Results 11 to 20 of about 1,496,086 (365)
Design and Evaluation of a Rack-Scale Disaggregated Memory Architecture For Data Centers [PDF]
, 2023 Memory disaggregation is being considered as a strong alternative to traditional architecture to deal with the memory under-utilization in data centers. Disaggregated memory can adapt to dynamically changing memory requirements for the data center applications like data analytics, big data, etc., that require in-memory processing. However, such systems
arxiv +1 more source
A Study on Difference in Short-Term Memory in Healthy Males and Females of Kerala
Journal of Nobel Medical College, 2013 Journal of Nobel Medical College Vol.
Sailesh Sai Kumar +2 more
doaj +1 more source
Intrusion detection systems using long short-term memory (LSTM)
Journal of Big Data, 2021 An intrusion detection system (IDS) is a device or software application that monitors a network for malicious activity or policy violations. It scans a network or a system for a harmful activity or security breaching. IDS protects networks (Network-based
FatimaEzzahra Laghrissi +3 more
semanticscholar +1 more source
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
doaj +1 more source
Simple and Complex Working Memory Tasks Allow Similar Benefits of Information Compression
Journal of Cognition, 2018 Complex working memory span tasks were designed to engage multiple aspects of working memory and impose interleaved processing demands that limit the use of mnemonic strategies, such as chunking.
Fabien Mathy +2 more
doaj +1 more source
A long short‐term memory‐based model for greenhouse climate prediction
International Journal of Intelligent Systems, 2021 Greenhouses can grow many off‐season vegetables and fruits, which improves people's quality of life. Greenhouses can also help crops resist natural disasters and ensure the stable growth of crops.
Yuwen Liu +8 more
semanticscholar +1 more source
Quantum Long Short-Term Memory [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020 Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established. In this work, we propose a hybrid quantum-classical model of LSTM, which
Samuel Yen-Chi Chen +2 more
semanticscholar +1 more source
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
doaj +1 more source
Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
Annual Meeting of the Association for Computational Linguistics, 2016 Relation classification is an important semantic processing task in the field of natural language processing (NLP). State-ofthe-art systems still rely on lexical resources such as WordNet or NLP systems like dependency parser and named entity recognizers
P. Zhou +6 more
semanticscholar +1 more source
Conceptual Short Term Memory in perception and thought
Frontiers in Psychology, 2012 Conceptual short term memory (CSTM) is a theoretical construct that provides one answer to the question of how perceptual and conceptual processes are related. CSTM is a mental buffer and processor in which current perceptual stimuli and their associated
Mary C. Potter
doaj +1 more source