Keyword search (4,163 papers available)

"Sensors (Basel)" Category Publications:

Title Authors PubMed ID
1 On the Impact of Biceps Muscle Fatigue in Human Activity Recognition. Elshafei M, Costa DE, Shihab E 33557239
ENCS
2 Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables. Elshafei M, Shihab E 33498702
ENCS
3 Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker. Singh P, Abedini Sohi P, Kahrizi M 33467459
ENCS
4 A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects. Khannouz M; Glatard T; 33202905
ENCS
5 Contactless Capacitive Electrocardiography Using Hybrid Flexible Printed Electrodes. Lessard-Tremblay M, Weeks J, Morelli L, Cowan G, Gagnon G, Zednik RJ 32927651
ENCS
6 Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City. Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S 32316356
ENCS
7 A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors. Dehghani A, Sarbishei O, Glatard T, Shihab E 31752158
ENCS
8 Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development. Alsaig A, Alagar V, Chammaa Z, Shiri N 31141899
CONCORDIA
9 A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing. Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO 29762493
ENCS
10 Fast Feature-Preserving Approach to Carpal Bone Surface Denoising. Salim I, Hamza AB 30037109
ENCS
11 Big Data-Driven Cellular Information Detection and Coverage Identification. Wang H, Xie S, Li K, Ahmad MO 30813353
ENCS
12 Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing. Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D 28906434
PHYSICS

 

Title:A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing.
Authors:Li KWang HXu XDu YLiu YAhmad MO
Link:https://www.ncbi.nlm.nih.gov/pubmed/29762493?dopt=Abstract
Publication:
Keywords:
PMID:29762493 Category:Sensors (Basel) Date Added:2019-06-04
Dept Affiliation: ENCS
1 College of Smart City, Beijing Union University, Beijing 100101, China. like@buu.edu.cn.
2 College of Smart City, Beijing Union University, Beijing 100101, China. whyxdt@163.com.
3 College of Smart City, Beijing Union University, Beijing 100101, China. 151081210202@buu.edu.cn.
4 College of Robotics, Beijing Union University, Beijing 100101, China. duyu@buu.edu.cn.
5 College of Robotics, Beijing Union University, Beijing 100101, China. yuansheng@buu.edu.cn.
6 Department of Electrical and Computer Engineering, Concordia University, Montreal, QC H3G IM8, Canada. omair@ece.concordia.ca.

Description:

A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing.

Sensors (Basel). 2018 May 15;18(5):

Authors: Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO

Abstract

Service perception analysis is crucial for understanding both user experiences and network quality as well as for maintaining and optimizing of mobile networks. Given the rapid development of mobile Internet and over-the-top (OTT) services, the conventional network-centric mode of network operation and maintenance is no longer effective. Therefore, developing an approach to evaluate and optimizing users' service perceptions has become increasingly important. Meanwhile, the development of a new sensing paradigm, mobile crowdsensing (MCS), makes it possible to evaluate and analyze the user's OTT service perception from end-user's point of view other than from the network side. In this paper, the key factors that impact users' end-to-end OTT web browsing service perception are analyzed by monitoring crowdsourced user perceptions. The intrinsic relationships among the key factors and the interactions between key quality indicators (KQI) are evaluated from several perspectives. Moreover, an analytical framework of perceptional degradation and a detailed algorithm are proposed whose goal is to identify the major factors that impact the perceptional degradation of web browsing service as well as their significance of contribution. Finally, a case study is presented to show the effectiveness of the proposed method using a dataset crowdsensed from a large number of smartphone users in a real mobile network. The proposed analytical framework forms a valuable solution for mobile network maintenance and optimization and can help improve web browsing service perception and network quality.

PMID: 29762493 [PubMed]





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University