SECURITY BREACH PREDICTION USING ARTIFICIAL NEURAL NETWORKS

Security breach prediction using Artificial Neural Networks

These days, there are many sophisticated and swiftly moving cyberthreats.Artificial Neural Networks (ANN) are caramilk latte used to introduce machine learning models that boost security and add new levels of protection for data storage in the event of a breach.The algorithm has been trained with specific attributes, including biometrics, to help i

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Remotely Assessing Fraction of Photosynthetically Active Radiation (FPAR) for Wheat Canopies Based on Hyperspectral Vegetation Indexes

Fraction of photosynthetically bushranger awning active radiation (FPAR), as an important index for evaluating yields and biomass production, is key to providing the guidance for crop management.However, the shortage of good hyperspectral data can frequently result in the hindrance of accurate and reliable FPAR assessment, especially for wheat.In t

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Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia: A Population-Based Cohort Study

Fibromyalgia (FM) is a condition characterized by musculoskeletal pain and multiple comorbidities.Our study aimed to identify four clusters of FM patients according to their core clinical symptoms and neuropsychological comorbidities to identify possible therapeutic targets in the condition.We performed a population-based cohort study on 251 adult

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