With the rapid development of intelligent transformation in China's petrochemical industry, the intelligent inspection of oil and gas operation sites such as oil pumping stations has become a crucial initiative. T...
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Panoramic images are different from traditional 2D images, panoramic images can provide viewers with a broader perspective. Based on the human visual system and panoramic images, this paper proposes a new quality eval...
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Autonomous driving technology has brought the challenge of efficient and accurate detection to the forefront. To address this, this paper presents an improved YOLOv5 model by incorporating channel attention and spatia...
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Drug-drug interaction(DDI)prediction is a crucial issue in molecular *** methods of observing drug-drug interactions through medical experiments require significant resources and *** authors present a Medical Knowledg...
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Drug-drug interaction(DDI)prediction is a crucial issue in molecular *** methods of observing drug-drug interactions through medical experiments require significant resources and *** authors present a Medical Knowledge Graph Question Answering(MedKGQA)model,dubbed MedKGQA,that predicts DDI by employing machine reading comprehension(MRC)from closed-domain literature and constructing a knowledge graph of“drug-protein”triplets from open-domain *** model vectorises the drug-protein target attributes in the graph using entity embeddings and establishes directed connections between drug and protein entities based on the metabolic interaction pathways of protein targets in the human *** aligns multiple external knowledge and applies it to learn the graph neural *** bells and whistles,the proposed model achieved a 4.5%improvement in terms of DDI prediction accuracy compared to previous state-of-the-art models on the QAngaroo MedHop *** results demonstrate the efficiency and effectiveness of the model and verify the feasibility of integrating external knowledge in MRC tasks.
It is crucial to predict the outputs of a thickening system,including the underflow concentration(UC)and mud pressure,for optimal control of the *** proliferation of industrial sensors and the availability of thickeni...
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It is crucial to predict the outputs of a thickening system,including the underflow concentration(UC)and mud pressure,for optimal control of the *** proliferation of industrial sensors and the availability of thickening-system data make this ***,the unique properties of thickening systems,such as the non-linearities,long-time delays,partially observed data,and continuous time evolution pose challenges on building data-driven predictive *** address the above challenges,we establish an integrated,deep-learning,continuous time network structure that consists of a sequential encoder,a state decoder,and a derivative module to learn the deterministic state space model from thickening *** a case study,we examine our methods with a tailing thickener manufactured by the FLSmidth installed with massive sensors and obtain extensive experimental *** results demonstrate that the proposed continuous-time model with the sequential encoder achieves better prediction performances than the existing discrete-time models and reduces the negative effects from long time delays by extracting features from historical system *** proposed method also demonstrates outstanding performances for both short and long term prediction tasks with the two proposed derivative types.
A cyber-physical system is considered to be a collection of strongly coupled communication systems and devices that poses numerous security trials in various industrial applications including healthcare. The security ...
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(α, β)-core decomposition is a fundamental problem in graph analysis, and has been widely adopted for anomaly detection and online group recommendation. Nevertheless,(α, β)-core model only considers the distance-1...
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As a core technology of Intelligent Transportation System, traffic flow forecasting has a wide range of applications. Existing methods typically utilize graph neural network (GNNs) and temporal neural networks (TNNs) ...
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High coupling efficiency (CE) edge coupler are crucial for thin-film lithium niobate (TFLN) photonic integrated *** design and simulate a kind of high-performance b ident edge coupler based on TFLN using genetic *** r...
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Object detection represents a fundamental task within the realm of computer vision. However, achieving object detection in the dark is still a substantial challenge due to the low contrast of images and the lack of la...
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