Safety equipment detection is an important application of object detection, receiving widespread attention in fields such as smart construction sites and video surveillance. Significant progress has been made in objec...
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Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages,such as convenience,safety,simplicity,and avoidance of *** on many studies,...
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Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages,such as convenience,safety,simplicity,and avoidance of *** on many studies,exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration,type and other characteristics of specific *** the existing gas analysis technology,the electronic nose(eNose)analysis method has great advantages of high sensitivity,rapid response,real-time monitoring,ease of use and ***,this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis,existing breath testing technologies and the development and research status of electronic nose *** the electronic nose technology section,the three aspects of sensors,algorithms and existing systems are summarized in ***,the related challenges and limitations involved in the abovementioned technologies are also ***,the conclusion and perspective of eNose technology are presented.
In the present study, three hybrid models include support vector regression-salp swarm optimization (SVR-SSO), support vector regression-biogeography-based (SVR-BBO), and support vector regression-phasor particle swar...
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The use of unmanned aerial vehicles (UAVs) as aerial base stations has attracted increasing research interest in recent years. A key challenge in this field is determining how to deploy multiple UAVs in dynamic enviro...
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Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractab...
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Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractable shortcoming of multi-hop reasoning with RL is that sparse reward signals make performance *** mainstream methods apply heuristic reward functions to counter this ***,the inaccurate rewards caused by heuristic functions guide the agent to improper inference paths and unrelated object *** this end,we propose a novel adaptive Inverse Reinforcement Learning(IRL)framework for multi-hop reasoning,called AInvR.(1)To counter the missing and spurious paths,we replace the heuristic rule rewards with an adaptive rule reward learning mechanism based on agent’s inference trajectories;(2)to alleviate the impact of over-rewarded object entities misled by inaccurate reward shaping and rules,we propose an adaptive negative hit reward learning mechanism based on agent’s sampling strategy;(3)to further explore diverse paths and mitigate the influence of missing facts,we design a reward dropout mechanism to randomly mask and perturb reward parameters for the reward learning *** results on several benchmark knowledge graphs demonstrate that our method is more effective than existing multi-hop approaches.
This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one han...
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Making house calls is very crucial to deal with the competitive pressures of the service business and to improve service quality. We design a model called service routing problem with time windows and stochastic servi...
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Making house calls is very crucial to deal with the competitive pressures of the service business and to improve service quality. We design a model called service routing problem with time windows and stochastic service time(SRPTW-SST) that is based on vehicle routing problem with time windows. A self-adaptive discrete cuckoo search algorithm with genetic mechanism(sDCSGM) is proposed for the model SRPTW-SST. Moreover,we design a selection mechanism to improve the logicality of the algorithm based on the strong randomness of the Lévy flight. We introduce a genetic mechanism and design a neighborhood search mechanism for improving the robustness of the algorithm. In addition, an adaptive parameter adjustment method is designed to eliminate the impact of fixed parameters. The experimental results show that the sDCS-GM algorithm is more robust and effective than the state-of-the-art methods.
Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-...
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PROBLEM Recent years have witnessed the rapid progress of self-supervised language models (LMs)[1],especially large language models (LLMs)[2].LLMs not only achieved state-of-the-art performance on many natural languag...
PROBLEM Recent years have witnessed the rapid progress of self-supervised language models (LMs)[1],especially large language models (LLMs)[2].LLMs not only achieved state-of-the-art performance on many natural language processing tasks,but also captured widespread attention from the public due to their great potential in a variety of real-world applications (***,search engines,writing assistants,etc.)through providing general-purpose intelligent services.A few of the LLMs are becoming foundation models,an analogy to infrastructure,that empower hundreds of downstream applications.
The brain is the central part of the body that controls the overall functionality of the human body. The formulation of abnormal cells in the brain may lead to a brain tumor. Manual examination of a brain tumor is cha...
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