Existing smart contract vulnerability identification approaches mainly focus on complete program detection. Consequently, lots of known potentially vulnerable locations need manual verification, which is energy-exhaus...
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Pressure injury (PI) is one of the major causes of short-term death. Early intervention for patients at risk plays an essential role in PI. However, many nurses may ignore risks. This paper aims to establish a model t...
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Building upon the impressive success of CLIP (Contrastive Language-Image Pretraining), recent pioneer works have proposed to adapt the powerful CLIP to video data, leading to efficient and effective video learners for...
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Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate th...
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Road network restoration is an important issue in the post-disaster disposal and rescue,especially when extraordinarily serious natural disasters(e.g.,floods and earthquakes) *** to this endeavour is the problem of de...
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Road network restoration is an important issue in the post-disaster disposal and rescue,especially when extraordinarily serious natural disasters(e.g.,floods and earthquakes) *** to this endeavour is the problem of determining how to reasonably schedule and route the repair crew to quickly restore the damaged road network and establish reliable supply lines from supply nodes to demand ***,most existing work focuses on the activities of the single repair crew in the static road network,which is unable to adapt to the dynamic changes of the road network caused by secondary disasters,such as rock slides and debris ***,this work is concentrated on multicrew dynamic scheduling and routing in road network ***,a model of multicrew dynamic scheduling and routing is first ***,the Markov decision process is adopted to construct a decision model for repair crews,based on which a multiagent Q-learning algorithm is developed to find the best scheduling and routing ***,experimental results demonstrate that the proposed method can make repair crews adjust their scheduling and routing strategies according to the dynamic changes of the damaged road network and provides a useful attempt to restore the damaged road network in complex,dynamic emergency scenarios of post-disaster.
Next-POI recommendation aims to explore from user check-in sequence to predict the next possible location to be visited. Existing methods are often difficult to model the implicit association of multi-modal data with ...
Next-POI recommendation aims to explore from user check-in sequence to predict the next possible location to be visited. Existing methods are often difficult to model the implicit association of multi-modal data with user choices. Moreover, traditional methods struggle to fully explore the variation of user preferences at variable time intervals. To tackle these limitations, we propose a Multi-Modal Temporal knowledge Graph-aware Sub-graph Embedding approach (Mandari). We first construct a novel Multi-Modal Temporal knowledge Graph. Based on the proposed knowledge graph, we integrate multi-modal information and leverage the graph attention network to calculate sub-graph prediction probability. Next, we implement a temporal knowledge mining method to model the segmentation and periodicity of user check-in and obtain temporal prediction probability. Finally, we fuse temporal prediction probability with the previous sub-graph prediction probability to obtain the final result. Extensive experiments demonstrate that our approach outperforms existing state-of-the-art methods.
Logistics vehicle and cargo matching problem is a typical combination optimization problem, which has important theoretical and application value in the field of logistics distribution. The proved particle swarm optim...
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The problem of vehicle routing planning (VRP) has far-reaching influence, and is widely used in vehicle scheduling, industrial production, transportation, logistics and distribution. The study of VRP and its associate...
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Aiming at the problem that the amplitude of load oscillation is not easy to control in the movement process of overhead crane, this paper designs a switching PID control method based on whale optimization algorithm(WO...
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Weakly supervised semantic segmentation (WSSS), which aims to mine the object regions by merely using class-level labels, is a challenging task in computer vision. The current state-of-the-art CNN-based methods usuall...
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