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Context-aware ubiquitous learning is a promising way to learn languages; however, it requires developers and operators of much effort to construct, deploy, and use the specialized system. As its alternative, this paper proposes movie based context-aware language learning (MBCALL) that enables learners to learn languages through quizzes generated along virtual contexts occurring in the movie to be replayed. Since full automatic context capturing from the movie is impossible, the authors define an object-oriented context model (OOCM) and also a textual context description language subject to the OOCM to describe the movie context easily by human work. The OOCM introduces the case grammar concept of natural language processing. This enables quiz generation based on types of the words for objects, actions, and modes found in the movie. Evaluation with a small movie by three subjects shows that the OOCM can guide them to enrich information included in the movie context; therefore, we can generate more types of quizzes based on the movie context.

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Arrangement patient’s report process of Elim Rantepao hospital is especially complicated because patient data was obtained from FCR Console Prima what saved as DDO file extension as Unicode string. This problem makes understanding and select data manually become difficult. This research tries to give a solution on how to arrange reports easily through application tools developing. This research uses a rule-based classification algorithm to extract Patient Name, Age, ID Number, Date, and time. Applying this algorithm, increase system performance up to 96,6%. This application is very accurate as long as the file DDO has not broken.