Results 21 to 30 of about 6,701,261 (238)
Classifying emotions in Stack Overflow and JIRA using a multi-label approach [PDF]
, 2020 A forum or social media post can express multiple emotions, such as love, joy or anger. Emotion classification has been proven useful for measuring aspects such as user satisfaction.
BESSIS, NIKOLAOS +2 more
core +1 more source
Multi-Source Data Fusion and Hydrodynamics for Urban Waterlogging Risk Identification
International Journal of Environmental Research and Public Health, 2023 The complex formation mechanism and numerous influencing factors of urban waterlogging disasters make the identification of their risk an essential matter. This paper proposes a framework for identifying urban waterlogging risk that combines multi-source
Zongjian Zhang +4 more
semanticscholar +1 more source
Bayesian analysis of multi-source data [PDF]
Physics Letters B, 1997 We present a simple method, based on Bayes' theorem, to fit binned data to one or more multi-source models. Assuming a Poisson probability for the count in each bin we can eliminate exactly the nuisance parameters from the likelihood function and arrive at a formula that can be broadly applied.
Pushpalatha C. Bhat +2 more
openaire +1 more source
Intelligent computing for WPT–MEC-aided multi-source data stream
EURASIP Journal on Advances in Signal Processing, 2023 Due to its low latency and energy consumption, edge computing technology is essential in processing multi-source data streams from intelligent devices. This article investigates a mobile edge computing network aided by wireless power transfer (WPT) for ...
Xiangdong Zheng +5 more
semanticscholar +1 more source
ProteoClade: A taxonomic toolkit for multi-species and metaproteomic analysis [PDF]
, 2020 We present ProteoClade, a Python toolkit that performs taxa-specific peptide assignment, protein inference, and quantitation for multi-species proteomics experiments.
Held, Jason M +3 more
core +2 more sources
Food chemistry: X, 2023 Highlights • The sources of multi-source data of cash crops and the strategies for processing multi-source data are summarized.• This paper summarizes several machine learning algorithms commonly used to analyze multi-source data of cash crops.• This ...
Yanying Zhang, Yuanzhong Wang
semanticscholar +1 more source
Journal of Cloud Computing: Advances, Systems and Applications, 2023 Multi-source data fusion techniques are widely applied in dynamic target detection scenarios, such as target situational awareness, radar signal resolution, and feature fusion labeling.
Nan Yang +5 more
doaj +1 more source
Secrecy performance of TAS/SC-based multi-hop harvest-to-transmit cognitive WSNs under joint constraint of interference and hardware imperfection [PDF]
, 2019 In this paper, we evaluate the secrecy performance of multi-hop cognitive wireless sensor networks (WSNs). In the secondary network, a source transmits its data to a destination via the multi-hop relaying model using the transmit antenna selection (TAS ...
Duy, Tran Trung +4 more
core +1 more source
SPOT: Open Source framework for scientific data repository and interactive visualization [PDF]
, 2018 SPOT is an open source and free visual data analytics tool for multi-dimensional data-sets. Its web-based interface allows a quick analysis of complex data interactively. The operations on data such as aggregation and filtering are implemented.
Attema, Jisk +5 more
core +2 more sources
Medical Concept Representation Learning from Multi-source Data [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Representing words as low dimensional vectors is very useful in many natural language processing tasks. This idea has been extended to medical domain where medical codes listed in medical claims are represented as vectors to facilitate exploratory analysis and predictive modeling.
Tian, Bai +3 more
openaire +2 more sources