AIMC Topic: Hot Temperature

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A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.

Journal of thermal biology
The health issues of hazardous operations in high-temperature environments are increasing concerns to the public, especially since global warming and extreme weather conditions have made the high-temperature work more frequent and harsher. The abnorm...

Co-pyrolysis kinetics and enhanced synergy for furfural residues and polyethylene using artificial neural network and fast heating.

Waste management (New York, N.Y.)
The efficient co-utilization of biomass and waste plastics is a key method to address the widely concerned environmental problem and replace traditional energy. Co-pyrolysis behaviors and synergistic effects of furfural residues (FR) and polyethylene...

Understanding the low-temperature drying process of sludge with machine learning in a sewage-source heat pump drying system.

Journal of environmental management
Heat pump drying technology based on sewage heat source is an eco-friendly sludge drying method. It can effectively reduce the pollution of natural water bodies by waste heat while reducing energy consumption. However, the drying characteristics of s...

Intelligent Thermochromic Heating E-Textile for Personalized Temperature Control in Healthcare.

ACS applied materials & interfaces
Heating electronic textiles (e-textiles) are widely used for thermal comfort and energy conservation, but prolonged heating raises concerns about heat-related illnesses, especially in the elderly. Despite advancements, achieving universal user satisf...

The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers.

BMC public health
BACKGROUND: Workplace may not only increase the risk of heat-related illnesses and injuries but also compromise work efficiency, particularly in a warming climate. This study aimed to utilize machine learning (ML) and deep learning (DL) algorithms to...

Evaluation and process monitoring of jujube hot air drying using hyperspectral imaging technology and deep learning for quality parameters.

Food chemistry
Timely and effective detection of quality attributes during drying control is essential for enhancing the quality of fruit processing. Consequently, this study aims to employ hyperspectral imaging technology for the non-destructive monitoring of solu...

Artificial intelligence as a tool for predicting the quality attributes of garlic (Allium sativum L.) slices during continuous infrared-assisted hot air drying.

Journal of food science
Effective drying methods are a highly suitable solution for ensuring stable food supply chains, reducing postharvest agricultural losses, and preventing the spoilage of perishable fruits and vegetables. Moreover, machine learning techniques are innov...

Predictive models for heat stress assessment in Holstein dairy heifers using infrared thermography and machine learning.

Tropical animal health and production
Heat stress is a condition that impairs the animal's productive and reproductive performance, and can be monitored by physiological and environmental variables, including body surface temperature, through infrared thermography. The objective of this ...

Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study aims to design a time-continuous pain level assessment system for temporomandibular joint therapy. Our objectives cover verifying literature suggestions on pain stimulus, protocols for collecting reference data, and continuous pain recogni...

Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste.

PloS one
Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyra...