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Titlebook: Leadership and Nursing; June Girvin Textbook 1998Latest edition June Girvin 1998 development.nursing.Personal

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June Girvinointly with the Symposium on Human Interface (Japan) 2007, the 7th International Conference on Engineering Psychology and Cognitive Ergonomics, the 4th International Conference on Universal Access in Human-Computer Interaction, the 2nd International Conf- ence on Virtual Reality, the 2nd Internation
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June Girvinh the Symposium on Human Interface (Japan) 2007, the 7th International Conference on Engineering Psychology and Cognitive Ergonomics, the 4th International Conference on Universal Access in Human-Computer Interaction, the 2nd International Conf- ence on Virtual Reality, the 2nd International Confere
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June Girvino lower the continuously rising problem of poor medication adherence due to patients misunderstanding what is being instructed on medication labels. Research on pictograms show that their use could increase patients’ comprehension of medication instructions, but the comprehension rates are still low
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June Girvincedure. The goal of story envisioning is to provide intuitive, concrete and consistent visualization contents as interactive drama for storytellers who are not professional at storytelling. We employ graphic recording to symbolize and visualize the stories written in natural language. We built a par
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June Girvine agent (as nodes of its network) is different each other, and exploring how the agents can be promoted to share only correct opinions by preventing to acquire the incorrect opinions in the weighted network. For this purpose, this paper focuses on Autonomous Adaptive Tuning algorithm (AAT) which can
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June Girvine agent (as nodes of its network) is different each other, and exploring how the agents can be promoted to share only correct opinions by preventing to acquire the incorrect opinions in the weighted network. For this purpose, this paper focuses on Autonomous Adaptive Tuning algorithm (AAT) which can
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lso one of the widely research topics. Many tourism recommendation system studies use Collaborative Filtering (CF) method and try to add personality traits to the recommendation system methods to improve the precision. Zhou et al. (2007) suggested that Mass Diffusion (MD) method has more precision t
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