Radar chart: Scanning for high QoE in QoS dimensions

Chang, Yuchun; Chang, Chi-Jui; Chen, Kuan-Ta; Lei, Chin-Laung

doi:10.1109/cqr.2010.5619915

Cited by 8 publications

(3 citation statements)

References 9 publications

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“…Research on the Radar Chart Theory also has applied to the indoor environmental comfort level evaluation [13]. In multimedia area, the authors in [14] adapt radar chart to map the many-to-one relationship between QoS metrics and QoE. But this radar chart adaption they introduced lacks of readability and does not build a practicable model to implement QoE evaluation.…”

Section: B Radar Chart Theorymentioning

confidence: 99%

A novel QoE evaluation model for video quality

Yueze

Sun

2013

IEEE Conference Anthology

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In this paper, a novel objective no-reference model for evaluating video quality of experience (QoE) based on pattern matching of radar chart is proposed. With the input of N-dimensional data, the novel model may have the various video QoE with the different shapes of radar chart patterns. By discriminatory analysis of the patterns, the proposed model makes an effective and visual evaluation for video quality. Experimental results show effectiveness of the proposed model.

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Section: B Radar Chart Theorymentioning

confidence: 99%

A novel QoE evaluation model for video quality

Yueze

Sun

2013

IEEE Conference Anthology

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“…Figure 10 shows four examples of profiles in the form of a radar chart (or Kiviat diagram, as described in Chang et al 18 ) based on data collected on four participants having different characteristics in our dataset. The minimum and maximum axes for each characteristic are determined according to our dataset.…”

Section: Use-casementioning

confidence: 99%

“…Indeed, the veracity of the Android activity recognition API has been largely verified by the literature and supported by previous studies. 7 Use-case Figure 10 shows four examples of profiles in the form of a radar chart (or Kiviat diagram, as described in Chang et al 18 ) based on data collected on four participants having different characteristics in our dataset. The minimum and maximum axes for each characteristic are determined according to our dataset.…”

Section: Mobility Metricsmentioning

confidence: 99%

Characterizing user mobility using mobile sensing systems

Faye

Bronzi

Tahirou

et al. 2017

International Journal of Distributed Sensor Networks

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Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allows us to assess human behavior and movement at different levels. In this article, extended from previous work, we focus on the concept of human mobility and explore how we can exploit a dataset collected opportunistically from multiple participants. In particular, we study how the different sensor groups present in most commercial smart devices can be used to deliver mobility information and patterns. In addition to traditional motion sensors that are obviously important in this field, we are also exploring data from physiological and environmental sensors, including new ways of displaying, understanding, and analyzing data. Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. We finally offer a mobility assistant that can represent different user characteristics anonymously, based on a combination of Wi-Fi, activity data, and graph theory.

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A Three-Step Service Experience Approach with Feedback for Service Provider

Yang

et al. 2011

2011 IEEE Asia-Pacific Services Computing Conference

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Radar chart: Scanning for high QoE in QoS dimensions

Cited by 8 publications

References 9 publications

A novel QoE evaluation model for video quality

A novel QoE evaluation model for video quality

Characterizing user mobility using mobile sensing systems

A Three-Step Service Experience Approach with Feedback for Service Provider

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