AIMC Topic: Engineering

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Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial.

Journal of medical Internet research
Prompt engineering is a relatively new field of research that refers to the practice of designing, refining, and implementing prompts or instructions that guide the output of large language models (LLMs) to help in various tasks. With the emergence o...

Artificial dragonfly algorithm in the Hopfield neural network for optimal Exact Boolean k satisfiability representation.

PloS one
This study proposes a novel hybrid computational approach that integrates the artificial dragonfly algorithm (ADA) with the Hopfield neural network (HNN) to achieve an optimal representation of the Exact Boolean kSatisfiability (EBkSAT) logical rule....

Integrative soft computing approaches for optimizing thermal energy performance in residential buildings.

PloS one
As is known, early prediction of thermal load in buildings can give valuable insight to engineers and energy experts in order to optimize the building design. Although different machine learning models have been promisingly employed for this problem,...

A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance behavior.

Accident; analysis and prevention
In recent years, identifying road users' behavior and conflicts at intersections have become an essential data source for evaluating traffic safety. According to the Federal Highway Administration (FHWA), in 2020, more than 50% of fatal and injury cr...

Ethics and biomedical engineering for well-being: a cocreation study of remote services for monitoring and support.

Scientific reports
The well-being of students and staff directly affects their output and efficiency. This study presents the results of two focus groups conducted in 2022 within a two-phase project led by the Applied Biomedical and Signal Processing Intelligent e-Heal...

Evaluation and Improvement of Employee Performance with respect to Health, Safety, and Environment (HSE) Factors: A Case of Complex Transport Construction Project.

Computational intelligence and neuroscience
Risk control in complex transport construction is complicated due to the dangerous nature of high variation and unpredictability. Most of the current research analysis focuses on the health, safety, and environment (HSE) risk assessment and employee ...

Online dynamic ensemble deep random vector functional link neural network for forecasting.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's representation ability. Ea...

From Corrective to Predictive Maintenance-A Review of Maintenance Approaches for the Power Industry.

Sensors (Basel, Switzerland)
Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead...

Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time-Frequency-Based Features and Deep Learning Models.

Sensors (Basel, Switzerland)
The milling machine serves an important role in manufacturing because of its versatility in machining. The cutting tool is a critical component of machining because it is responsible for machining accuracy and surface finishing, impacting industrial ...

Detection of Missing Bolts for Engineering Structures in Natural Environment Using Machine Vision and Deep Learning.

Sensors (Basel, Switzerland)
The development of an accurate and efficient method for detecting missing bolts in engineering structures is crucial. To this end, a missing bolt detection method that leveraged machine vision and deep learning was developed. First, a comprehensive d...