In the Internet of Things (IoT), optimizing machine performance through data analysis and improved connectivity is pivotal. Addressing the growing need for environmentally friendly IoT solutions, we focus on "gre...
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Online learning, particularly Multi-Armed Bandit (MAB) algorithms, has been extensively adopted in various real-world networking applications. In certain applications, such as fair heterogeneous networks coexistence, ...
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Communication is one of the fields that adopts quantum characteristics to improve its potential. In particular, quantum teleportation (QT) is considered a fundamental tool for enabling quantum networks. This paper foc...
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Advancements in quantum computer hardware and software have paved the way for the application of quantum computing across various fields. With the development of computers with thousands of qubits, the power of quantu...
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Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally ***-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC ***,their limited ability to collect and ...
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Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally ***-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC ***,their limited ability to collect and acquire contextual information hinders their *** propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address *** proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human *** used text augmentation techniques to producemore training data,improving the proposed model’s *** encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual *** integration improves the accuracy and robustness of the proposed ***,we present a method for balancing the training dataset by creating enhanced samples from the original *** balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed *** results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ***-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based *** balanced dataset and the additional training samples also enhance its *** findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.
Decentralized applications leveraging blockchain technology are gaining widespread adoption within the decentralized applications ecosystem. Interoperability, a fundamental concept facilitating seamless data and proce...
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Tourism route planning is widely applied in the smart tourism *** Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions proble...
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Tourism route planning is widely applied in the smart tourism *** Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions problems,which leads to uneven distribution and weak diversity of optimization solutions of tourism *** by these limitations,we propose a multi-objective evolutionary algorithm for tourism route recommendation(MOTRR)with two-stage and Pareto layering based on *** method decomposes the multiobjective problem into several subproblems,and improves the distribution of solutions through a two-stage *** crowding degree mechanism between extreme and intermediate populations is used in the two-stage *** neighborhood is determined according to the weight of the subproblem for crossover ***,Pareto layering is used to improve the updating efficiency and population diversity of the *** two-stage method is combined with the Pareto layering structure,which not only maintains the distribution and diversity of the algorithm,but also avoids the same *** with several classical benchmark algorithms,the experimental results demonstrate competitive advantages on five test functions,hypervolume(HV)and inverted generational distance(IGD)*** the experimental results of real scenic spot datasets from two famous tourism social networking sites with vast amounts of users and large-scale online comments in Beijing,our proposed algorithm shows better *** proves that the tourism routes recommended by our proposed algorithm have better distribution and diversity,so that the recommended routes can better meet the personalized needs of tourists.
The distributed data infrastructure in Internet of Things (IoT) ecosystems requires efficient data-series compression methods, as well as the capability to meet different accuracy demands. However, the compression per...
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Recent research in quantum computing has gained significant momentum, promising transformative advances across various fields, including artificial intelligence (AI). This paper focuses on quantum reinforcement learni...
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Various methods have been proposed to secure access to sensitive information over time, such as many cryptographic methods in use to facilitate secure communications on the internet. But other methods like steganograp...
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