Background: For the past few years, scientific controversy has surrounded the large number of errors in forensic and literature mitochondrial DNA (mtDNA) data. However, recent research has shown that using mtDNA phylogeny and referring to known mtDNA haplotypes can be useful for checking the quality of sequence data.
Abstract. The notable developments in pervasive and wireless technology enable us to collect enormous sensor data from each individual. With contextaware technologies, these data can be summarized into context data which support each individual's reflection process of one's own memory and communication process between the individuals. To improve reflection and communication, this paper proposes an automatic cartoon generation method for fun. Cartoon is a suitable medium for the reflection and the communication of one's own memory, especially for the emotional part. By considering the fun when generating cartoons, the advantage of the cartoon can be boosted. For the funnier cartoon, diversity and consistency are considered during the cartoon generation. For the automated generation of diverse and consistent cartoon, context data which represent the user's behavioral and mental status are exploited. From these context information and predefined user profile, the similarity between context and cartoon image is calculated. The cartoon image with high similarity is selected to be merged into cartoon cuts. Selected cartoon cuts are arranged with the constraints for the consistency of cartoon story. To evaluate the diversity and consistency of the proposed method, several operational examples are employed.
Recent home theater system requires for users to control various devices such as TV, audio equipment, DVD and video players, and set-top box simultaneously. To obtain the services that a user wants in this situation, user should know the functions and positions of the buttons in several remote controllers. Since it is usually difficult to manipulate them and the number of the devices that we can control increases, we get to confuse more as the ubiquitous home environment is realized. Moreover, there are a lot of mobile and stationary controller devices in ubiquitous computing environment, so that user interface should be adaptive in selecting the functions that user wants and in adjusting the features of UI to fit in a specific controller. To implement the user and controller adaptive interface, we model the ubiquitous home environment and use the modeled context and device information. We have used Bayesian network to get the degree of necessity in each situation. Action selection network uses predicted user situation and necessary devices, and it selects necessary functions in current situation. Selected functions are used to construct adaptive interface for each controller using presentation template. For experiments, we have implemented ubiquitous home environment and generated controller usage log in this environment. We have confirmed the BN predicted user requirements effectively as evaluating the inferred results of controller necessity based on generated scenario. Finally, comparing the adaptive home UI with the fixed one by 14 subjects, we confirm that the generated adaptive UI is more useful for general tasks than the fixed UI.
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