Analysis Of Algorithms
Mostrando 1-12 de 618 artigos, teses e dissertações.
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1. Identifying olive oil fraud and adulteration using machine learning algorithms
As olive oil (OO) is more expensive than other vegetable oils, it is usually adulterated by blending it with more economic edible oils such as cottonseed oil (CSO), canola oil (CO), and soybean oil (SO). This research aimed to determine the fatty acid compositions obtained as a result of blending different proportions of CSO, CO and SO with OO using a gas ch
Química Nova. Publicado em: 2022
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2. Optimization Techniques and Mathematical Modeling Applied to Reluctance Motors
Abstract The present work aims at the application of different optimization strategies in the electromagnetic analysis of the Variable Reluctance Motor (VRM) through Finite Element (FE) simulation. Two case studies are investigated: the first one aims to optimize the geometry and electrical characteristics of windings of a single-phase VRM 6/6, minimizing co
Journal of Microwaves, Optoelectronics and Electromagnetic Applications. Publicado em: 2022
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3. Association of FAAH p.Pro129Thr and COMT p.Ala72Ser with schizophrenia and comorbid substance use through next-generation sequencing: an exploratory analysis
Objective: Individuals with schizophrenia and substance use disorders have a poor prognosis and increased psychiatric symptoms. The present study aimed to explore the association of 106 genes in individuals with schizophrenia and comorbid substance use through a next-generation sequencing (NGS) analysis and different in silico algorithms. Methods: We includ
Brazilian Journal of Psychiatry. Publicado em: 2022
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4. Rapid Recognizing the Producing Area of a Tobacco Leaf Using Near-Infrared Technology and a Multi-Layer Extreme Learning Machine Algorithm
A novel recognition method was put forward to identify the producing areas of the flue-cured tobacco leaves rapidly and non-destructively by using a near-infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA) and extreme learning machine (ELM) algorithms, the ac
Journal of the Brazilian Chemical Society. Publicado em: 2022
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5. Use of artificial intelligence in ophthalmology: a narrative review
ABSTRACT BACKGROUND: Artificial intelligence (AI) deals with development of algorithms that seek to perceive one’s environment and perform actions that maximize one’s chance of successfully reaching one’s predetermined goals. OBJECTIVE: To provide an overview of the basic principles of AI and its main studies in the fields of glaucoma, retinopathy of
Sao Paulo Medical Journal. Publicado em: 2022
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6. Decision tree-based classification as a support to diagnosis in the Alzheimer’s disease continuum using cerebrospinal fluid biomarkers: insights from automated analysis
Objective: Cerebrospinal fluid (CSF) biomarkers add accuracy to the diagnostic workup of cognitive impairment by illustrating Alzheimer’s disease (AD) pathology. However, there are no universally accepted cutoff values for the interpretation of AD biomarkers. The aim of this study is to determine the viability of a decision-tree method to analyse CSF bioma
Brazilian Journal of Psychiatry. Publicado em: 2022
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7. Numerical analysis of collapse modes in optimized design of alveolar Steel-concrete composite beams via genetic algorithms
Abstract The objective of this study is to present the formulation and applications of the optimization problem of steel-concrete composite alveolar beams. In addition to presenting the formulation, a comparative analysis of the predominant collapse modes is performed numerically via the finite element method. The optimization program was developed with the
REM, Int. Eng. J.. Publicado em: 2021-06
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8. Applicability of computer vision in seed identification: deep learning, random forest, and support vector machine classification algorithms
ABSTRACT The use of computer image analysis can assist the extraction of morphological information from seeds, potentially serving as a resource for solving taxonomic problems that require extensive training by specialists whose primary method of examination is visual identification. We propose to test the ability of deep learning, SVM and random forest algo
Acta Bot. Bras.. Publicado em: 2021-03
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9. Automated Framework for Developing Predictive Machine Learning Models for Data-Driven Drug Discovery
The increasing availability of extensive collections of chemical compounds associated with experimental data provides an opportunity to build predictive quantitative structure-activity relationship (QSAR) models using machine learning (ML) algorithms. These models can promote data-driven decisions and have the potential to speed up the drug discovery process
J. Braz. Chem. Soc.. Publicado em: 2021-01
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10. Predictive Factors of Mortality in Acute Aortic Dissection and Validity of the EuroSCORE Algorithm in a Small-Sized Cardiac Surgery Institution
Abstract Introduction: Acute aortic dissection (AAD) is a devastating surgical emergency, with high operative mortality. Several scoring algorithms have been used to establish the expected mortality in these patients. Our objective was to define the predictive factors for mortality in our center and to validate the EuroSCORE and Penn classification system.
Braz. J. Cardiovasc. Surg.. Publicado em: 2020-12
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11. Evaluation of patients undergoing emergency surgery in a COVID-19 pandemic hospital: a cross-sectional study
ABSTRACT BACKGROUND: The COVID-19 pandemic is threatening healthcare systems and hospital operations on a global scale. Treatment algorithms have changed in general surgery clinics, as in other medical disciplines providing emergency services, with greater changes seen especially in pandemic hospitals. OBJECTIVES: To evaluate the follow-up of patients un
Sao Paulo Med. J.. Publicado em: 2020-08
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12. Analysis of the impacts of slope angle variation on slope stability and NPV via two different final pit definition techniques
Abstract The traditionally and widely used Lerchs-Grossmann algorithm presents well-known limitations that newer propositions attempt to overcome. The direct block schedule (DBS) methodology, which has gained relevance with computational advances, obtains the final pit as a natural result of production sequencing, different from Lerchs-Grossmann-based algori
REM, Int. Eng. J.. Publicado em: 2020-03