A5082488845- Energy Load and Power Forecasting
- Neural Networks and Applications
- Power Quality and Harmonics
- Electricity Theft Detection Techniques
- Smart Grid Energy Management
- Stock Market Forecasting Methods
- Building Energy and Comfort Optimization
- Blind Source Separation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Power Transformer Diagnostics and Insulation
- Fuzzy Logic and Control Systems
- COVID-19 diagnosis using AI
- Psychology and Mental Health
- Machine Fault Diagnosis Techniques
- Palliative and Oncologic Care
- Medical Imaging Techniques and Applications
- Health, Nursing, Elderly Care
- Software System Performance and Reliability
- AI in cancer detection
- Digital Imaging for Blood Diseases
- Network Security and Intrusion Detection
- Image and Signal Denoising Methods
- Healthcare during COVID-19 Pandemic
- Spam and Phishing Detection
- Anomaly Detection Techniques and Applications
Universidade Estadual Paulista (Unesp)
2015-2024
Federal Institute of São Paulo
2020
Instituto Federal de Educação, Ciência e Tecnologia de Brasília
2019
Agência Nacional de Energia Elétrica
2015
A atuação de equipes multidisciplinares no Sistema Único Saúde (SUS) tem sido fundamental para a qualidade da assistência e integralidade do cuidado. Este estudo como objetivo analisar importância dessas na melhoria dos resultados clínicos pacientes, bem os desafios as estratégias sua consolidação. pesquisa foi realizada por meio uma revisão literatura, com análise artigos publicados nos últimos cinco anos em bases dados científicos. Os apontam que integrada profissionais diferentes áreas...
A Escala de Desenvolvimento Infantil Bayley-III é considerada padrão-ouro para avaliação do desenvolvimento em crianças 16 dias a 42 meses, abrangendo domínios cognitivo, linguístico, motor, socioemocional e adaptativo. Este estudo revisou procedimentos psicométricos adaptações transculturais da Bayley-III, com foco no Brasil. Realizou-se uma revisão escopo, seguindo diretrizes PRISMA, buscas PubMed, Scopus SciELO. Foram incluídos artigos que abordaram validade (conteúdo, construto,...
Electric energy demand in residences represents around 30% of the global demand. This requires a detailed knowledge about electrical load patterns, leading to change final consumer behavior reduce general work uses fuzzy system, considering quantity occupants Brazilian family different periods day aiming obtain residential electric profile.
Considering the increasing electrical energy demand in residences, it is necessary to know detailed pattern of electricity use, change behavior final consumer and reduce global consumption. Knowing load curve profile advance very important for detecting peaks valleys habits consumption, principally during periods when prices are lower, i.e., following power industry opportunities. This work studies how behaves individually, as well identifies similarities with other consumers. Thus, we...
COVID-19, caused by the SARS-CoV-2 virus, has spread around world and killed 6.9 million people. Rapid accurate diagnosis is essential for preventing controlling disease, reducing transmission consequently saving lives. RT-PCR gold standard test used to detect disease. However, expensive result time-consuming, which makes mass testing difficult, especially in countries with limited resources. In addition, high analytical specificity low diagnostic sensitivity, leads false-negative results....
The prediction of electric charges is essential in the power system, because it establishes when and how much generation, transmission distribution capacity must be arranged to meet expected load without interruptions supply. Therefore, more accurate, reliable fast results, better quality forecast will be. This paper proposes an approach that performs considering several points electricity network (multinodal forecast), where different types consumers are considered (industrial, commercial...
Forecasting electric demand is a fundamental part of the power systems, since, it provides useful information on several aspects network, acting directly in planning generation, transmission and distribution energy consequently economy resources. This work seeks to explore application artificial neural networks prediction load considering points electrical network (multinodal prediction). A model based adaptive resonance theory (ART), called Euclidean ARTMAP was used. methodology can obtain...
Metodologias híbridas estão sendo cada vez mais utilizadas para realizar a previsões de séries temporais. Neste trabalho apresentam-se resultados uma série temporal demanda energia elétrica companhia setor elétrico, proposto um modelo no qual são utilizados o método stepwise seleção variáveis com auxílio da regressão linear múltipla e rede neural ARTMAP Fuzzy.
Medical image segmentation is an increasingly popular area of research in medical imaging processing and analysis. However, many researchers who are new to the field struggle with basic concepts. This tutorial paper aims provide overview fundamental concepts imaging, a focus on Magnetic Resonance Computerized Tomography. We will also discuss deep learning algorithms, tools, frameworks used for tasks, suggest best practices method development Our includes sample tasks using public data,...
Realizar a previsão de cargas elétricas é indispensável do ponto vista prático e econômico, pois através dessa que possível fornecer energia forma segura continua, sem interrupções no fornecimento. Na literatura maioria dos trabalhos realiza carga elétrica considera demanda global, isto soma consumo total energia. Este trabalho propõe realizar ao longo barramentos um sistema distribuição (previsão multimodal). O método pro-posto utiliza uma rede neural ARTMAP Fuzzy para nas subestações...