Entity disambiguation (ED) is crucial in natural language processing (NLP) for tasks such as question-answering and information extraction. A major challenge in ED is handling overshadowed entities-uncommon entities s...
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The development of artificial intelligence (AI) has changed how hate speech is detected. In hate speech identification using machine learning, a number of methods are used to automatically find text that uses vocabula...
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Improve capitation accuracy by residual network and multiscale image training, There are two methods to detect caphead characteristics, Previously based on pre-described head characteristics, And methods based on the ...
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The density-based spatial clustering of applications with noise (DBSCAN) method is exceptionally sensitive to the selection of parameters, making it difficult to obtain more accurate clustering results. To solve the a...
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The comprehensive popularity of the Internet has gradually made it possible for blockchain technology to be applied to different industry sectors. The use of blockchain technology in lost and found platforms is conduc...
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Recently, how to handle the situation where only a few samples in the dataset are labeled has become a hot academic topic. Semi-Supervised Learning (SSL) has shown its great capacity and potential in this topic. Howev...
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This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)*** proposed MADQN is applied to tra...
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This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)*** proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly *** is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)*** enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in *** is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic *** proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.
In wireless communication networks, it is difficult to solve many NP-hard problems owing to computational complexity and high cost. Recently, quantum annealing (QA) based on quantum physics was introduced as a key ena...
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This paper designs a crib monitoring system based on the STM32 microcontroller. The system uses temperature and humidity sensors to collect the ambient temperature and humidity. The microcontroller processes and analy...
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The problem of attribute revocation exists in attribute encryption schemes, and with attribute revocation, user permissions will change accordingly. Aiming at the problem of user permissions and shared data verificati...
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