scholarly journals First performance measurements of the Fast Tracker Real Time Processor at ATLAS

2019 ◽  
Author(s):  
Nicolo Vladi Biesuz ◽  
Keyword(s):  
Real Time ◽  
Performance Measurements ◽  
Fast Tracker

scholarly journals Weightlifting Performance Measurements Using Low Cost Accelerometers With Applications to Real Time Coaching and Rehabilitation

2010 ◽  
Vol 28 (1) ◽  
pp. 24-25
Author(s):  
G.L. Tangonan ◽  
N. Libatique ◽  
F.T. Pulma ◽  
D.L. Lagazo ◽  
M. Castro
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Performance Measurements

scholarly journals Design and Implementation of a Framework for Multi-Cloud Service Broker

2021 ◽  
Author(s):  
Md Ahsan Ullah
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Location Awareness ◽  
Performance Measurements ◽  
Positioning Systems ◽  
Network Connection ◽  
Service Broker

Cloud service broker (CSB) as an emerging technology intermediates heterogeneous multiple cloud services for both the providers and consumers. Recently, Cloud computing & mobile cloud computing applications (MCA) have gained an enormous popularity, which has led to an increasing need for the development of platform independent Middleware/CSB to support all types of cloud service consumer applications including x86*x64 based standard OS & ARM based mobile applications, web browsers, etc. Developing Platform Independent Hybrid CSB, however, is not an easy task. Developers have to deal with difficulties inherent from the different cloud controllers, cloud service providers environments, clients’ application types, network connection types (wired, wireless), GPS (Global Positioning Systems) information of cloud resources and clients’ etc. In this thesis, the proposed design of a middleware/CSB that abstracts the real-time resources of various clouds (private, public, home, Local) and stores the resources in its own Database. It will also store clients requests then analyzes the request to find the nearest available servers which is running the appropriate applications. Then the CSB will forward the destination servers information to the clients. Thesis goal is to achieve context awareness, location awareness, platform independence, portability, efficiency, and usability. Portability is achieved by following the J2ME platform specifications. The middleware has been implemented and tested on a real time Openstack cloud using by our newly designed Android Clients and platform independent Mozilla Firefox browser. The performance measurements of the middleware show that it achieves its efficiency requirements. Furthermore, the middleware’s database can be used for resource algorithm, pattern analysis, and for future requirements.

scholarly journals A Mathematical Model toward Real-Time Monitoring of Automotive PEM Fuel Cells

2020 ◽  
Author(s):  
Alireza Goshtasbi ◽  
Benjamin L. Pence ◽  
Jixin Chen ◽  
Michael A. DeBolt ◽  
Chunmei Wang ◽  
...  
Keyword(s):  
Fuel Cells ◽  
Real Time ◽  
Computational Cost ◽  
Membrane Electrode Assembly ◽  
Pem Fuel Cells ◽  
Membrane Electrode ◽  
Performance Measurements ◽  
Real Time Monitoring ◽  
Model Calculations ◽  
Wide Range

A computationally efficient model toward real-time monitoring of automotive polymer electrolyte membrane (PEM) fuel cell stacks is developed. Computational efficiency is achieved by spatio-temporal decoupling of the problem, developing a new reduced-order model for water balance across the membrane electrode assembly (MEA), and defining a new variable for cathode catalyst utilization that captures the trade-off between proton and mass transport limitations without additional computational cost. Together, these considerations result in the model calculations to be carried out more than an order of magnitude faster than real time. Moreover, a new iterative scheme allows for simulation of counter-flow operation and makes the model flexible for different flow configurations. The proposed model is validated with a wide range of experimental performance measurements from two different fuel cells. Finally, simulation case studies are presented to demonstrate the prediction capabilities of the model.

scholarly journals HYBRIDJOIN for Near-Real-Time Data Warehousing

2011 ◽  
Vol 7 (4) ◽  
pp. 21-42 ◽  
Author(s):  
M. Asif Naeem ◽  
Gillian Dobbie ◽  
Gerald Weber
Keyword(s):  
Real Time ◽  
Data Stream ◽  
Time Integration ◽  
Synthetic Data ◽  
Performance Measurements ◽  
Time Data ◽  
Join Algorithm ◽  
Real Time Data ◽  
Set Up ◽  
Nested Loop

An important component of near-real-time data warehouses is the near-real-time integration layer. One important element in near-real-time data integration is the join of a continuous input data stream with a disk-based relation. For high-throughput streams, stream-based algorithms, such as Mesh Join (MESHJOIN), can be used. However, in MESHJOIN the performance of the algorithm is inversely proportional to the size of disk-based relation. The Index Nested Loop Join (INLJ) can be set up so that it processes stream input, and can deal with intermittences in the update stream but it has low throughput. This paper introduces a robust stream-based join algorithm called Hybrid Join (HYBRIDJOIN), which combines the two approaches. A theoretical result shows that HYBRIDJOIN is asymptotically as fast as the fastest of both algorithms. The authors present performance measurements of the implementation. In experiments using synthetic data based on a Zipfian distribution, HYBRIDJOIN performs significantly better for typical parameters of the Zipfian distribution, and in general performs in accordance with the theoretical model while the other two algorithms are unacceptably slow under different settings.

Data Infrastructure for Connected Vehicle Applications

2020 ◽  
Vol 2674 (5) ◽  
pp. 85-96
Author(s):  
Xingmin Wang ◽  
Shengyin Shen ◽  
Debra Bezzina ◽  
James R. Sayer ◽  
Henry X. Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Transportation Systems ◽  
Connected Vehicle ◽  
Performance Measurements ◽  
Trajectory Data ◽  
Test Environment ◽  
Data Infrastructure ◽  
Time Space ◽  
Wide Range

Ann Arbor Connected Vehicle Test Environment (AACVTE) is the world’s largest operational, real-world deployment of connected vehicles (CVs) and connected infrastructure, with over 2,500 vehicles and 74 infrastructure sites, including intersections, midblocks, and highway ramps. The AACVTE generates a massive amount of data on a scale not seen in the traditional transportation systems, which provides a unique opportunity for developing a wide range of connected vehicle (CV) applications. This paper introduces a data infrastructure that processes the CV data and provides interfaces to support real-time or near real-time CV applications. There are three major components of the data infrastructure: data receiving, data pre-processing, and visualization including the performance measurements generation. The data processing algorithms include signal phasing and timing (SPaT) data compression, lane phase mapping identification, trajectory data map matching, and global positioning system (GPS) coordinates conversion. Simple performance measures are derived from the processed data, including the time–space diagram, vehicle delay, and observed queue length. Finally, a web-based interface is designed to visualize the data. A list of potential CV applications including traffic state estimation, traffic control, and safety, which can be built on this connected data infrastructure is discussed.

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