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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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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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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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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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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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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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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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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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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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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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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,...
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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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A hybridization of multiple imputation and one-class bagging ensemble approach for missing value and class imbalance problem
Class imbalance in a dataset leads to erroneous outcomes that engrave the learning techniques and high misclassification cost in the minority class....
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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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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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Context-aware cross feature attentive network for click-through rate predictions
Click-through rate (CTR) prediction aims to estimate the likelihood that a user will interact with an item. It has gained significant attention in...
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An enhanced energy and distance based optimized clustering and dynamic adaptive cluster-based routing in software defined vehicular network
Software-Defined Vehicular Networks (SDVN) have been established to facilitate secure and adaptable vehicle communication within the dynamic...
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Statistical inference on multicomponent stress–strength reliability with non-identical component strengths using progressively censored data from Kumaraswamy distribution
In this article, we draw inferences on stress–strength reliability in a multicomponent system with non-identical strength components based on the...
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Optimal feature with modified bi-directional long short-term memory for big data classification in healthcare application
Artificial intelligence together with its applications are advancing in all fields, particularly medical science. A considerable quantity of clinical...
