Adaptive Transformation for a Scalable User Interface Framework Supporting Multi-screen Services

Bae, Yuseok; Oh, Bong-Jin; Park, Jongyoul

doi:10.1007/978-3-642-41671-2_54

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…Fukazawa et al [21] proposed and evaluated a method that ranks (using Ranking SVM -Support Vector Machine-) the menu functions of a mobile application based on user operation history. Bae et al [22] proposed an adaptive transformation framework that automatically adjusts the content and the appearance to different devices (different sizes and capabilities).…”

Section: Related Workmentioning

confidence: 99%

A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major Depression

Bresó

Martı́nez-Miranda

Fuster–Garcia

et al. 2016

International Journal of Human-Computer Studies

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Human Computer Interaction (HCI) is a research field which aims to improve the relationship between users and interactive computer systems. A main objective of this research area is to make the user experience more pleasant and efficient, minimizing the barrier between the users' cognition of what they want to accomplish and the computer's understanding of the user's tasks, by means of user-friendly, useful and usable designs. A bad HCI design is one of the main reasons behind user rejection of computer-based applications, which in turn produces loss of productivity and economy in industrial environments. In the eHealth domain, user rejection of computer-based systems is a major barrier to exploiting the maximum benefit from those applications developed to support the treatment of diseases, and in the worst cases a poor design in these systems may cause deterioration in the clinical condition of the patient. Thus,

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Section: Related Workmentioning

confidence: 99%

A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major Depression

Bresó

Martı́nez-Miranda

Fuster–Garcia

et al. 2016

International Journal of Human-Computer Studies

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“…Kwon et al [22] identified the different factors such as service quality, ease of use, and price fairness that affect the behavioral intent of using existing N-Screen service. A scalable framework is proposed in [23] to provide web-based N-Screen user interface management for different screen layouts. A seamless screen switching scheme without intervention of user is proposed considering the user's context extracted from the embedded sensors in the devices [24].…”

Section: Background and Related Workmentioning

confidence: 99%

QoS and QoE Aware N-Screen Multicast Service

Sarwar¹,

Ullah²,

Lee

2016

Journal of Sensors

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The paper focuses on ensuring the quality-of-service (QoS) and quality-of-experience (QoE) requirements of users having heterogeneous devices in a multicast session. QoS parameters such as bit rate, delays, and packet losses are good indicators for optimizing network services but fall short in characterizing user perception (QoE). In N-Screen service, the users have different devices with heterogeneous attributes like screen size, resolution, and access network interface, and the users have different QoE on N-Screen devices with the same QoS parameters. We formulate the objective function of the N-Screen multicast grouping to ensure the minimum user’s QoE with smaller bandwidth requirement. We propose a dynamic user reassignment scheme to maintain and satisfy the QoE by adapting the user’s membership to the varying network conditions. The proposed schemes combine the available bandwidth and multimedia visual quality to ensure the QoS and QoE. In the network architecture, we introduce the functions of the QoS and QoE aware multicast group management and the estimation schemes for the QoS and QoE parameters. The simulation results show that the proposed multicast service ensures the network QoS and guarantees the QoE of users in the varying network conditions.

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“…Fukazawa et al (Fukazawa et al 2009) proposed and evaluated a method that ranks (using Ranking SVM -Support Vector Machine-) the menu functions of a mobile application based on user operation history. Bae et al (Bae, Oh, and Park 2014) proposed an adaptive transformation framework that automatically adjusts the content and the appearance to different devices (different sizes and capabilities).…”

Section: Related Workmentioning

confidence: 99%

A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents

Guardado¹

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Adaptive Transformation for a Scalable User Interface Framework Supporting Multi-screen Services

Cited by 4 publications

References 3 publications

A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major Depression

A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major Depression

QoS and QoE Aware N-Screen Multicast Service

A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents

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