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Pay Attention: Leveraging Sequence Models to Predict the Useful Life of Batteries [article]

Samuel Paradis, Michael Whitmeyer
2019 arXiv   pre-print
We use data on 124 batteries released by Stanford University to first try to solve the binary classification problem of determining if a battery is "good" or "bad" given only the first 5 cycles of data  ...  We approach the problem from a purely data-driven standpoint, hoping to use deep learning to learn the patterns in the sequences of data that the Stanford team engineered by hand.  ...  Note-Our final model, which leveraged an LSTM and Attention to process the sequential data, compares to Severson et al. (2019)s state of the art model on a held out test set of 20 batteries.  ... 
arXiv:1910.01347v2 fatcat:ygwt4efdsncynccqfrxvo3wtk4

Optimal Battery Control Under Cycle Aging Mechanisms in Pay for Performance Settings [article]

Yuanyuan Shi and Bolun Xu and Yushi Tan and Daniel Kirschen and Baosen Zhang
2018 arXiv   pre-print
We study the optimal control of battery energy storage under a general "pay-for-performance" setup such as providing frequency regulation and renewable integration.  ...  In particular, we present an electrochemically accurate and trackable battery degradation model called the rainflow cycle-based model. We prove the degradation cost is convex.  ...  Battery Degradation Cost After counting the cycles, a cycle depth stress function Φ(u) is used to model the life loss from a single cycle of depth u measured in terms of (normalized) changes in the SoC  ... 
arXiv:1709.05715v4 fatcat:cf3ni43uv5gj3d4tg3qe5dapee

MemX: An Attention-Aware Smart Eyewear System for Personalized Moment Auto-capture [article]

Yuhu Chang, Yingying Zhao, Mingzhi Dong, Yujiang Wang, Yutian Lu, Qin Lv, Robert P. Dick, Tun Lu, Ning Gu, Li Shang
2021 arXiv   pre-print
MemX captures human visual attention on the fly, analyzes the salient visual content, and records moments of personal interest in the form of compact video snippets.  ...  Using the YouTube-VIS dataset and 30 participants, we experimentally show that MemX significantly improves the attention tracking accuracy over the eye-tracking-alone method, while maintaining high system  ...  of interest, and FP (false positive) denotes when MemX incorrectly identifies an object of interest that the user actually did not pay attention to.  ... 
arXiv:2105.00916v1 fatcat:rzuvr6rehjhqljlc25omdotthq

Hierarchical Attention Based Position-Aware Network for Aspect-Level Sentiment Analysis

Lishuang Li, Yang Liu, AnQiao Zhou
2018 Proceedings of the 22nd Conference on Computational Natural Language Learning  
On this basis, we also propose a succinct hierarchical attention based mechanism to fuse the information of targets and the contextual words.  ...  Therefore, we propose a hierarchical attention based position-aware network (HAPN), which introduces position embeddings to learn the position-aware representations of sentences and further generate the  ...  Acknowledgments This paper is supported by the National Natural Science Foundation of China under NO.61672126. We thank anonymous reviewers for their valuable comments.  ... 
doi:10.18653/v1/k18-1018 dblp:conf/conll/LiLZ18 fatcat:iapqzln6bzdkxoqsydxky5j4yy

Simultaneous Pickup and Delivery Traveling Salesman Problem considering the Express Lockers Using Attention Route Planning Network

Yu Du, Shaochuan Fu, Changxiang Lu, Qiang Zhou, Chunfang Li, Carmen De Maio
2021 Computational Intelligence and Neuroscience  
A modified deep Q-learning network is designed to get the optimal results from our model, leveraging masked multi-head attention to select the courier paths.  ...  This paper presents a simultaneous pickup and delivery route designing model, which considers the use of express lockers.  ...  Here, we use the multihead attention model from the transformer. e attention mechanism forces the model to pay more attention to nodes with higher weights. e multihead attention further introduces masks  ... 
doi:10.1155/2021/5590758 pmid:34122533 pmcid:PMC8166504 fatcat:m6ahwdsvrneije43edbmtrn22a

The Role of Gender in Promotion and Pay over a Career

John T. Addison, Orgul Demet Ozturk, Si Wang
2014 Journal of Human Capital  
In its use of three career stages, the study builds on earlier work using the NLSY79 that considers gender differences in the early career years alone.  ...  Using data from the National Longitudinal Survey of Youth (NLSY79), this paper considers the role of gender in promotion and subsequent earnings development and how this evolves over a career.  ...  Another model, now paying explicit attention to gender differences, has exploited the idea that equal-ability women have better alternatives to market work than their male counterparts.  ... 
doi:10.1086/677942 fatcat:b7icoism4ne77ou63uiofp62iq

H.264 Sensor Aided Video Encoder for UAV BLOS Missions [chapter]

Cesario Vincenzo Angelino, Luca Cicala, Marco De Mizio, Paolo Leoncini, E. Baccaglini, M. Gavelli, N. Raimondo, R. Scopigno
2013 Lecture Notes in Computer Science  
The encoder employs a new motion estimation scheme which make use of the global motion information provided by the onboard navigation system.  ...  The results are relevant in low frame rate video coding, which is a typical scenario in UAV behind line-of-sight (BLOS) missions.  ...  No particular attention has been payed in previous works to low overlap frame sequences and BLOS applications.  ... 
doi:10.1007/978-3-642-41184-7_76 fatcat:ipc7an2vyjcwbeuylzplli72du

Empowering Commercial Vehicles through Data-Driven Methodologies

Paolo Bethaz, Sara Cavaglion, Sofia Cricelli, Elena Liore, Emanuele Manfredi, Stefano Salio, Andrea Regalia, Fabrizio Conicella, Salvatore Greco, Tania Cerquitelli
2021 Electronics  
We discussed performance of TETRAPAC in two real-life settings related to trucks.  ...  In this paper, we focus on analyzing data collected from heavy trucks during their use, a relevant task for companies due to the high commercial value of the monitored vehicle.  ...  Acknowledgments: Thanks to Valentina Diaferio (Accenture S.p.A.) for taking care of the graphic part of Figure 1 . Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics10192381 doaj:9e9fb2a3cb264d78b359c5342ea4d482 fatcat:tki2mkjvbvchtanctjo57dyjim

Sentiment Classification towards Question-Answering with Hierarchical Matching Network

Chenlin Shen, Changlong Sun, Jingjing Wang, Yangyang Kang, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Finally, we characterize the importance of the generated matching vectors via a selfmatching attention layer.  ...  Then, by leveraging a QA bidirectional matching layer, the proposed approach can learn the matching vectors of each [Q-sentence, A-sentence] unit.  ...  Acknowledgments We would like to thank the anonymous reviewers for their valuable comments.  ... 
doi:10.18653/v1/d18-1401 dblp:conf/emnlp/ShenSWKLLSZZ18 fatcat:3e4qt7qiwvgrtm2dwlzkrsglyq

The life cycle of an organization in a changing economic environment

Evgeniya Eliseeva, Angela Mottaeva, V. Breskich, S. Uvarova
2021 E3S Web of Conferences  
The concept of "life cycle" is used by an organization to plan a certain sequence of changes in the current state and maintain its position in the market in the future.  ...  In the theory of the life cycle of the organization's position in the market, it is emphasized that the development of an enterprise occurs according to an algorithm common to all organizations.  ...  Organizations pay more attention to the adopted main indicators of the analyzed period, but do not trace them in the dynamics of the life cycle activities.  ... 
doi:10.1051/e3sconf/202124410028 fatcat:onobptuepza4pk6qil2dg5qhpi

Automating App Review Response Generation Based on Contextual Knowledge [article]

Cuiyun Gao, Wenjie Zhou, Xin Xia, David Lo, Qi Xie, Michael R. Lyu
2020 arXiv   pre-print
Experiments on practical review data show that CoRe can outperform the state-of-the-art method by 11.53% in terms of BLEU-4, an accuracy metric that is widely used to evaluate text generation systems.  ...  Accurately responding to the app reviews is one of the ways to relieve user concerns and thus improve user experience.  ...  battery life .  ... 
arXiv:2010.06301v1 fatcat:5phg5xqk5vdxrkm62opuwr2vay

TNT-KID: Transformer-based Neural Tagger for Keyword Identification [article]

Matej Martinc, Blaž Škrlj, Senja Pollak
2020 arXiv   pre-print
By adapting the transformer architecture for a specific task at hand and leveraging language model pretraining on a domain specific corpus, the model is capable of overcoming deficiencies of both supervised  ...  This study also offers thorough error analysis with valuable insights into the inner workings of the model and an ablation study measuring the influence of specific components of the keyword identification  ...  The authors acknowledge also the financial support from the Slovenian Research Agency for research core funding for the programme Knowledge Technologies (No.  ... 
arXiv:2003.09166v2 fatcat:dqacyazwnvcqhf5d7y6gjr2gl4

E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce [article]

Denghui Zhang, Zixuan Yuan, Yanchi Liu, Fuzhen Zhuang, Haifeng Chen, Hui Xiong
2021 arXiv   pre-print
On the other hand, product-level knowledge like product associations can enhance the language modeling of E-commerce, but they are not factual knowledge thus using them indiscriminately may introduce noise  ...  To utilize product-level knowledge, we introduce Neighbor Product Reconstruction, which trains E-BERT to predict a product's associated neighbors with a denoising cross attention layer.  ...  The cross attention layer enables the model to ing to select noun phrases for masking, our phrase pool is pay more/less attention to different positions of the content  ... 
arXiv:2009.02835v3 fatcat:w4p4ldnwd5g3tomjiqdw5ndkla

Detecting Attended Visual Targets in Video [article]

Eunji Chong, Yongxin Wang, Nataniel Ruiz, James M. Rehg
2020 arXiv   pre-print
In addition, we apply our predicted attention maps to two social gaze behavior recognition tasks, and show that the resulting classifiers significantly outperform existing methods.  ...  We address the problem of detecting attention targets in video.  ...  The toddler dataset used in Sec. 5.3 was collected and annotated under the direction of Agata Rozga, Rebecca Jones, Audrey Southerland, and Elysha Clark-Whitney.  ... 
arXiv:2003.02501v2 fatcat:72jamucspnb3hpthu2zdqz77bq

Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition [article]

Alessio Burrello, Francesco Bianco Morghet, Moritz Scherer, Simone Benatti, Luca Benini, Enrico Macii, Massimo Poncino, Daniele Jahier Pagliari
2022 arXiv   pre-print
To tackle this challenge, complex neural networks are employed, which require large memory footprints, consume relatively high energy and limit the maximum battery life of devices used for classification  ...  This new family of ultra-small attention-based architectures approaches state-of-the-art performance while reducing the number of parameters and operations of 4.9X.  ...  of the target task (i.e., paying "more attention" to the most important inputs).  ... 
arXiv:2203.12932v2 fatcat:dzcwjs5aqjb67iea72ekrvycg4
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