Validating the application of occupancy sensor networks for lighting control

We evaluated the performance of the system by training it to recognize 32 material types in both indoor and outdoor environments.Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials.Furthermore, participants’ age, gender and security behavioral intention strongly correlated with how they heard about and shared S&P news-e.g., males more often felt a personal responsibility to share, and older people were less likely to hear about S&P news through conversation.We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment.In this paper, we analyze empirical data on how users (n=12) interact with our VUI calendar system, Discover Cal, over three sessions.In particular, we identify the main obstacle categories and types of tactics our participants employ to overcome them.Through the lens of statistical modeling, we also highlight rich signals in conversational interactions for inferring user satisfaction with the instrumental usage and playful interactions with the agent.These signals can be utilized to develop agents that adapt functionality and interaction styles.

Very few studies exist on what people do to overcome VUI problems they encounter, or how VUIs can be designed to aid people when these problems occur.We analyzed the patterns of how different tactics are used in each obstacle category.We found that while NLP Error obstacles occurred the most, other obstacles are more likely to frustrate or confuse the user.By contrasting these signals, we shed light on the varying functions of conversational interactions.

We discuss design implications for CAs, and directions for developing adaptive agents based on users’ conversational behaviors.In everyday use of CAs, user experience may extend beyond satisfying information needs to the enjoyment of conversations with CAs, some of which represent playful interactions.

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