Electrochromic Response Time Performance of NiOx Film Prepared by Reactive Sputtering

2011 ◽  
Vol 31 (5) ◽  
pp. 0531003
Author(s):  
杨海刚 Yang Haigang ◽  
宋桂林 Song Guilin ◽  
王天兴 Wang Tianxing ◽  
尤天友 You Tianyou ◽  
常方高 Chang Fanggao
Keyword(s):  
Response Time ◽  
Reactive Sputtering ◽  
Time Performance

Lower Extremity Response Time Performance in Boys With ADHD

2007 ◽  
Vol 10 (4) ◽  
pp. 343-349 ◽  
Author(s):  
Scott J. Pedersen ◽  
Matthew Heath ◽  
Paul R. Surburg
Keyword(s):  
Lower Extremity ◽  
Response Time ◽  
Time Performance

Effect of fatigue on reaction time, response time, performance time, and kick impact in taekwondo roundhouse kick

2016 ◽  
Vol 16 (2) ◽  
pp. 201-209 ◽  
Author(s):  
Jader Sant’Ana ◽  
Emerson Franchini ◽  
Vinicius da Silva ◽  
Fernando Diefenthaeler
Keyword(s):  
Reaction Time ◽  
Response Time ◽  
Time Response ◽  
Time Performance ◽  
Performance Time ◽  
Reaction Time Response

Fractionated Lower Extremity Response Time Performance in Boys with and Without ADHD

2004 ◽  
Vol 21 (4) ◽  
pp. 315-329 ◽  
Author(s):  
Scott J. Pedersen ◽  
Paul R. Surburg ◽  
Matthew Heath ◽  
David M. Koceja
Keyword(s):  
Lower Extremity ◽  
Response Time ◽  
Comparison Group ◽  
Choice Response ◽  
Children With Adhd ◽  
Central Processing ◽  
Time Performance ◽  
Midline Crossing ◽  
Choice Response Time ◽  
Processing Mechanisms

The purpose was to investigate central and peripheral processing mechanisms through the use of electromyography (EMG) to determine differences between the performance of children with and without ADHD on a lower extremity choice response time task. Sixteen children with ADHD were tested on and off medication along with 19 children without ADHD. For premotor time, the comparison group performed significantly faster than children with ADHD. The longer latencies exhibited in central processing of children with ADHD were related to midline crossing inhibition (MCI). Medication improved the speed of processing for children with ADHD, but did not negate MCI.

scholarly journals Performance comparison of programming interfaces on the example of REST API, GraphQL and gRPC

2021 ◽  
Vol 21 ◽  
pp. 356-361
Author(s):  
Mariusz Śliwa ◽  
Beata Pańczyk
Keyword(s):  
Response Time ◽  
Execution Time ◽  
Web Applications ◽  
Performance Comparison ◽  
Performance Tests ◽  
Time Performance ◽  
Data Volume ◽  
Rest Api ◽  
Programming Interfaces ◽  
Made In

The article presents a comparison of the performance of three ways of implementing programming interfaces used in web applications - REST, GraphQL and gRPC. For the purposes of the research, three applications were developed, which were made in each of the indicated technologies and with the same functionalities. The applications were used for performance tests carried out with the use of the k6 tool. The applications are used to measure the execution time, performance and volume of processed data during display and adding operations. The obtained results allowed for the conclusion that the best interface in terms of performance (measured as the number of transactions per second) and server response time is REST. However, in terms of the smallest data volume, gRPC is the best choice.

Response time performance of a narrowband information broadcast system

1995 ◽  
Vol 8 (2) ◽  
pp. 111-116
Author(s):  
Y. M. Siu ◽  
C. K. Chan ◽  
K. L. Ho
Keyword(s):  
Response Time ◽  
Time Performance

scholarly journals Extended Adaptive Join Operator with Bind-Bloom Join for Federated SPARQL Queries

2017 ◽  
Vol 13 (3) ◽  
pp. 47-72
Author(s):  
Damla Oguz ◽  
Shaoyi Yin ◽  
Belgin Ergenç ◽  
Abdelkader Hameurlain ◽  
Oguz Dikenelli
Keyword(s):  
Response Time ◽  
Query Optimization ◽  
Linked Data ◽  
Completion Time ◽  
Optimal Response ◽  
Time Performance ◽  
Communication Time ◽  
Extended Operator ◽  
Adaptation Ability ◽  
Hash Join

The goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.

Why the Closest Ambulance Cannot be Dispatched in an Urban Emergency Medical Services System

2008 ◽  
Vol 23 (2) ◽  
pp. 161-165 ◽  
Author(s):  
Stephen F. Dean
Keyword(s):  
Response Time ◽  
Emergency Medical Services ◽  
Response Times ◽  
Peak Load ◽  
Medical Services ◽  
Structured Interviews ◽  
Time Performance ◽  
Emergency Medical ◽  
Dynamic Deployment ◽  
Computer Aided

AbstractIntroduction:Response time performance is related to increased survival for a relatively small group of patients with critical emergencies. Effectively utilizing current resources is a challenge for all emergency medical services (EMS) systems for reasons of cost-effectiveness and safety.Problem:The objective of this study was to identify opportunities for improving ambulance response-time performance in an urban EMS system using fixed deployment.Methods:This was a qualitative and quantitative case study which consisted of structured interviews with policy makers, managers, and workers in a fire department EMS division, as well as analysis of dispatch data and observation of dispatch operations.Results:The current computer-aided dispatch (CAD) system does not identify the closest ambulance to the emergency, and therefore, dispatchers must guess which unit is closer when units are not within their stations or “first due” areas. There is no means to track how often dispatchers guess correctly or how often the closest ambulance actually is dispatched to the emergency.Temporal and geographic patterns were identified. Opportunities also were identified to improve response time performance through the use of dynamic deployment and peak-load staffing.Conclusions:The results suggest that there were opportunities for improving ambulance response times by implementing strategies such as peak-load staffing and dynamic deployment. However, the most important improvement would be the implementation of a policy to send the closest ambulance to the emergency. More research is needed to identify how prevalent the failure to send the closest ambulance is within EMS systems that use fixeddeployment response strategies and computer-aided dispatch systems that are incapable of tracking unit locations outside of their stations.

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