AIMC Topic: Compressive Strength

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Several machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks.

Scientific reports
In engineering practices, it is critical and necessary to either measure or estimate the uniaxial compressive strength (UCS) of the rock. Measuring the UCS of rocks requires comprehensive studies in the field and in the laboratory for the rock block ...

Jellyfish Search-Optimized Deep Learning for Compressive Strength Prediction in Images of Ready-Mixed Concrete.

Computational intelligence and neuroscience
Most building structures that are built today are built from concrete, owing to its various favorable properties. Compressive strength is one of the mechanical properties of concrete that is directly related to the safety of the structures. Therefore...

Stability Risk Assessment of Underground Rock Pillars Using Logistic Model Trees.

International journal of environmental research and public health
Pillars are important structural elements that provide temporary or permanent support in underground spaces. Unstable pillars can result in rock sloughing leading to roof collapse, and they can also cause rock burst. Hence, the prediction of undergro...

Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS.

PloS one
An extensive simulation program is used in this study to discover the best ANN model for predicting the compressive strength of concrete containing Ground Granulated Blast Furnace Slag (GGBFS). To accomplish this purpose, an experimental database of ...

Soft robotic constrictor for in vitro modeling of dynamic tissue compression.

Scientific reports
Here we present a microengineered soft-robotic in vitro platform developed by integrating a pneumatically regulated novel elastomeric actuator with primary culture of human cells. This system is capable of generating dynamic bending motion akin to th...

Developing a boosted decision tree regression prediction model as a sustainable tool for compressive strength of environmentally friendly concrete.

Environmental science and pollution research international
One of the most significant parameters in concrete design is compressive strength. Time and money could be saved if the compressive strength of concrete is accurately measured. In this study, two machine learning models, namely, boosted decision tree...

Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment.

Environmental science and pollution research international
One of the most critical parameters in concrete design is compressive strength. As the compressive strength of concrete is correctly measured, time and cost can be decreased. Concrete strength is relatively resilient to impacts on the environment. Th...

EMG-based lumbosacral joint compression force prediction using a support vector machine.

Medical engineering & physics
Electromyography-assisted optimization (EMGAO) approach is widely used to predict lumbar joint loads under various dynamic and static conditions. However, such approach uses numerous anthropometric, kinematic, kinetic, and electromyographic data in t...

Applied Force during Piston Prosthesis Placement in a 3D-Printed Model: Freehand vs Robot-Assisted Techniques.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVES: To describe a 3D-printed middle ear model that quantifies the force applied to the modeled incus. To compare the forces applied during placement and crimping of a stapes prosthesis between the Robotic ENT Microsurgery System ( REMS) and t...

Handling limited datasets with neural networks in medical applications: A small-data approach.

Artificial intelligence in medicine
MOTIVATION: Single-centre studies in medical domain are often characterised by limited samples due to the complexity and high costs of patient data collection. Machine learning methods for regression modelling of small datasets (less than 10 observat...