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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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Exploring the dynamics of ICT and globalization on human development in India: asymmetric analysis and policy implications
The present study examines the asymmetrical relationship among globalization (GLB), information communication and technology (ICT), and human...
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How clustering affects the convergence of decentralized optimization over networks: a Monte-Carlo-based approach
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent...
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Procedure-Aware Action Quality Assessment: Datasets and Performance Evaluation
In this paper, we investigate the problem of procedure-aware action quality assessment, which analyzes the action quality by delving into the...
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Application of neural networks to predict indoor air temperature in a building with artificial ventilation: impact of early stop**
Indoor air temperature prediction can facilitate energy-saving actions without compromising the indoor thermal comfort of occupants. The aim of this...
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Privacy-preserving matrix factorization for recommendation systems using Gaussian mechanism and functional mechanism
Building a recommendation system involves analyzing user data, which can potentially leak sensitive information about users. As shown in numerous...
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DNA codes over \(GR(2^{3},d)[X]/\langle X^{2},2X \rangle\)
The main results of this paper are in two directions. First, the family of finite local rings of length 4 whose annihilator of their maximal ideals...
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Parameters optimization and precision enhancement of Takagi–Sugeno fuzzy neural network
Takagi–Sugeno fuzzy neural network (TSFNN) has been widely used in intelligent prediction. The prediction accuracy of TSFNN is impacted by its model...
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A novel fusion feature imageization with improved extreme learning machine for network anomaly detection
As the complexity and quantity of network data continue to increase, accurate and efficient anomaly detection methods become critical. Deep...
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MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods
In recent years, some classical graph contrastive learning(GCL) frameworks have been proposed to address the problem of sparse labeling of graph data...
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Distributed neuro-fuzzy routing for energy-efficient IoT smart city applications in WSN
Wireless sensor networks (WSNs) enable seamless data gathering and communication, facilitating efficient and real-time decision-making in IoT...
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Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans
The use of algorithms and automated systems, especially those leveraging artificial intelligence (AI), has been exploding in the public sector, but...
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Fake and propaganda images detection using automated adaptive gaining sharing knowledge algorithm with DenseNet121
An additional tool for swaying public opinion on social media is to present recent developments in the creation of natural language. The term “Deep...
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Analyzing processing time and load factor: 5-node mix network with ElGamal encryption and XOR shuffling
To provide anonymous communication, this paper proposes the implementation of a 5-node mix network using ElGamal encryption and XOR Shuffling. An...
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When is it acceptable to break the rules? Knowledge representation of moral judgements based on empirical data
Constraining the actions of AI systems is one promising way to ensure that these systems behave in a way that is morally acceptable to humans. But...
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Enhancing SNV identification in whole-genome sequencing data through the incorporation of known genetic variants into the minimap2 index
MotivationAlignment of reads to a reference genome sequence is one of the key steps in the analysis of human whole-genome sequencing data obtained...
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VLSI realization of hybrid fast fourier transform using reconfigurable booth multiplier
A discrete fourier transform (DFT) of a series of samples may be quickly and efficiently computed with the use of a mathematical procedure known as...
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Subgraph generation applied in GraphSAGE deal with imbalanced node classification
In graph neural network applications, GraphSAGE applies inductive learning and has been widely applied in important research topics such as node...
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A Review of Anonymization Algorithms and Methods in Big Data
In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of...
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Deep reinforcement learning based mapless navigation for industrial AMRs: advancements in generalization via potential risk state augmentation
This article introduces a novel Deep Reinforcement Learning (DRL)-based approach for mapless navigation in Industrial Autonomous Mobile Robots,...
