large number of types of procedures that must be scheduled. The general approach we describe is to classify procedures by their length-of-stay data. An efficient scheduling tool can then be used to determine the optimal schedule for operations, where the aim is to reduce variability in the number of beds being used. We describe the application
of the method using a case study coming from a network of private hospitals in the UK
MEMS actuators and sensors: observations on their performance and selection for purpose
No full textThis paper presents an exercise in comparing the performance of microelectromechanical systems (MEMS) actuators and sensors as a function of operating principle. Data have been obtained from the literature for the mechanical performance characteristics of actuators, force sensors and displacement sensors. On-chip and off-chip actuators and sensors are each sub-grouped into families, classes and members according to their principle of operation. The performance of MEMS sharing common operating principles is compared with each other and with equivalent macroscopic devices. The data are used to construct performance maps showing the capability of existing actuators and sensors in terms of maximum force and displacement capability, resolution and frequency. These can also be used as a preliminary design tool, as shown in a case study on the design of an on-chip tensile test machine for materials in thin-film form
Classification analysis for simulation of the duration of machine breakdowns
No full textMachine failure can have a significant impact on the throughput of manufacturing systems, therefore accuratemodelling of breakdowns in manufacturing simulation models is essential. Finite mixture distributions havebeen successfully used by Ford Motor Company to model machine breakdown durations in simulation modelsof engine assembly lines. These models can be very complex, with a large number of machines. To simplifythe modelling we propose a method of grouping machines with similar distributions of breakdown durations,which we call the Arrows Classification Method, where the Two-Sample Cram´er-von-Mises statistic is usedto measure the similarity of two sets of the data. We evaluate the classification procedure by comparing thethroughput of a simulation model when run with mixture models fitted to individual machine breakdowndurations; mixture models fitted to group breakdown durations; and raw data. Details of the methods andresults of the classification will be presented, and demonstrated using an exampl
A new approach in data visualization to integrate time and space variability of daylighting in the design process
Full text linkThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 124-126).Daylighting design has great impact on the performance and aesthetical quality of a work of architecture but requires many issues to be addressed during the design process. The way existing daylighting tools deliver data to designers is still inefficient. The output display has no quick switch between quantitative and qualitative data and simply considers single moments with fixed weather condition. Designers are interrupted in their design process, and they usually need to make a data synthesis themselves, with the risk of overlooking critical periods or aspects of the design. Therefore, this thesis proposed a new data visualization method to improve this situation and create a more efficient data transmission between the designer and the program to better inform and support the design process. It used some existing research work in progress and developed a functional data visualization platform to simultaneously present sufficient quantitative and qualitative data over the year while linking closely the performance to annual weather variations, sun positions, and surroundings. As a result, designers are able to focus on refining their design while still taking into account the environmental influence over time in a convenient way. The proposed platform will work as an analysis interface for the ongoing LightSolve project at MIT Daylighting Lab.by Lu Yi.S.M
The Sacramental Theory in John 19:26-27
Full text linkAbout the author: Father Theodore Koehler, S.M., of the Seminaire Marianiste at the University of Fribourg, Switzerland, studied under Father Neubert
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