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Magnetic-guided nanocarriers for ionizing/non-ionizing radiation synergistic treatment against triple-negative breast cancer
BackgroundTriple-negative breast cancer (TNBC) is a subtype of breast cancer with the worst prognosis. Radiotherapy (RT) is one of the core...
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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...
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Multiobjective optimization-based trajectory planning for laser 3D scanner robots
In our industrial material defect detecting processes, the multi criteria is considered in two-level motion planning structure. Firstly, the feed...
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SIM-GCN: similarity graph convolutional networks for charges prediction
In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in...
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Factors leading to falls in transfemoral prosthesis users: a case series of prosthesis-side stumble recovery responses
BackgroundFalls due to stumbling are prevalent for transfemoral prosthesis users and may lead to increased injury risk. This preliminary case series...
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Improving predictive performance in e-learning through hybrid 2-tier feature selection and hyper parameter-optimized 3-tier ensemble modeling
The paper presents a new feature selection technique developed in detail here to address improved prediction accuracy not only for the...
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Towards Cardinality-Aware Evidential Combination Rules in Dempster–Shafer Theory
The Dempster–Shafer theory has garnered significant attention for effectively managing uncertainty across various disciplines. However, the core...
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Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing
In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams,...
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Fast Global Image Smoothing via Quasi Weighted Least Squares
Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
