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Twin Bounded Support Vector Machine with Capped Pinball Loss
In order to obtain a more robust and sparse classifier, in this paper, we propose a novel classifier termed as twin bounded support vector machine...
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Ant lion optimization based inertia weight optimized KGMO for mobility Management in Heterogeneous LTE cellular networks
This study proposes a hybrid optimization-based mobility management strategy employing Kinetic Gas Molecular Optimization (KGMO) and Ant Lion...
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Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based...
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Encryption of medical data based on blockchain and multi-chaotic maps
In this work, the SHA-256 mapper of the blockchain has been utilized to secure medical data from brute-force attacks. The uniform distribution and...
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Constructing a non-degenerate 2D chaotic map with application in irreversible PRNG
To solve the weakness of reversibility that exited in some pseudo-random number generators (PRNGs), we designed an enhanced chaos-based irreversible...
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Multi-layered access control based auto tuning relational key implications in enterprise-level multi-tenancy
This article discusses the importance of cloud-based multi-tenancy in private–public-private secure cloud environments, which is achieved through the...
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Text classification based on optimization feature selection methods: a review and future directions
A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a...
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Anomaly detection using deep learning approach for IoT smart city applications
With the advancements of IoT devices, many smart applications start to rule this era. In particular, smart cities has been adapted and realized by...
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Pothole detection in adverse weather: leveraging synthetic images and attention-based object detection methods
Potholes are a pervasive road hazard with the potential to cause accidents and vehicle damage. Detecting potholes accurately is essential for timely...
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Storage of weights and retrieval method (SWARM) approach for neural networks hybridized with conformal prediction to construct the prediction intervals for energy system applications
The prediction intervals represent the uncertainty associated with the model-predicted responses that impacts the sequential decision-making...
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Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey
Over the past few years, larger and deeper neural network models, particularly convolutional neural networks (CNNs), have consistently advanced...
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Image encryption framework based on multi-chaotic maps and equal pixel values quantization
The importance of image encryption has considerably increased, especially after the dramatic evolution of the internet and network communications,...
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Heart disease prediction using machine learning, deep Learning and optimization techniques-A semantic review
Cardiovascular disease holds the position of being the foremost cause of death worldwide. Heart Disease Prediction (HDP) is a difficult task as it...
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A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of...
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Advanced detection techniques for driver drowsiness: a comprehensive review of machine learning, deep learning, and physiological approaches
Road mishaps, a global concern, see driver fatigue contributing to roughly 40% of accidents in India. Detecting drowsiness early is pivotal in...
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ASOD: an adaptive stream outlier detection method using online strategy
In the current era of information technology, blockchain is widely used in various fields, and the monitoring of the security and status of the...
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Deep learning in medicine: advancing healthcare with intelligent solutions and the future of holography imaging in early diagnosis
Deep Learning (DL) is currently transforming health services by significantly improving early cancer diagnosis, drug discovery, protein–protein...
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A heuristic approach for insertion of multiple-complex coefficient-filter based DSTATCOM to enhancement of power quality in distribution system
The advent of non-linear systems has resulted in several power quality challenges, including harmonics, power losses, and voltage swings. To solve...
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A novel framework integrating ensemble transfer learning and Ant Colony Optimization for Knee Osteoarthritis severity classification
Knee Osteoarthritis (KOA), the most prevalent joint disease, significantly impacts elderly mobility due to progressive cartilage degeneration. Early...
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Correlated time-window constrained high-utility itemsets mining with certain and uncertain real-life datasets
High-utility Itemsets mining (HUIM) plays a crucial role in extracting valuable patterns from transaction data, aiding decision-making across...
