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Automated Early Detection of Drops in Commercial Egg Production Using Neural Networks
(Taylor & Francis, 2017-10-17)
[Abstract] 1. The purpose of this work was to support decision-making in poultry farms by performing automatic early detection of anomalies in egg production.
2. Unprocessed data were collected from a commercial egg ...
Application of Functional Data Analysis for the Prediction of Maximum Heart Rate
(IEEE-Institute of Electrical and Electronics Engineers, 2019-08-29)
[Abstract]: Maximum heart rate (MHR) is widely used in the prescription and monitoring of exercise intensity, and also as a criterion for the termination of sub-maximal aerobic _tness tests in clinical populations.
Traditionally, ...
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning
(MDPI, 2019)
[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new
B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its
sequence, a known ...
Information Fusion and Ensembles in Machine Learning
(2019)
[Abstract] Traditionally, machine learning methods have used a single learning model to solve
a particular problem. However, the idea of combining multiple models instead of a
single one to solve a problem has its rationale ...
Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques
(PeerJ, Ltd., 2020-07-27)
[Abstract]
Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the nutritional status have determined that the adoption of a ...
IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection
(MDPI, 2021)
[Abstract] With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing ...
IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds
(MDPI, 2021)
[Abstract] The parasite species of genus Plasmodium causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, ...
Machine Learning-Based Radon Monitoring System
(MDPI, 2022)
[Abstract] Radon (Rn) is a biological threat to cells due to its radioactivity. It is capable of penetrating the human body and damaging cellular DNA, causing mutations and interfering with cellular dynamics. Human exposure ...
On a Neural Network to Extract Implied Information from American Options
(Routledge, 2022)
[Abstract] Extracting implied information, like volatility and dividend, from observed option prices is a challenging task when dealing with American options, because of the complex-shaped early-exercise regions and the ...
Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches
(IEEE, 2021)
[Abstract] Epiretinal Membrane (ERM) is a disease caused by a thin layer of scar tissue that is formed on the surface of the retina. When this membrane appears over the macula, it can cause distorted or blurred vision. ...