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Edge Computing with Fog-cloud for Heart Data Processing using Particle Swarm Optimized Deep Learning Technique
Chronic illnesses such as heart disease, diabetes, cancer, and respiratory diseases are complex and pose a significant threat to global health....
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2D MRI registration using glowworm swarm optimization with partial opposition-based learning for brain tumor progression
Magnetic resonance imaging (MRI) registration is important in detection, diagnosis, treatment planning, determining radiographic progression,...
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Task scheduling using glowworm-based optimal heterogeneous earliest finish time algorithm for mobile grid
Mobile grids include features that support mobile users and mobile resources, including limited energy, unstable network connections, etc. Grid...
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Weak Association Mining Algorithm for Long Distance Wireless Hybrid Transmission Data in Cloud Computing
Long distance wireless hybrid transmission data is vulnerable to noise, resulting in low data mining accuracy, large mining error and poor mining...
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Analyzing Passing Sequences for the Prediction of Goal-Scoring Opportunities
Over the last years, more and more sport related data are being collected, stored, and analyzed to give valuable insights. Football is no exception...
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A smart intelligent approach based on hybrid group search and pelican optimization algorithm for data stream clustering
Big data applications generate a huge range of evolving, real-time, and high-dimensional streaming data. In many applications, data stream clustering...
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Chronological sewing training optimization enabled deep learning for autism spectrum disorder using EEG signal
Autism spectrum disorder (ASD) is a disorder in neurological growth, which includes cognitive and behavioral impairment and it starts from infancy....
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Performance analysis of path planning techniques for autonomous robots
Autonomous robots can use path planning techniques to determine the optimal trajectory during the mission. These techniques can be classified as...
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Enhancing efficiency in agriculture: densely connected convolutional neural network for smart farming
Smart farming plays a revolutionary paradigm shift in the realm of agriculture to enhance farming practices across the globe. Traditional smart...
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Efficient feature selection for breast cancer classification using soft computing approach: A novel clinical decision support system
One of the essential data pre-processing methods for enhancing the performance of machine learning (ML) models is feature selection. Because they...
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Deep-GAN: an improved model for thyroid nodule identification and classification
Tailoring a deep convolutional neural network (DCNN) is a tedious and time-consuming task in the field of medical image analysis. In this research...
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GSO-CNN-based model for the identification and classification of thyroid nodule in medical USG images
Thyroid ultrasonography is one of the widely used techniques for the detection and classification of thyroid nodules. In this paper, grid search...
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Optimized clustering routing framework to maintain the optimal energy status in the wsn mobile cloud environment
Nowadays, energy-efficient data transmission is one of the biggest challenges in Wireless Sensor Networks (WSNs). Therefore, various routing...
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Severity of lung infection identification and classification using optimization-enabled deep learning with IoT
A major disease affecting individuals irrespective of the different ages is lung disease and this problem is a result of different causes. The recent...
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Grid self-occlusion: a grid self-occlusion data augmentation for better classification
Data augmentation is a widely used regularization strategy, which can effectively alleviate the over-fitting and improve the robustness of the DCNNs...
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An enhanced soft-computing based strategy for efficient feature selection for timely breast cancer prediction: Wisconsin Diagnostic Breast Cancer dataset case
When contemplating the improvement of overall performance in machine learning (ML) models, a critical strategy for optimizing data preparation is...
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Theoretical and Empirical Analysis of FALCON and SOLMAE Using Their Python Implementation
Since NIST has recently selected FALCON as one of quantum–resistant digital signatures which uses the hash-and-sign paradigm in the style of...
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Modeling of automated glowworm swarm optimization based deep learning model for legal text summarization
Automatic legal text summarization becomes a challenging process because of unusual structure and high complexity of the documents. Existing works...
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A New Gadget Decomposition Algorithm with Less Noise Growth in HE Schemes
A gadget decomposition algorithm can invert a specific gadget matrix and produce an output with specific statistical properties. Such algorithms are...