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Calibration

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Nature inspired computation and ensemble neural network to build a robust model for spectral data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
UV spectrophotometry was introduced for simultaneous determination of Itraconazole (ITZ) and Secnidazole (SEZ) in their mixture without any prior separation. In this study, fourteen nature-inspired algorithms combined with partial least squares (PLS)...

Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research.

Science robotics
During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disor...

The relevance of signal timing in human-robot collaborative manipulation.

Science robotics
To achieve a seamless human-robot collaboration, it is crucial that robots express their intentions without perturbating or interrupting the task that a human partner is performing at that moment. Although it has not received much attention so far, t...

Automated Calibration of RSS Fingerprinting Based Systems Using a Mobile Robot and Machine Learning.

Sensors (Basel, Switzerland)
This paper describes an automated method for the calibration of RSS-fingerprinting-based positioning systems. The method assumes using a robotic platform to gather fingerprints in the system environment and using them for training machine learning mo...

Highly Dense FBG Temperature Sensor Assisted with Deep Learning Algorithms.

Sensors (Basel, Switzerland)
In this paper, we demonstrate the application of deep neural networks (DNNs) for processing the reflectance spectrum from a fiberoptic temperature sensor composed of densely inscribed fiber bragg gratings (FBG). Such sensors are commonly avoided in p...

Predicting the risk of cancer in adults using supervised machine learning: a scoping review.

BMJ open
OBJECTIVES: The purpose of this scoping review is to: (1) identify existing supervised machine learning (ML) approaches on the prediction of cancer in asymptomatic adults; (2) to compare the performance of ML models with each other and (3) to identif...

Unsupervised Learning in RSS-Based DFLT Using an EM Algorithm.

Sensors (Basel, Switzerland)
Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was...

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals.

Nature methods
Markerless three-dimensional (3D) pose estimation has become an indispensable tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by multi-view triangulation of deep network-based two-dimensional (2D) pose estimate...

Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

PloS one
INTRODUCTION: Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RS...

Embryo selection with artificial intelligence: how to evaluate and compare methods?

Journal of assisted reproduction and genetics
Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best embryo(s) available within a patient cohort for subsequent transfer or cryopreservation. In recent year...