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Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms
In contemporary real-time applications, diminutive devices are increasingly employing a greater portion of the spectrum to transmit data despite the...
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Learning from Failure: Towards Develo** a Disease Diagnosis Assistant That Also Learns from Unsuccessful Diagnoses
In recent years, automatic disease diagnosis has gained immense popularity in research and industry communities. Humans learn a task through both...
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Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
With the widespread adoption of deep learning, there has been a notable increase in the prevalence of multimodal deepfake content. These deepfakes...
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Towards Long-Term Remembering in Federated Continual Learning
BackgroundFederated Continual Learning (FCL) involves learning from distributed data on edge devices with incremental knowledge. However, current FCL...
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Prognostic prediction model for esophageal cancer based on probability membrane systems
Esophageal squamous cell carcinoma (ESCC) is a clinically common heterogeneous malignant tumor of the digestive system and also one of the diseases...
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SPEI-FL: Serverless Privacy Edge Intelligence-Enabled Federated Learning in Smart Healthcare Systems
Smart healthcare systems promise significant benefits for fast and accurate medical decisions. However, working with personal health data presents...
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Evolutionary spiking neural networks: a survey
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural...
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Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
The burgeoning practice of unauthorized acquisition and utilization of personal textual data (e.g., social media comments and search histories) by...
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Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective
The automatic analysis of histology images is an open research field where machine learning techniques and neural networks, especially deep...
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Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
In medical imaging, traditional methods have long been relied upon. However, the integration of Generative Adversarial Networks (GANs) has sparked a...
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CPD-NSL: A Two-Stage Brain Effective Connectivity Network Construction Method Based on Dynamic Bayesian Network
Current brain science reveals that the connectivity patterns of the human brain are constantly changing when performing different tasks. Thus, brain...
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A conceptual examination of an additive manufactured high-ratio coaxial gearbox
This research introduces the novel “Kraken-Gear” mechanism, emphasizing the advantages of additive polymer 3D printing in high-ratio gearbox systems...
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Generative AI and Cognitive Computing-Driven Intrusion Detection System in Industrial CPS
Industrial Cyber-Physical Systems (ICPSs) are becoming more and more networked and essential to modern infrastructure. This has led to an increase in...
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A Novel Memristors Based Echo State Network Model Inspired by the Brain’s Uni-hemispheric Slow-Wave Sleep Characteristics
Memristors serve as electronic components with the ability to store charge and demonstrate resistive states, which are similar to the synaptic...
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Effect of subjective health conditions on facial skin temperature distribution: a 1-year statistical analysis among four participants
Thermal skin images are used to evaluate the physiological and psychological states of patients. To implement remote daily health monitoring, we...
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Effect of Leakage Delays on Bifurcation in Fractional-Order Bidirectional Associative Memory Neural Networks with Five Neurons and Discrete Delays
As is well known that time delays are inevitable in practice due to the finite switching speed of amplifiers and information transmission between...
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Inferring source of learning by chimpanzees in cognitive tasks using reinforcement learning theory
Reinforcement learning is a mathematical framework for learning better choices through trial-and-error. Recent studies revealed that reinforcement...
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A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques
Neuromarketing is an emerging research field that aims to understand consumers’ decision-making processes when choosing which product to buy. This...
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Connecto-informatics at the mesoscale: current advances in image processing and analysis for map** the brain connectivity
Map** neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow...
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Multi-view graph-based interview representation to improve depression level estimation
Depression is a serious mental illness that affects millions worldwide and consequently has attracted considerable research interest in recent years....
