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Research on Configurations for Marketing Performance of Science and Technology Enterprises in China Based on the TOE Framework
Published 2024-12-01“…Based on the Technology, Organization, and Environment (TOE) framework, this study uses a sample of 258 listed science and technology enterprises in China and applies the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method to examine the relationship between six conditions, namely, R&D capability, information technology application capability, marketing level, enterprise scale, government support, market competition, and marketing performance of science and technology enterprises from a configurational perspective. …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution
Published 2025-01-01“…The FedBFGCN was evaluated on standard reference network datasets (Cora, Citeseer, Polblogs), and experimental results showed that it has lower losses and higher performance in multiple aspects. This framework is capable of addressing various challenges in graph federated learning, significantly improving learning effectiveness and application capabilities. …”
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Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms
Published 2025-07-01“…Results We propose MM-IDTarget, a novel deep learning framework that employ a multimodal fusion strategy based on the intra and inter cross-attention mechanisms. …”
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AI-driven smart agriculture using hybrid transformer-CNN for real time disease detection in sustainable farming
Published 2025-07-01“…This study introduces the AttCM-Alex model, a novel deep-learning framework designed to boost the detection and classification of plant diseases under challenging environmental conditions. …”
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Development of a core competency evaluation index system for specialist nurses in robot-assisted surgery: a Delphi study
Published 2025-08-01“…Conclusion This study established a structured competency evaluation framework for nurses in robot-assisted surgery, comprising three primary, twelve secondary, and sixty-seven tertiary indicators. …”
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