17,994 research outputs found
Real-time Recognition of Interleaved Activities based on Ensemble of LSTM and Fuzzy Temporal Windows
In this paper, we present a methodology for Real-Time Activity Recognition of Interleaved Activities based on Fuzzy Logic and Recurrent Neural Networks. Firstly, we propose a representation of binary-sensor activations based on multiple Fuzzy Temporal Windows. Secondly, an ensemble of activity-based classifiers for balanced training and selection of relevant sensors is proposed. Each classifier is configured as a Long Short-Term Memory with self-reliant detection of interleaved activities. The proposed approach was evaluated using well-known interleaved binary-sensor datasets comprised of activities of daily living
Effect of virtual memory on efficient solution of two model problems
Computers with virtual memory architecture allow programs to be written as if they were small enough to be contained in memory. Two types of problems are investigated to show that this luxury can lead to quite an inefficient performance if the programmer does not interact strongly with the characteristics of the operating system when developing the program. The two problems considered are the simultaneous solutions of a large linear system of equations by Gaussian elimination and a model three-dimensional finite-difference problem. The Control Data STAR-100 computer runs are made to demonstrate the inefficiencies of programming the problems in the manner one would naturally do if the problems were indeed, small enough to be contained in memory. Program redesigns are presented which achieve large improvements in performance through changes in the computational procedure and the data base arrangement
What is the functional role of adult neurogenesis in the hippocampus?
The dentate gyrus is part of the hippocampal memory system and special in
that it generates new neurons throughout life. Here we discuss the
question of what the functional role of these new neurons might be. Our
hypothesis is that they help the dentate gyrus to avoid the problem of
catastrophic interference when adapting to new environments. We assume
that old neurons are rather stable and preserve an optimal encoding
learned for known environments while new neurons are plastic to adapt to
those features that are qualitatively new in a new environment. A simple
network simulation demonstrates that adding new plastic neurons is indeed
a successful strategy for adaptation without catastrophic interference
Domain-general and Domain-specific Patterns of Activity Support Metacognition in Human Prefrontal Cortex
Metacognition is the capacity to evaluate the success of one's own cognitive processes in various domains; for example, memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks or if self-evaluative processes are domain specific. Here, we investigated this issue directly by examining the neural substrates engaged when metacognitive judgments were made by human participants of both sexes during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing patterns of fMRI activity while subjects evaluated their performance, we revealed both domain-specific and domain-general metacognitive representations. Multivoxel activity patterns in anterior prefrontal cortex predicted levels of confidence in a domain-specific fashion, whereas domain-general signals predicting confidence and accuracy were found in a widespread network in the frontal and posterior midline. The demonstration of domain-specific metacognitive representations suggests the presence of a content-rich mechanism available to introspection and cognitive control
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