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Differences between BT and if-then systems and their applications

Navigation of this blog[/su_button Differences Between BT (Behavior Tree) and If-Then Systems A Behavior Tre...
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Roughness, Harmony and Japanese Culture

Amaterasu-Omikami and Susanoo-no-Mikoto Takachiho in Miyazaki Prefecture is mentioned in the Kojiki (R...
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Recommendation systems in Netflix

  Netflix recommendation system The Netflix recommendation system will be based on information such as a user'...
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FIDO and Passkey

  FIDO FIDO (Fast Identity Online) is a standardisation framework for more secure and easier online authenticati...
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Overview of ChebNet and Examples of Algorithms and Implementations

Overview of ChebNet ChebNet (Chebyshev network) is a type of graph neural network (GNN) proposed by Deffer...
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Antimatter, Gravity and its Applications

Introduction The other day, NHK news reported "First Observation of Gravitational Fall of 'Antimatter' Internat...
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Bipolar lithium-ion iron phosphate battery

  Introduction From "Really?" Life expectancy is 1,000,000 km? Toyota's new battery will save Japan! Coming in 202...
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Overview of state space models and examples of implementing time series data analysis using R and Python

Overview of time series data analysis Time-series data is called data whose values change over time, suc...
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What is a function – its history, programming and machine learning

About Functions A function will generally be mathematically defined as a rule that assigns to each element in ...
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Protected: Explainable Machine Learning (18)Adversarial Examples

Explainable Machine Learning with Adversarial Sample Approach utilized for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Cyber Security, Surrogate Models, Neural Networks, Black Box Attack, Expectation Over Transformation algorithm, EOT, InceptionV3, TensorFlow, Fast gradient method, VGG16 classifier, ImageNet, adversarial patch, 1-pixel attack, L-BFGS method, Fast gradient sign method
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