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Intelligent and efficient task caching for mobile edge computing
Given the problems with a centralized cloud and the emergence of ultra-low latency applications, and the needs of the Internet of Things (IoT), it...
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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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Trust attack prevention based on Spark-blockchain in social IoT: a survey
Integrating the Internet of Things (IoT) with Social Networks (SN) has given rise to a new paradigm called Social IoT, which allows users and objects...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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Hierarchical adaptive evolution framework for privacy-preserving data publishing
The growing need for data publication and the escalating concerns regarding data privacy have led to a surge in interest in Privacy-Preserving Data...
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Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
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M2AST:MLP-mixer-based adaptive spatial-temporal graph learning for human motion prediction
Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences....
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Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
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An exploratory evaluation of code smell agglomerations
Code smell is a symptom of decisions about the system design or code that may degrade its modularity. For example, they may indicate inheritance...
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Global adaptive histogram feature network for automatic segmentation of infection regions in CT images
Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to...
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Examining ALS: reformed PCA and random forest for effective detection of ALS
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that...
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MIM: A multiple integration model for intrusion detection on imbalanced samples
The quantity of normal samples is commonly significantly greater than that of malicious samples, resulting in an imbalance in network security data....
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FlexpushdownDB: rethinking computation pushdown for cloud OLAP DBMSs
Modern cloud-native OLAP databases adopt a storage-disaggregation architecture that separates the management of computation and storage. A major...
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Data reduction in big data: a survey of methods, challenges and future directions
Data reduction plays a pivotal role in managing and analyzing big data, which is characterized by its volume, velocity, variety, veracity, value,...
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Unveiling the impact of employee-customer familiarity on customer purchase intentions: an empirical investigation within the realm of web-based date analytics
This research delves into the intricate dynamics of employee-customer familiarity and its profound influence on customer purchase intentions within...
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Emotion AWARE: an artificial intelligence framework for adaptable, robust, explainable, and multi-granular emotion analysis
Emotions are fundamental to human behaviour. How we feel, individually and collectively, determines how humanity evolves and advances into our shared...
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Survey-based analysis of cybersecurity awareness of Turkish seafarers
In recent years, vessels have become increasingly digitized, reflecting broader societal trends. As a result, maritime operations have become an...
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Smart contract vulnerabilities detection with bidirectional encoder representations from transformers and control flow graph
Up to now, the smart contract vulnerabilities detection methods based on sequence modal data and sequence models have been the most commonly used....
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A principal label space transformation and ridge regression-based hybrid gorilla troops optimization and jellyfish search algorithm for multi-label classification
Classification as an essential part of Machine Learning and Data Mining has significant roles in engineering, medicine, agriculture, military, etc....
