AIMC Topic: Artificial Intelligence

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How does artificial intelligence development affect green technology innovation in China? Evidence from dynamic panel data analysis.

Environmental science and pollution research international
As the global climate problem becomes increasingly serious, the green technology innovation to achieve "carbon peak and carbon neutral" has gradually become the global consensus of major countries, and how the rapid development of artificial intellig...

Unleashing the mechanism among environmental regulation, artificial intelligence, and global value chain leaps: a roadmap toward digital revolution and environmental sustainability.

Environmental science and pollution research international
Strengthening environmental regulation and adhering to the green as well as sustainable development of China's manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intellig...

Prediction of evaporation from dam reservoirs under climate change using soft computing techniques.

Environmental science and pollution research international
This study aimed to predict evaporation from dam reservoirs using artificial intelligence considering climate change. Mahabad Dam, near Lake Urmia, in northwestern Iran, is used to investigate the proposed approach. There are three parts to the study...

Artificial neural networks in contemporary toxicology research.

Chemico-biological interactions
Artificial neural networks (ANNs) have a huge potential in toxicology research. They may be used to predict toxicity of various chemical compounds or classify the compounds based on their toxic effects. Today, numerous ANN models have been developed,...

DeepGA for automatically estimating fetal gestational age through ultrasound imaging.

Artificial intelligence in medicine
Accurate estimation of gestational age (GA) is vital for identifying fetal abnormalities. Conventionally, GA is estimated by measuring the morphology of the cranium, abdomen, and femur manually and inputting them into the classic Hadlock formula to a...

The synergy of synchrotron imaging and convolutional neural networks towards the detection of human micro-scale bone architecture and damage.

Journal of the mechanical behavior of biomedical materials
The growing health and economic burden of bone fractures, their intricate multiscale features and the existing knowledge gaps in the comprehension of micro-scale bone damage occurrence make fracture diagnosis a challenging issue. In this scenario, de...

Wearable Devices for Remote Monitoring of Heart Rate and Heart Rate Variability-What We Know and What Is Coming.

Sensors (Basel, Switzerland)
Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a measure of variation in time between each heartbeat, representing the balance between the parasympathetic and sympathetic nervous system and may predict adve...

Efficient Object Detection Based on Masking Semantic Segmentation Region for Lightweight Embedded Processors.

Sensors (Basel, Switzerland)
Because of the development of image processing using cameras and the subsequent development of artificial intelligence technology, various fields have begun to develop. However, it is difficult to implement an image processing algorithm that requires...

The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets.

Scientific reports
Animal-borne tagging (bio-logging) generates large and complex datasets. In particular, accelerometer tags, which provide information on behaviour and energy expenditure of wild animals, produce high-resolution multi-dimensional data, and can be chal...