Month: July 2020

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Abstract Rotating machinery fault diagnosis problems have been well-addressed when sufficient supervised data of the tested machine are available using the latest data-driven methods. However, it is still challenging to …

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Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-determination Theory Perspective

Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-determination Theory Perspective

Abstract The teaching of artificial intelligence (AI) topics in school curricula is an important global strategic initiative in educating the next generation. As AI technologies are new to K-12 schools, …

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Machine Learning Security: Threats, Countermeasures, and Evaluations

Machine Learning Security: Threats, Countermeasures, and Evaluations

Abstract Machine learning has been pervasively used in a wide range of applications due to its technical breakthroughs in recent years. It has demonstrated significant success in dealing with various …

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Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children’s learning and emotive engagement

Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children’s learning and emotive engagement

Abstract Pedagogical agents are typically designed to take on a single role: either as a tutor who guides and instructs the student or as a tutee that learns from the …

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The impact of artificial intelligence in medicine on the future role of the physician

The impact of artificial intelligence in medicine on the future role of the physician

Abstract The practice of medicine is changing with the development of new Artificial Intelligence (AI) methods of machine learning. Coupled with rapid improvements in computer processing, these AI-based systems are …

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Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithm

Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithm

Abstract Optimizing the hyper-parameters of a multi-layer perceptron (MLP) artificial neural network (ANN) is not a trivial task, and even today the trial-and-error approach is widely used. Many works have …

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A Biological Mechanism Based Structure Self-Adaptive Algorithm for Feedforward Neural Network and Its Engineering Applications

A Biological Mechanism Based Structure Self-Adaptive Algorithm for Feed forward Neural Network and Its Engineering Applications

Abstract Feedforward neural network (FNN) is an information processing system that simulates human brain function to a certain extent by referring to the structure of a biological neural network and …

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Distributed Feature Extraction on Apache Spark forHuman Action Recognition

Distributed Feature Extraction on Apache Spark for Human Action Recognition

Abstract Local feature extraction is one of the most im-portant tasks to build robust video representation in humanaction recognition. Recent advances in computing visual features,especially deep-learned features, have achieved excellent …

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A Survey on Spark Ecosystem: Big Data Processing Infrastructure, Machine Learning, and Applications

A Survey on Spark Ecosystem: Big Data Processing Infrastructure, Machine Learning, and Applications

Abstract With the explosive increase of big data, it is necessary to apply large-scale data processing systems to analyze Big Data. Arguably, Spark is state of the art in large-scale …

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