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ISSN: 2666-3074

Optimizing breast cancer diagnosis: Harnessing the power of nature-inspired metaheuristics for feature selection with soft voting classifiers

•Machine learning aids early detection of breast cancer.•Nature-inspired algorithms efficiently identify informative features, enhancing model performance.•Study compares soft voting with machine learning...

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A novel and secured email classification and emotion detection using hybrid deep neural network

•A challenge that hasn't been fully solved yet is measuring semantic relationships and similarities of WordNet ontologies to semantically reduce email functionality.•As far as aware no research has...

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Exploring static rebalancing strategies for dockless bicycle sharing systems based on multi-granularity behavioral decision-making

•We propose an adjustable MG CIF PRT based on the TWD framework. This method expands the range of choices for DMs across different granularities and enhances the accuracy of decision outcomes.•We put...

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Novel Darknet traffic data synthesis using Generative Adversarial Networks enhanced with oscillatory Growing Cosine Unit activated convolution layers

•Created a Generative Adversarial network which generates training and testing data for Darknet traffic which is otherwise very difficult to capture.•Enhanced the performance of the GAN by using an...

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Analyze the impact of feature selection techniques in the early prediction of CKD

•Early prediction of CKD is a challenging task.•Machine Learning (ML) Techniques play a significant role.•Optimal feature selection by EFS.•Importance of feature selection in CKD analysis....

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DDSS: Driver decision support system based on the driver behaviour prediction to avoid accidents in intelligent transport system

•Driver behaviour prediction algorithm constructed based on driver physical parameters and external parameters.•Driver physical parameters measures the driver drowsiness and alcohol consumption and...

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From predictive analytics to emotional recognition–The evolving landscape of cognitive computing in animal welfare

•Cognitive computing reshapes agriculture & livestock.•Cognitive systems mimic human thought, impacting farming.•Computing detects animal behavior nuances for well-being.•Ethical use of computing is...

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Deep learning-based approaches for abusive content detection and classification for multi-class online user-generated data

•an abusive language detection model that perform multiclass classification of offensive language.•experimented with five deep learning models: Bi-LSTM, LSTM, Bi-GRU, GRU, and multi-dense LSTM.•dataset...

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Multi-Agent cubature Kalman optimizer: A novel metaheuristic algorithm for solving numerical optimization problems

•Develop a novel meta-heuristics optimization algorithm inspired by cubature Kalman filter.•Test the MACKO algorithm against CEC2014 test suite with 30 benchmark functions.•Compare the MACKO algorithm...

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Handwritten alphabet classification in Tamil language using convolution neural network

Handwritten Alphabet Recognition can be defined as the way of detecting characters from images of Handwritten language alphabets. This is one of the important problems that can be solved by Convolution...

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ECDSA-based tamper detection in medical data using a watermarking technique

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care to patients remotely. The use of telemedicine has seen a significant increase in recent years,...

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Twitter sentiment analysis using conditional generative adversarial network

•In this paper, Conditional Generative Adversarial Network (CGAN), a deep learning framework for sentiment analysis for twitter is proposed.•The Convolutional Neural Network (CNN) a deep learning technique...

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A tweet sentiment classification approach using an ensemble classifier

•A new ensemble classifier is proposed which is a combination of machine learning classifiers (random forest, decision tree, support vector machine) and ensemble classifier performs high level classification...

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Analyzing emotions in online classes: Unveiling insights through topic modeling, statistical analysis, and random walk techniques

High dropout rates globally perpetuate educational disparities with various underlying causes. Despite numerous strategies to address this issue, more attention should be given to understanding and...

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Fake review detection using transformer-based enhanced LSTM and RoBERTa

•Comprehensive examination of various methodologies in the identification of false reviews.•A novel and practical approach that leverages transformer architecture to identify fake reviews.•A comprehensive...

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Navigating the Nexus: A systematic review of the symbiotic relationship between the metaverse and gaming

•Present a detailed review on the impact of metaverse on the gaming industry and communities.•Present insights into key dimensions and mechanisms of the symbiotic relationship between the metaverse...

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Image cyberbullying detection and recognition using transfer deep machine learning

•This research addresses shortcomings in existing literature and offers a new perspective in the fight against cyberbullying.•It proposes a hybrid approach that utilizes the strengths of both deep learning...

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Supportive particle swarm optimization with time-conscious scheduling (SPSO-TCS) algorithm in cloud computing for optimized load balancing

•Optimized load balancing in cloud computing.•Supportive particle swarm optimization algorithm.•Time conscious scheduling.•Particle swarm optimization vs ant colony optimization.•Resource utilization...

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Advanced Parkinson’s Disease Detection: A comprehensive artificial intelligence approach utilizing clinical assessment and neuroimaging samples

Medical experts are utilizing neuroimaging and clinical assessments to enhance the early identification of Parkinson’s disease. The current research initiative offers ways to identify Parkinson’s disease...

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Adversarial learning for Mirai botnet detection based on long short-term memory and XGBoost

•The aim of this research is to develop a resilient defence against Mirai botnet attacks. The Long Short Term Memory term (LSTM) and XGBoost combined have the best performance of 97.7% accuracy score.With...

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Data-driven strategies for digital native market segmentation using clustering

The rapid growth of internet users and social networking sites presents significant challenges for entrepreneurs and marketers. Understanding the evolving behavioral and psychological patterns across...

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A novel rice plant leaf diseases detection using deep spectral generative adversarial neural network

•(S2AFS) using deep spectral generative adversarial neural network (DSGAN2) model for detection and prediction of disease in rice plant leaf.•To test and validate the developed model using a standard...

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Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN

Human activity recognition (HAR) plays a crucial role in assisting the elderly and individuals with vascular dementia by providing support and monitoring for their daily activities. This paper presents...

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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies

In the rapidly advancing era of educational technology, customized learning materials have the potential to enhance individuals’ learning capacities. This research endeavors to devise an effective method...

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Knowledge mapping analysis of situational awareness and aviation: A bibliometric study

•SA's growing relevance lacks thorough aviation review.•754 articles map SA in aviation, exploring the research landscape of SA in aviation.•Study yields SA framework aids new researchers to identify...

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