Titlebook: Computer Information Systems and Industrial Management; 22nd International C Khalid Saeed,Jiří Dvorský,Makoto Fukumoto Conference proceedin

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Die Boussesche Transportvorrichtung,ature that could enlighten the context factors as well as provide empirical data is still not conclusive, leading to a relevant gap to explore. Specifically in Brazil, previous literature shows the struggles of most companies to establish a solid and sustainable collaboration in their supply chains,

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Die Boussesche Transportvorrichtung,onal institutions have been forced to offer contextualized training programs according to the personal characteristics of the actors. The article presents the results of a research carried out at Barranquilla-Colombia, whose objective was to analyze the relationship between the appropriation of ICT

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https://doi.org/10.1007/978-3-642-50791-5 inquiry in interactive learning environments. Flipped learning turns the classroom into an active learning environment by emphasizing higher order thinking abilities like assessing, analyzing, and producing to involve students in the learning process. It creates a dynamic, interactive learning envi

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Die Boussesche Transportvorrichtung,raction with tourists, generate mobility in the environment and with other users, and provide helpful information about the destination. However, recommender systems applied to tourism tend to focus mainly on the indicator of destination promotion and management, neglecting other competitiveness ind

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/233581.jpg

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Proposal of Earprint Authentication System Considering Pressing Forcecases in which earprints are used to identify criminals. Earprints are still being researched to find out how to use them. Among them, it has been reported that the earprint is deformed by pressing force, but the conventional study of earprint recognition does not consider the pressing force. In the

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Biometric Gait Analysis Using Wrist-Mounted Wearable Sensorsotion sensors located on the right and left wrist. The biometric system presented used input data in the form of accelerometer and gyroscope measurement values. The classifier was trained with fragments of a time series known as gait cycles - periods of time between which the participant touched his

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