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Title: A New Attention Mechanism to Classify Multivariate Time Series

Classifying multivariate time series (MTS), which record the values of multiple variables over a continuous period of time, has gained a lot of attention. However, existing techniques suffer from two major issues. First, the long-range dependencies of the time-series sequences are not well captured. Second, the interactions of multiple variables are generally not represented in features. To address these aforementioned issues, we propose a novel Cross Attention Stabilized Fully Convolutional Neural Network (CA-SFCN) to classify MTS data. First, we introduce a temporal attention mechanism to extract long- and short-term memories across all time steps. Second, variable attention is designed to select relevant variables at each time step. CA-SFCN is compared with 16 approaches using 14 different MTS datasets. The extensive experimental results show that the CA-SFCN outperforms state-of-the-art classification methods, and the cross attention mechanism achieves better performance than other attention mechanisms.

 
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Award ID(s):
1757207 1633330 1914635
NSF-PAR ID:
10177556
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Page Range / eLocation ID:
1999 to 2005
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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We soon realized that we needed to broaden our focus to capture a variety of prefabricated building methods that are often colloquially or idiomatically referred to as “modular.” This included a range of prefabricated building systems (e.g., manufactured, volumetric modular, system-built, and Quonset huts and other reused military buildings[2]). Our further questions about prefabricated housing in the region became the basis for this annotated bibliography. Thus, while this bibliography is one of multiple methods used to investigate these issues, it played a significant role in guiding our research and helped us bring together the diverse perspectives we were hearing from our interviews with building experts in the region and the wider debates that were circulating in the media and, to a lesser degree, in academia. 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The program aims to create an all-inclusive high school level engineering course(s), a professional development platform, and a learning community to support student pathways to higher education institutions. An introductory engineering course was developed and professional development was provided to nine high school teachers to instruct and assess engineering learning during the first year of the project. This study investigates participating teachers’ implementation of the course in high schools across the nation to understand the extent to which their experiences vary as a function of student demographic (race, ethnicity, socioeconomic status) and resource level of the school itself. Analysis of these experiences was undertaken using a collective case-study approach (Creswell, 2013) involving in-depth analysis of a limited number of cases “to focus on fewer "subjects," but more "variables" within each subject” (Campbell & Ahrens, 1998, p. 541). 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