Monitoring of Domestic Activities Using Multiple Beamformers and Attention Mechanism

Yuki Kaneko; Takeshi Yamada; Shoji Makino

doi:10.2299/jsp.25.239

An Attention Mechanism Extension of Automatic HTML Generation from Web Page Design Images

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.140.1393 ◽

2020 ◽

Vol 140 (12) ◽

pp. 1393-1401

Author(s):

Hiroki Chinen ◽

Hidehiro Ohki ◽

Keiji Gyohten ◽

Toshiya Takami

Keyword(s):

Attention Mechanism ◽

Web Page ◽

Web Page Design ◽

Page Design

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Online Speaker Adaptation for LVCSR Based on Attention Mechanism

2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) ◽

10.23919/apsipa.2018.8659609 ◽

2018 ◽

Cited By ~ 2

Author(s):

Jia Pan ◽

Diyuan Liu ◽

Genshun Wan ◽

Jun Du ◽

Qingfeng Liu ◽

...

Keyword(s):

Attention Mechanism

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Mobile agents' dynamic small-world network based on attention mechanism

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) ◽

10.23919/apnoms50412.2020.9237037 ◽

2020 ◽

Author(s):

Rong Xie

Keyword(s):

Mobile Agents ◽

Small World ◽

Attention Mechanism ◽

Small World Network

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LANGUAGE USE BETWEEN MALE AND FEMALE HOST IN HITAM PUTIH TALK SHOW

LINGUISTIK TERAPAN ◽

10.24114/lt.v14i2.8368 ◽

2018 ◽

Vol 14 (2) ◽

Author(s):

Nurmaliana Sari ◽

Sumarsih Sumarsih ◽

Busmin Gurning

Keyword(s):

Language Use ◽

The Other ◽

Male And Female ◽

Talk Show ◽

Dominant Language ◽

Other Hand ◽

Domestic Activities ◽

Female Host ◽

Negative Connotation ◽

Descriptive Qualitative

This study discusses about language use occurred by male and female host in Hitam Putih talk show. The method of this research is descriptive qualitative. The subjects of this study are male and female host in Hitam Putih talk show. The data are the utterances produced by male and female host in Hitam Putih talk show. This research focuses on the show broadcasted on October 2016 by taking 4 videos randomly. The objective of this study is to describe kinds of the language use uttered by male and female host in Hitam Putih talk show. The findings showed that the kinds of language use consist of 6 parts. The dominant language use uttered by male host is expletive, because male’s utterances are frequently stated in a negative connotation. On the other hand, female host utterances are found in specialized vocabulary as the most dominant because female host has more interest in talking family affairs, such as the education of children, clothes, cooking, and fashion, etc. Women also tended to talk about one thing related to the home and domestic activities. However, the representation of language use uttered by male and female are deficit, dominance and different. Keywords: Language Use, Gender, Talk Show

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A New Time-Frequency Attention Mechanism for TDNN and CNN-LSTM-TDNN, with Application to Language Identification

10.21437/interspeech.2019-1256 ◽

2019 ◽

Cited By ~ 3

Author(s):

Xiaoxiao Miao ◽

Ian McLoughlin ◽

Yonghong Yan

Keyword(s):

Attention Mechanism ◽

Language Identification ◽

Time Frequency ◽

New Time

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Dam Deformation Interpretation and Prediction Based on a Long Short-Term Memory Model Coupled with an Attention Mechanism

Applied Sciences ◽

10.3390/app11146625 ◽

2021 ◽

Vol 11 (14) ◽

pp. 6625

Author(s):

Yan Su ◽

Kailiang Weng ◽

Chuan Lin ◽

Zeqin Chen

Keyword(s):

Short Term Memory ◽

Attention Mechanism ◽

Impact Factors ◽

Nonlinear Prediction ◽

Time Dimension ◽

Short Term ◽

Deformation Prediction ◽

Term Memory ◽

Long Short Term Memory ◽

Dam Deformation

An accurate dam deformation prediction model is vital to a dam safety monitoring system, as it helps assess and manage dam risks. Most traditional dam deformation prediction algorithms ignore the interpretation and evaluation of variables and lack qualitative measures. This paper proposes a data processing framework that uses a long short-term memory (LSTM) model coupled with an attention mechanism to predict the deformation response of a dam structure. First, the random forest (RF) model is introduced to assess the relative importance of impact factors and screen input variables. Secondly, the density-based spatial clustering of applications with noise (DBSCAN) method is used to identify and filter the equipment based abnormal values to reduce the random error in the measurements. Finally, the coupled model is used to focus on important factors in the time dimension in order to obtain more accurate nonlinear prediction results. The results of the case study show that, of all tested methods, the proposed coupled method performed best. In addition, it was found that temperature and water level both have significant impacts on dam deformation and can serve as reliable metrics for dam management.

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