71 research outputs found
8 Methods to generate Electricity efficiently (Pollution free)
Volume 7 Issue 11 (November 201
Wireless ARM based Automated System for Geriatrics
This paper is an attempt to presentWireless ARM based automated system with extended range of Bluetooth, keeping in mind the low cost factor while conceiving the design having a user friendly interface and easy installation process enabling user to control the various home appliances in the connected cluster/s in a comfortable manner.The target customers are geriatrics who needs special attention.
DOI: 10.17762/ijritcc2321-8169.15085
Wearable Internet of Things Medical Alert Device with Fall Detection and Real Time Posture Monitoring
This paper presents an overview about inexpensive fall sensor design. Impact of falls cannot be determined, if there is an aid which can call for help under this circumstances it would be of great help to the person in distress and we are trying to build this aid
Intrinsically motivated graph exploration using network theories of human curiosity
Intrinsically motivated exploration has proven useful for reinforcement
learning, even without additional extrinsic rewards. When the environment is
naturally represented as a graph, how to guide exploration best remains an open
question. In this work, we propose a novel approach for exploring
graph-structured data motivated by two theories of human curiosity: the
information gap theory and the compression progress theory. The theories view
curiosity as an intrinsic motivation to optimize for topological features of
subgraphs induced by the visited nodes in the environment. We use these
proposed features as rewards for graph neural-network-based reinforcement
learning. On multiple classes of synthetically generated graphs, we find that
trained agents generalize to larger environments and to longer exploratory
walks than are seen during training. Our method computes more efficiently than
the greedy evaluation of the relevant topological properties. The proposed
intrinsic motivations bear particular relevance for recommender systems. We
demonstrate that curiosity-based recommendations are more predictive of human
behavior than PageRank centrality for several real-world graph datasets,
including MovieLens, Amazon Books, and Wikispeedia.Comment: 14 pages, 5 figures in main text, and 15 pages, 8 figures in
supplemen
- …