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Aircraft Gearbox Fault Diagnosis System: An Approach based on Deep Learning Techniques
Journal of Intelligent Systems, 2020 Gearbox is one of the vital components in aircraft engines. If any small damage to gearbox, it can cause the breakdown of aircraft engine. Thus it is significant to study fault diagnosis in gearbox system.
Mallikarjuna P B +3 more
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Effect of acute predator stress on learning and memory in a zebrafish model
National Journal of Physiology, Pharmacy and Pharmacology, 2023 Background: In zebrafish, the stress system is represented by the hypothalamo–pituitary–interrenal axis which is similar to human HPA axis. Several studies have reported that stress affects the learning and memory in humans and rodents.
Latha Ramalingam, Vijay Madhaiyan
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THE PSYCHOLINGUISTIC BASIS OF THE LINGUISTIC CONCEPTUALIZATION
Revista de Investigaciones Universidad del Quindío, 2022 The object of this article is the methodology of psycholinguistics concerning analyzing concepts. The article's relevance is due to the need to apply new approaches to linguistic phenomena analysis, for which a purely linguistic methodology is not
Zhao Yuanze +3 more
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Performance optimization for Intrusion Detection by Long Short Term Memory (LSTM) [PDF]
E3S Web of Conferences, 2023 Concerns about cyber threats have emerged as the expansion of system connectivity and the proliferation of system applications intensified in the industry.
Khatkar Monika +8 more
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Parallelizable Stack Long Short-Term Memory [PDF]
Proceedings of the Third Workshop on Structured Prediction for, 2019 Stack Long Short-Term Memory (StackLSTM) is useful for various applications such as parsing and string-to-tree neural machine translation, but it is also known to be notoriously difficult to parallelize for GPU training due to the fact that the computations are dependent on discrete operations.
Shuoyang Ding, Philipp Koehn
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IET Generation, Transmission & Distribution, 2021 Short‐term load forecasting is essential to power systems management. However, most existing forecasting methods fail to fully consider how to rationally integrate the intrinsic time‐related dimensions of electric load data and the decomposition methods ...
Jiehui Huang +4 more
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Bidirectional Long-Short Term Memory for Video Description [PDF]
Proceedings of the 24th ACM international conference on Multimedia, 2016 Video captioning has been attracting broad research attention in multimedia community. However, most existing approaches either ignore temporal information among video frames or just employ local contextual temporal knowledge. In this work, we propose a novel video captioning framework, termed as Bidirectional Long-Short Term Memory (BiLSTM), which ...
Bin, Yi +4 more
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Dependency-based long short term memory network for drug-drug interaction extraction
BMC Bioinformatics, 2017 Background Drug-drug interaction extraction (DDI) needs assistance from automated methods to address the explosively increasing biomedical texts. In recent years, deep neural network based models have been developed to address such needs and they have ...
Wei Wang +5 more
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