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Optimization framework of laser oscillation welding based on a deep predictive reward reinforcement learning net
This research proposed a laser oscillation welding optimization system based on a deep reinforcement learning model with neural-network-based reward...
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Partitioned least squares
Linear least squares is one of the most widely used regression methods in many fields. The simplicity of the model allows this method to be used when...
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LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios
Multi-target multi-camera tracking is crucial to intelligent transportation systems. Numerous recent studies have been undertaken to address this...
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Exploring the dynamics of ICT and globalization on human development in India: asymmetric analysis and policy implications
The present study examines the asymmetrical relationship among globalization (GLB), information communication and technology (ICT), and human...
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A position-enhanced sequential feature encoding model for lung infections and lymphoma classification on CT images
PurposeDifferentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT...
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Edge highlighting with depth-dependent opacity gradation of laser-scanned point clouds improves the accuracy of perceived depth in transparent multi-view 3D visualizations
There is an activity called "digital archiving" in which cultural property is digitized for preservation and utilization, and transparent...
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Procedure-Aware Action Quality Assessment: Datasets and Performance Evaluation
In this paper, we investigate the problem of procedure-aware action quality assessment, which analyzes the action quality by delving into the...
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Application of neural networks to predict indoor air temperature in a building with artificial ventilation: impact of early stop**
Indoor air temperature prediction can facilitate energy-saving actions without compromising the indoor thermal comfort of occupants. The aim of this...
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Privacy-preserving matrix factorization for recommendation systems using Gaussian mechanism and functional mechanism
Building a recommendation system involves analyzing user data, which can potentially leak sensitive information about users. As shown in numerous...
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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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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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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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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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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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ASRE-KG&RS: knowledge graph and recommender system for adaptive smart radio environment
With the rapid advancement of wireless communication technologies, efficient utilization of the spectrum has become more complex and competitive....
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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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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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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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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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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...
