Research and Design of a Real-Time Interactive Application Development Model Based on the Android Platform

Author(s):  
Zhilong Yang ◽  
Yong Wang ◽  
Yongquan Yang ◽  
Zhiqiang Wei
Author(s):  
Andito Haryo Saputro

<div align="center"><table width="627" border="0" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="627"><p>This study aims to create an interactive application of beginning counting with Montessori method that appropriate to apply as a source of learning in Pustaka Arridho kindergarten and know the appropriateness of interactive applications made</p><p>The research method used in this research is Research and Development (RnD) using ADDIE development model adapted from Lee &amp; Owens. The development model is divided into 5 stages: Analysis, Design, Development, Implementation, and Evaluation. In the development stage, RAD (Rapid Application Development) method is used. Interview methods, literature methods, and instrument methods is used in collecting data. Further, interactive applications validated or assessed by media experts and material experts.</p><p>The results showed that interactive applications on the lesson of beginning counting successfully created. That divided into 3 parts, that is knowing numbers, sorting numbers, and counting with numbers. Based on the results of the validation of interactive applications, the percentage of interactive applications appropriateness was obtained 96.6% of material experts, and 94.7% of media experts. This shows that the interactive applications that have been developed can be used as learning resources or learning media of beginning counting.</p></td></tr><tr><td valign="top" width="627"><p><strong>Keywords :</strong> Interactive Application, Beginning Counting, Montessori Method.</p></td></tr></tbody></table></div>


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4141
Author(s):  
Wouter Houtman ◽  
Gosse Bijlenga ◽  
Elena Torta ◽  
René van de Molengraft

For robots to execute their navigation tasks both fast and safely in the presence of humans, it is necessary to make predictions about the route those humans intend to follow. Within this work, a model-based method is proposed that relates human motion behavior perceived from RGBD input to the constraints imposed by the environment by considering typical human routing alternatives. Multiple hypotheses about routing options of a human towards local semantic goal locations are created and validated, including explicit collision avoidance routes. It is demonstrated, with real-time, real-life experiments, that a coarse discretization based on the semantics of the environment suffices to make a proper distinction between a person going, for example, to the left or the right on an intersection. As such, a scalable and explainable solution is presented, which is suitable for incorporation within navigation algorithms.


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