A traffic control method for service quality assurance in an ATM network

1994 ◽  
Vol 12 (2) ◽  
pp. 322-331 ◽  
Author(s):  
S. Abe ◽  
T. Soumiya
Keyword(s):  
Quality Assurance ◽  
Service Quality ◽  
Traffic Control ◽  
Control Method ◽  
Atm Network

Psychiatric occupational therapy service – quality assurance

2004 ◽  
Vol 58 (5) ◽  
pp. 403-407 ◽  
Author(s):  
Lena Haglund ◽  
Ingalill Rahm Hallberg ◽  
Merdita Pettersson
Keyword(s):  
Quality Assurance ◽  
Occupational Therapy ◽  
Service Quality ◽  
Therapy Service

scholarly journals A Bayesian Network Based Method for Service Quality Optimization

2018 ◽  
Vol 11 (3) ◽  
pp. 1
Author(s):  
Lian Gaofeng
Keyword(s):  
Quality Assurance ◽  
Service Quality ◽  
Bayesian Network ◽  
Video Quality ◽  
Quality Parameters ◽  
Industrial Sectors ◽  
Internet Streaming ◽  
Contextual Awareness ◽  
The Relationship ◽  
Quality Assurance Method

Video conference, as an application of Internet streaming media, has attracted wide attention from both academic and industrial sectors. However, usersmay encounter many problemsindailyuse, such as poor video quality, playback delay, and lack of adjustable context, whichcausenegative impactson customers’usage experience. Existing end-to-end service quality assurance method mainly analyzes the relationship between the target service quality parameters and the context in a “single” manner. In this paper, we propose a Bayesian network-based service quality assurance method (named as Comprehensively Context-Aware approach, CCA), which combines Bayesian network and fuzzy set theoryand obtainsrandomrelationshipsamongdifferent service quality parameters through contextual awareness. Comprehensive experimentsclearly validate the superiority of CCA against other well-established methods.

A Novel Non-Supervised Deep-Learning-Based Network Traffic Control Method for Software Defined Wireless Networks

2018 ◽  
Vol 25 (4) ◽  
pp. 74-81 ◽  
Author(s):  
Bomin Mao ◽  
Fengxiao Tang ◽  
Zubair Md. Fadlullah ◽  
Nei Kato ◽  
Osamu Akashi ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Deep Learning ◽  
Network Traffic ◽  
Traffic Control ◽  
Control Method

Using a Fuzzy Quality Function Deployment Model to Identify Improvement Points in Airport Cargo Terminals

2005 ◽  
Vol 1935 (1) ◽  
pp. 130-140
Author(s):  
Gin-Shuh Liang ◽  
Tzeu-Chen Han ◽  
Tsung-Yu Chou
Keyword(s):  
Quality Assurance ◽  
Service Quality ◽  
Quality Function Deployment ◽  
Service Management ◽  
Practical Investigations ◽  
Fuzzy Relation ◽  
Quality Function ◽  
Customer Needs ◽  
Fuzzy Relation Matrix ◽  
Fuzzy Quality Function Deployment

The main purpose of this paper is to present a fuzzy quality function deployment model to achieve service quality assurance before implementing service action. First, customer needs with their importance and satisfaction levels acquired from practical investigations are constructed. Then, by combining the experts’ opinions, service management requirements are developed for satisfying the observed customer needs. In addition, a fuzzy relation matrix for linking service management requirements to customer needs is constructed on the basis of cross-functional expertise. The aggregated fuzzy assessments of different service management requirements are also ranked to prioritize and determine their importance. Finally, the Chiang Kai-shek International Airport cargo terminal in Taiwan is used to demonstrate the proposed approach.

The control method for the multi-phase traffic model

2016 ◽  
Vol 27 (10) ◽  
pp. 1650111
Author(s):  
Yi Liu ◽  
Rong-Jun Cheng ◽  
Yan-Qiang Ma ◽  
Hong-Xia Ge
Keyword(s):  
Traffic Control ◽  
Control Method ◽  
Turning Points ◽  
Control Signal ◽  
Two Phase ◽  
Optimal Velocity ◽  
Car Following Model ◽  
The Stability ◽  
Improved Model ◽  
Multi Phase

Based on multi-phase car-following model proposed by Nagatani, the control theory method is used to analyze the stability of the model. The optimal velocity function is improved to have more turning points. The original optimal velocity with one turning point shows two-phase traffic, while the improved model with [Formula: see text] turning points exhibits [Formula: see text] phase traffic. Control signal is added into the model. Numerical simulation is conducted to show the results for the stability of the model with and without control signal.

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