Design of Multimedia Player based on Android (original) (raw)
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Different Approaches for Design of Android based Media Player: A Review
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This paper builds upon the work carried out by Brunel University in the field of "Fast Prototyping And Semiautomated User Interface And Application Generation for Converged Broadcast and Cellular Terminals". This work involved the development of a service creation application for interactive services on mobile devices and methodologies and tools to speed up and deskill the deployment process. This paper aims at further enhancing these tools and presents an enhanced open standards reference platform for mobile digital TV and rich media services. By using a Scalar Vector Graphics (SVG)-driven Java MIDP application (as opposed to bitmapped raster graphics-driven MHP), rich media services can be broadcast to mobile devices running various Java-supported platforms with a user interface scalable to any screen size. Moreover, the Rich Media Mobile Browser is integrated into a service creation tool, therefore enabling rapid testing and deployment of rich mobile media services. The following sections detail the motivation behind the need for a platform which allows for rich media play-out on mobile devices, along with the rich media mobile viewing application and the tools used to create and test rich media with speed and ease.
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This study aims to develop interactive learning media on Android application-based conventional filling systems, find out the level of feasibility and effectiveness of the media as well as knowing the students' responses. This research used development research methods with ADDIE development models and final test results using one group pretest-posttest design. The instruments used are questionnaires and tests. The results of media validation obtained 190 scores from media experts and a score of 339 from material experts. The assessment of media experts and materials experts declared very decent criteria. The research result of students proved to be effective since the average pretest score of 55.2 and the average posttest score of 82.3, the average difference of 27.1 with the completion of the test results achieved 86.7% from 3.3%. The t-test showed the value of t count = 27.85 > t table of 2.045. It means there is a significant difference, the results of the gain test get a...