AIMC Topic: Reproducibility of Results

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Collaborative 3D Scene Reconstruction in Large Outdoor Environments Using a Fleet of Mobile Ground Robots.

Sensors (Basel, Switzerland)
Teams of mobile robots can be employed in many outdoor applications, such as precision agriculture, search and rescue, and industrial inspection, allowing an efficient and robust exploration of large areas and enhancing the operators' situational awa...

Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals.

Sensors (Basel, Switzerland)
Due to their robustness, versatility and performance, induction motors (IMs) have been widely used in many industrial applications. Despite their characteristics, these machines are not immune to failures. In this sense, breakage of the rotor bars (B...

Evaluation of product conceptual design based on Pythagorean fuzzy set under big data environment.

Scientific reports
The concept design evaluation phase of the new product launch is extremely important. However, current evaluation information relies mainly on the a priori knowledge of decision makers and is subjective and ambiguous. For this reason, a conceptual de...

Artificial intelligence-based diagnosis of asbestosis: analysis of a database with applicants for asbestosis state aid.

European radiology
OBJECTIVES: In many countries, workers who developed asbestosis due to their occupation are eligible for government support. Based on the results of clinical examination, a team of pulmonologists determine the eligibility of patients to these program...

Recommended practices and ethical considerations for natural language processing-assisted observational research: A scoping review.

Clinical and translational science
An increasing number of studies have reported using natural language processing (NLP) to assist observational research by extracting clinical information from electronic health records (EHRs). Currently, no standardized reporting guidelines for NLP-a...

Automated quantification and statistical assessment of proliferating cardiomyocyte rates in embryonic hearts.

American journal of physiology. Heart and circulatory physiology
The use of digital image analysis and count regression models contributes to the reproducibility and rigor of histological studies in cardiovascular research. The use of formalized computer-based quantification strategies of histological images essen...

LiSA: an assisted literature search pipeline for detecting serious adverse drug events with deep learning.

BMC medical informatics and decision making
INTRODUCTION: Detecting safety signals attributed to a drug in scientific literature is a fundamental issue in pharmacovigilance. The constant increase in the volume of publications requires the automation of this tedious task, in order to find and e...

The design of compounds with desirable properties - The anti-HIV case study.

Journal of computational chemistry
Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identif...

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications.

Bioresource technology
Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which ...

Reliability of active robotic neuro-navigated transcranial magnetic stimulation motor maps.

Experimental brain research
Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method used to study corticomotor organization and intervention-induced plasticity. Reliability of resting maps is well established, but understudied for active maps and un...