Multi-step temperature prediction model based on surrounding cities and long-term memory neural networks

Author(s):  
Zhenyue Huang ◽  
Lei Zhang ◽  
Xiajiong Shen ◽  
Liyang Hou ◽  
Yihua Gao ◽  
...  
2020 ◽  
Vol 44 (3) ◽  
pp. 326-332
Author(s):  
Audreaiona Waters ◽  
Liye Zou ◽  
Myungjin Jung ◽  
Qian Yu ◽  
Jingyuan Lin ◽  
...  

Objective: Sustained attention is critical for various activities of daily living, including engaging in health-enhancing behaviors and inhibition of health compromising behaviors. Sustained attention activates neural networks involved in episodic memory function, a critical cognition for healthy living. Acute exercise has been shown to activate these same neural networks. Thus, it is plausible that engaging in a sustained attention task and engaging in a bout of acute exercise may have an additive effect in enhancing memory function, which was the purpose of this experiment. Methods: 23 young adults (Mage = 20.7 years) completed 2 visits, with each visit occurring approximately 24 hours apart, in a counterbalanced order, including: (1) acute exercise with sustained attention, and (2) sustained attention only. Memory was assessed using a word-list paradigm and included a short- and long-term memory assessment. Sustained attention was induced via a sustained attention to response task (SART). Acute exercise involved a 15-minute bout of moderate-intensity exercise. Results: Short-term memory performance was significantly greater than long-term memory, Mdiff = 1.86, p < .001, and short-term memory for Exercise with Sustained Attention was significantly greater than short-term memory for Sustained Attention Only, Mdiff = 1.50, p = .01. Conclusion: Engaging in an acute bout of exercise before a sustained attention task additively influenced short-term memory function.


2019 ◽  
Vol 29 (06) ◽  
pp. 1850053 ◽  
Author(s):  
Richard J. Duro ◽  
Jose A. Becerra ◽  
Juan Monroy ◽  
Francisco Bellas

In the framework of open-ended learning cognitive architectures for robots, this paper deals with the design of a Long-Term Memory (LTM) structure that can accommodate the progressive acquisition of experience-based decision capabilities, or what different authors call “automation” of what is learnt, as a complementary system to more common prospective functions. The LTM proposed here provides for a relational storage of knowledge nuggets given the form of artificial neural networks (ANNs) that is representative of the contexts in which they are relevant in a configural associative structure. It also addresses the problem of continuous perceptual spaces and the task- and context-related generalization or categorization of perceptions in an autonomous manner within the embodied sensorimotor apparatus of the robot. These issues are analyzed and a solution is proposed through the introduction of two new types of knowledge nuggets: P-nodes representing perceptual classes and C-nodes representing contexts. The approach is studied and its performance evaluated through its implementation and application to a real robotic experiment.


2021 ◽  
Vol 23 (4) ◽  
pp. 042001
Author(s):  
Yongwen Zhang ◽  
Dong Zhou ◽  
Jingfang Fan ◽  
Warner Marzocchi ◽  
Yosef Ashkenazy ◽  
...  

Philosophies ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 39 ◽  
Author(s):  
Trond A. Tjøstheim ◽  
Andreas Stephens ◽  
Andrey Anikin ◽  
Arthur Schwaninger

Numerous species use different forms of communication in order to successfully interact in their respective environment. This article seeks to elucidate limitations of the classical conduit metaphor by investigating communication from the perspectives of biology and artificial neural networks. First, communication is a biological natural phenomenon, found to be fruitfully grounded in an organism’s embodied structures and memory system, where specific abilities are tied to procedural, semantic, and episodic long-term memory as well as to working memory. Second, the account explicates differences between non-verbal and verbal communication and shows how artificial neural networks can communicate by means of ontologically non-committal modelling. This approach enables new perspectives of communication to emerge regarding both sender and receiver. It is further shown that communication features gradient properties that are plausibly divided into a reflexive and a reflective form, parallel to knowledge and reflection.


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