Previous studies on sequence-based extraction of human movement trajectories have an issue of inadequate trajectory representation. Specifically, a pair of locations may not be lined up in a sequence especially when one location includes the other geographically. In this study, we propose a graph representation that retains information on the geographic hierarchy as well as the temporal order of visited locations, and have constructed a benchmark dataset for graph-structured trajectory extraction. The experiments with our baselines have demonstrated that it is possible to accurately predict visited locations and the order among them, but it remains a challenge to predict the hierarchical relations.

In this paper, we present a deep learning-based framework for solving geometric construction problems through visual reasoning, which is useful for automated geometry theorem proving. Constructible problems in geometry often ask for the sequence of straightedge-and-compass constructions to construct a given goal given some initial setup. Our EuclidNet framework leverages the neural network architecture Mask R-CNN to extract the visual features from the initial setup and goal configuration with extra points of intersection, and then generate possible construction steps as intermediary data models that are used as feedback in the training process for further refinement of the construction step sequence. This process is repeated recursively until either a solution is found, in which case we backtrack the path for a step-by-step construction guide, or the problem is identified as unsolvable. Our EuclidNet framework is validated on complex Japanese Sangaku geometry problems, demonstrating its capacity to leverage backtracking for deep visual reasoning of challenging problems.

The first sports robot which Tanaka created, was one that reproduced particular techniques found in Japanese martial arts. Traditional Japanese martial arts feature a variety of body control exercises, within which exist some truly amazing techniques. One such technique allows you to "defeat your opponent without having to use any force at all." During his time studying for his postgraduate degree, Tanaka met Kunihiro Ogata - a senior member of the Intelligent Systems and Informatics Laboratory (currently at the National Institute of Advanced Industrial Science and Technology). After studying these martial arts, Ogata decided to incorporate motion-capture technology in an attempt to measure and scientifically analyze the body control exercises found in martial arts.The aim was to see if he could gain some clear understanding of the principles behind these techniques and discover if they could be incorporated into the design and manipulation of robots.

When the current emperor steps down in April next year, the Japanese calendar will move into a new era - and it could cause havoc with the country's computer systems. The calendar is based on era names that coincide with the rule of its emperors, and the country has been in the Heisei or'peace everywhere' era since Japan's current emperor, Akihito, took the throne in 1989. However, he is is set to step down on April 30, 2019. Japan's Emperor Akihito, took the throne in 1989. However, he is is set to step down on April 30, 2019.to: