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A hybrid deep learning based enhanced and reliable approach for VANET intrusion detection system
Advances in autonomous transportation technologies have profoundly influenced the evolution of daily commuting and travel. These innovations rely...
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A survey on privacy-preserving federated learning against poisoning attacks
Federated learning (FL) is designed to protect privacy of participants by not allowing direct access to the participants’ local datasets and training...
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Saver: a proactive microservice resource scheduling strategy based on STGCN
As container technology and microservices mature, applications increasingly shift to microservices and cloud deployment. Growing microservices scale...
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Visual identification of sleep spindles in EEG waveform images using deep learning object detection (YOLOv4 vs YOLOX)
The electroencephalogram (EEG) is a tool utilized to capture the intricate electrical dynamics within the brain, offering invaluable insights into...
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A hybrid approach of ALNS with alternative initialization and acceptance mechanisms for capacitated vehicle routing problems
The vehicle routing problem (VRP) with capacity constraints is a challenging problem that falls into the category of non-deterministic...
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An improved scheduling with advantage actor-critic for Storm workloads
Various resources as the essential elements of data centers, and their utilization is vital to resource managers. In terms of the persistence, the...
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File chunking towards on-chain storage: a blockchain-based data preservation framework
The growing popularity of the most current wave of decentralized systems, powered by blockchain technology, which act as data vaults and preserve...
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MTV-SCA: multi-trial vector-based sine cosine algorithm
The sine cosine algorithm (SCA) is a metaheuristic algorithm that employs the characteristics of sine and cosine trigonometric functions. SCA’s...
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A weighted multi-view clustering via sparse graph learning
Multi-view clustering considers the diversity of different views and fuses these views to produce a more accurate and robust partition than...
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Enhancing security and scalability by AI/ML workload optimization in the cloud
The pervasive adoption of Artificial Intelligence (AI) and Machine Learning (ML) applications has exponentially increased the demand for efficient...
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When large language models meet personalization: perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model...
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Gaming the system: tetromino-based covert channel and its impact on mobile security
Trojan droppers consistently emerge as challenging malware threats, particularly within the Android ecosystem. Traditional malware detection...
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PointDMIG: a dynamic motion-informed graph neural network for 3D action recognition
Point cloud contains rich spatial information, providing effective supplementary clues for action recognition. Existing action recognition algorithms...
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Research and optimization of task scheduling algorithm based on heterogeneous multi-core processor
Heterogeneous multi-core processor has the ability to switch between different types of cores to perform tasks, which provides more space and...
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Enhancement and formal verification of the ICC mechanism with a sandbox approach in android system
Inter-Component Communication (ICC) plays a crucial role in facilitating information exchange and functionality integration within the complex...
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Connecting the dots between stance and fake news detection with blockchain, proof of reputation, and the Hoeffding bound
Combating fake news is a crucial endeavor, yet the complexity of the task requires multifaceted approaches that transcend singular technological...
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Advanced cost-aware Max–Min workflow tasks allocation and scheduling in cloud computing systems
Cloud computing has emerged as an efficient distribution platform in modern distributed computing offering scalability and flexibility. Task...
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RAPTS: resource aware prioritized task scheduling technique in heterogeneous fog computing environment
The Internet of Things (IoT) is an emerging technology incorporating various hardware devices and software applications to exchange, analyze, and...
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DMFNet: deep matrix factorization network for image compressed sensing
Due to its outstanding performance in image processing, deep learning (DL) is successfully utilized in compressed sensing (CS) reconstruction....
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Federated learning for supervised cross-modal retrieval
In the last decade, the explosive surge in multi-modal data has propelled cross-modal retrieval into the forefront of information retrieval research....
