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Multi-channel anomaly detection using graphical models
Anomaly detection in multivariate time-series data is critical for monitoring asset conditions, enabling prompt fault detection and diagnosis to...
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Needle tracking in low-resolution ultrasound volumes using deep learning
PurposeClinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-time navigation, faces the challenge of precise...
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A network intrusion detection system based on deep learning in the IoT
As industrial and everyday devices become increasingly interconnected, the data volume within the Internet of Things (IoT) has experienced a...
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Parameters optimization and precision enhancement of Takagi–Sugeno fuzzy neural network
Takagi–Sugeno fuzzy neural network (TSFNN) has been widely used in intelligent prediction. The prediction accuracy of TSFNN is impacted by its model...
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Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans
The use of algorithms and automated systems, especially those leveraging artificial intelligence (AI), has been exploding in the public sector, but...
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Enhancing weld line visibility prediction in injection molding using physics-informed neural networks
This study introduces a novel approach using Physics-Informed Neural Networks (PINN) to predict weld line visibility in injection-molded components...
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Detection of pulmonary nodules in chest radiographs: novel cost function for effective network training with purely synthesized datasets
PurposeMany large radiographic datasets of lung nodules are available, but the small and hard-to-detect nodules are rarely validated by computed...
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Analyzing processing time and load factor: 5-node mix network with ElGamal encryption and XOR shuffling
To provide anonymous communication, this paper proposes the implementation of a 5-node mix network using ElGamal encryption and XOR Shuffling. An...
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VLSI realization of hybrid fast fourier transform using reconfigurable booth multiplier
A discrete fourier transform (DFT) of a series of samples may be quickly and efficiently computed with the use of a mathematical procedure known as...
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Subgraph generation applied in GraphSAGE deal with imbalanced node classification
In graph neural network applications, GraphSAGE applies inductive learning and has been widely applied in important research topics such as node...
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3D mobile regression vision transformer for collateral imaging in acute ischemic stroke
PurposeThe accurate and timely assessment of the collateral perfusion status is crucial in the diagnosis and treatment of patients with acute...
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Improving predictive performance in e-learning through hybrid 2-tier feature selection and hyper parameter-optimized 3-tier ensemble modeling
The paper presents a new feature selection technique developed in detail here to address improved prediction accuracy not only for the...
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Domain adaptation using AdaBN and AdaIN for high-resolution IVD mesh reconstruction from clinical MRI
PurposeDeep learning has firmly established its dominance in medical imaging applications. However, careful consideration must be exercised when...
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A novel artificial electric field strategy for economic load dispatch problem with renewable penetration
This article presents an innovative method to address the economic load dispatch (ELD) problem in power systems incorporating renewable energy...
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Enhancing Robotic Collaborative Tasks Through Contextual Human Motion Prediction and Intention Inference
Predicting human motion based on a sequence of past observations is crucial for various applications in robotics and computer vision. Currently, this...
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Risk management and its relationship with innovative construction technologies with a focus on building safety
Building safety has become a serious and important topic for the development of the construction industry, as well as for the preservation of...
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An improved approach for incomplete information modeling in the evidence theory and its application in classification
Incomplete information modeling and fusion under uncertain circumstances remain a significant open problem in practical engineering. In this study,...
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Statistical inference on multicomponent stress–strength reliability with non-identical component strengths using progressively censored data from Kumaraswamy distribution
In this article, we draw inferences on stress–strength reliability in a multicomponent system with non-identical strength components based on the...
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Optimal feature with modified bi-directional long short-term memory for big data classification in healthcare application
Artificial intelligence together with its applications are advancing in all fields, particularly medical science. A considerable quantity of clinical...
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SRGAN-enhanced unsafe operation detection and classification of heavy construction machinery using cascade learning
In the inherently hazardous construction industry, where injuries are frequent, the unsafe operation of heavy construction machinery significantly...
