The fatality index of public transport (express bus) in Malaysia

NI

A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

Rapid advancement of technology and their increasing affordability have transformed mobile devices from a means of communication to tools for socialization, entertainment, work and learning. However, advancement of battery technology and capacity is slow compared to energy need. Viewing content with high quality of experience will consume high power. In limited available energy, normal content adaptation system will decrease the content quality, hence reducing quality of experience. However, there is a need for optimizing content quality of experience (QoE) in a limited available energy. With modification and improvement, content adaptation may solve this issue. The key objective of this research is to propose a framework for energy-aware video content adaptation system to enable video delivery over the Internet. To optimise the QoE while viewing streaming video on a limited available smartphone energy, an algorithm for energy-aware video content adaptation decision-taking engine named EnVADE is proposed. The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. Thus, QoE can be improved. To evaluate EnVADE algorithm in term of energy efficiency, an experimental evaluation has been done. Subjective evaluation by selected respondents are also has been made using Absolute Category Rating method as recommended by ITU to evaluate EnVADE algorithm in term of QoE. In both evaluation, comparison with other methods has been made. The results show that the proposed solution is able to increase the viewing time of about 14% compared to MPEG-DASH which is an official international standard and widely used streaming method. In term of QoE subjective test, EnVADE algorithm score surpasses the score of other video streaming method. Therefore, EnVADE framework and algorithm has proven its capability as an alternative technique to stream video content with higher QoE and lower energy consumption

Distributed Content Adaptation for Pervasive Systems

International audiencePervasive systems are created by introducing wireless communication into distributed multimedia systems. These systems facilitate mobile data access to applications such as health care, tourism and emergency. However new challenges have emerged that has not been adequately addressed in traditional distributed multimedia systems. In pervasive systems, data must be adapted to the user's preferences, device capabilities and network conditions. Several content adaptation techniques have been proposed to fit the data to the usage environment. In this paper we present a distributed content adaptation framework (DCAF) for distributed multimedia systems and its prototype implementation. The architecture takes into consideration client profile, network conditions, content profile (meta-data) and available adaptation services (third party software elements) to construct an optimal dynamic adaptation graph