We develop a methodology that employs mixture of experts to scale up the parameters of reinforcement learning (RL) models in optimal execution tasks. The innovation of our approach stems from a spectral clustering-driven methodology for customized ...

Proper decision-making for endovascular treatment (EVT) is crucial in reducing complications of intracranial aneurysms (IAs) and improving the quality of patients’ lives. Electronic medical records (EMRs) possess comprehensive information about ...

The froth flotation process is a cost-effective and widely employed method for mineral separation. A core challenge is to maximize mineral recovery while maintaining a specified minimum concentrate grade. This requires precise control of aeration ...

• Enhance interpretability and generalizability with knowledge-embedded physical model.
• Capture uncertainty and learn unmodeled dynamics with ensemble residual data model.
• Extract latent features from uncertain states using fuzzy ...

Recently, a Multi-scale Representation Attention based deep multiple instance learning Network (MRAN) has been proposed to directly extract patch-level features from gigapixel whole slide images, and achieved promising performance on multiple ...

Multimodal learning, integrating histology images and genomics, promises to enhance precision oncology with comprehensive views at microscopic and molecular levels. However, existing methods may not sufficiently model the shared or complementary ...

Point cloud registration is a critical issue in 3D reconstruction and computer vision, particularly challenging in cases of low overlap and different datasets, where algorithm generalization and robustness are pressing challenges. In this paper, we ...

Smart homes, powered by the Internet of Things, offer great convenience but also pose security concerns due to abnormal behaviors, such as improper operations of users and potential attacks from malicious attackers. Several behavior modeling methods have ...

The plugging-in/-out of renewable distributed generation units (DGUs) often alters the microgrid size and coupling terms, resulting in computational burdens and voltage shocks. This article proposes a novel scalable fuzzy voltage control scheme for ...

The ability to ease operation and real-time feedback to image editing has attracted increasing attention in our everyday lives. Existing edit propagation approaches typically formulate the color editing task as a quadratic energy optimization ...

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• We presented a palette-based edit propagation for pixel-level color editing.
• We developed a graphical user interface (GUI) that is easy to use and learn.
• Our approach is efficient and requires fewer interactions than previous ...

The identification of compound-protein interactions (CPIs) plays a vital role in drug discovery. However, the huge cost and labor-intensive nature in vitro and vivo experiments make it urgent for researchers to develop novel CPI prediction ...

• We propose a novel cross multi-head attention oriented bidirectional interpretable CPI prediction model.
• The cross multi-head attention module of the proposed model integrates two multi-head scaled dot-product attentions, facilitating ...

The breakdown of healthcare facilities is a huge challenge for hospitals. Medical images obtained by Computed Tomography (CT) provide information about the patients' physical conditions and play a critical role in diagnosis of disease. ...

• A dictionary-based data-driven model is proposed to predict equipment anomalies in hospitals
• A meaningful Computed Tomography equipment anomaly indicator and the features with high importance are captured
• A fast and flexible data ...

Stochastic configuration networks (SCNs) have been widely used for modeling complex industrial process due to their rapid learning speed, ease of implementation, and universal approximation capability. For modeling water quality parameters in ...

Air quality monitoring is important to the green development of smart cities. Several technical challenges exist for intelligent, high-precision monitoring, such as computing overhead, area division, and monitoring granularity. In this article, we propose ...

This paper studies the problem of sensing mainlobe jamming strategy through interaction samples between a frequency agile radar and a transmit/receive time-sharing jammer. We model this interaction as an episodic Markov decision process, where the jammer&#...

• A novel PCG-logTV method is proposed for sparse reconstruction of BLT, which combines TV regularization and logarithm function.
• The method reduces the ill-posedness of BLT reconstruction and avoids the staircase artifacts of TV ...

Bioluminescence Tomography (BLT) is a powerful optical molecular imaging technique that enables the noninvasive investigation of dynamic biological phenomena. It aims to reconstruct the three-dimensional spatial ...

—Graph convolutional network (GCN) has attracted much attention in the field of hyperspectral image classification for its excellent feature representation and convolution on arbitrarily structured non-Euclidean data. However, most state-of-the-...

We investigate the explainability of graph neural networks (GNNs) as a step toward elucidating their working mechanisms. While most current methods focus on explaining graph nodes, edges, or features, we argue that, as the inherent functional mechanism of ...

The prognostic analysis for high grade serous adenocarcinoma (HGSC) holds significant clinical importance. However, current prognostic analysis primarily relies on statistical techniques like logistic regression and chi-square analysis alongside ...

Diagnosis of compound faults remains a challenge owing to the coupling of fault characteristics and the exponential increment of the number of possible fault types. Current compound faults diagnostic methods often require a large number of ...

Ultra-reliable and low-latency communications (URLLC) plays a critical role for the coming era of wireless industrial automation, which increases the flexibility without moderating the stringent requirements of latency and reliability. The task for URLLC ...