AIMC Topic: Learning

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Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach.

Sensors (Basel, Switzerland)
The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time p...

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations.

Nature communications
Deep neural networks (DNNs) optimized for visual tasks learn representations that align layer depth with the hierarchy of visual areas in the primate brain. One interpretation of this finding is that hierarchical representations are necessary to accu...

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph ...

The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research.

Research in social & administrative pharmacy : RSAP
Artificial Intelligence (AI) has revolutionized various domains, including education and research. Natural language processing (NLP) techniques and large language models (LLMs) such as GPT-4 and BARD have significantly advanced our comprehension and ...

ChatGPT in medical imaging higher education.

Radiography (London, England : 1995)
INTRODUCTION: Academic integrity among radiographers and nuclear medicine technologists/scientists in both higher education and scientific writing has been challenged by advances in artificial intelligence (AI). The recent release of ChatGPT, a chatb...

XRecon: An Explainbale IoT Reconnaissance Attack Detection System Based on Ensemble Learning.

Sensors (Basel, Switzerland)
IoT devices have grown in popularity in recent years. Statistics show that the number of online IoT devices exceeded 35 billion in 2022. This rapid growth in adoption made these devices an obvious target for malicious actors. Attacks such as botnets ...

Multiview child motor development dataset for AI-driven assessment of child development.

GigaScience
BACKGROUND: Children's motor development is a crucial tool for assessing developmental levels, identifying developmental disorders early, and taking appropriate action. Although the Korean Developmental Screening Test for Infants and Children (K-DST)...

Stable invariant models via Koopman spectra.

Neural networks : the official journal of the International Neural Network Society
Weight-tied models have attracted attention in the modern development of neural networks. The deep equilibrium model (DEQ) represents infinitely deep neural networks with weight-tying, and recent studies have shown the potential of this type of appro...

Three levels of information processing in the brain.

Bio Systems
Information, the measure of order in a complex system, is the opposite of entropy, the measure of chaos and disorder. We can distinguish several levels at which information is processed in the brain. The first one is the level of serial molecular gen...

CLDTLog: System Log Anomaly Detection Method Based on Contrastive Learning and Dual Objective Tasks.

Sensors (Basel, Switzerland)
System logs are a crucial component of system maintainability, as they record the status of the system and essential events for troubleshooting and maintenance when necessary. Therefore, anomaly detection of system logs is crucial. Recent research ha...