A new camera-based support system aims to help visually impaired or blind people find and stay on tactile paving paths. If an obstacle on the tactile paving is detected, the system warns the user through earphones. The number of visually impaired people in the world is likely to increase in the near future because of the rapidly aging population. Many challenges remain unsolved in currently available options, which results in limited applicability, researchers say. The system consists of a forward-facing depth camera worn around the chest that is connected to a small microcomputer board.
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Graphs are useful theoretical representations of the connections between groups of entities. They have been used for a variety of purposes in data science, from ranking web pages by popularity to mapping out social networks. In many cases, such applications require the processing of graphs containing hundreds of billions of edges. The proposed model, Adaptive Massively Parallel Computation (AMPC), augments the theoretical capabilities of MapReduce providing a pathway to solve many graph problems in fewer computation rounds.
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The Knowledge Graph appears to be based on a data-lake approach rather than the data-river approach of today's core algorithm. Any individual entity can see its confidence score increase or decrease on any day, whether there is an update or not. The fact that entities change and move between these major updates and the fact that the updates appear to be converging suggests that we aren't far from a Knowledge Graph algorithm that works on fresh data rivers.
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A new proof says guessing is sometimes the best way to solve systems of linear equations. It's the first method capable of surpassing a hard limit on how quickly some problems can be solved. linear systems involve two or more equations with variables that relate to each other. The new method was posted online in July and presented in January at an algorithm conference. It won the best-paper award at the ACM-SIAM Symposium on Discrete Algorithms in New York. "Now we have a proof that we can go faster," Mark Giesbrecht of the University of Waterloo says of the new method. .
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