Viviana Cocco Mariani
YOU?
Author Swipe
View article: Fault Detection in Power Distribution Systems Using Sensor Data and Hybrid YOLO with Adaptive Context Refinement
Fault Detection in Power Distribution Systems Using Sensor Data and Hybrid YOLO with Adaptive Context Refinement Open
Ensuring the reliability of power transmission systems depends on the accurate detection of defects in insulators, which are subject to environmental degradation and mechanical stress. Traditional inspection methods are time-consuming and …
View article: Fault Detection in Power Distribution Systems Using Sensor Data and Hybrid YOLO with Adaptive Context Refinement
Fault Detection in Power Distribution Systems Using Sensor Data and Hybrid YOLO with Adaptive Context Refinement Open
Ensuring the reliability of power transmission systems hinges on the accurate detection of defects in insulators, which are vulnerable to environmental degradation and mechanical stress. Traditional inspection methods are time-consuming an…
View article: Wind speed forecasting approach using conformal prediction and feature importance selection
Wind speed forecasting approach using conformal prediction and feature importance selection Open
Wind energy is a rising renewable energy source that plays an important role in the transition to a more sustainable energy system. Variation in wind power generation is one of the main challenges facing this energy source. Wind forecastin…
View article: Critical Extraction Parameters for Maximizing Oil Yield from Spent Coffee Grounds
Critical Extraction Parameters for Maximizing Oil Yield from Spent Coffee Grounds Open
Coffee is one of the most consumed beverages worldwide, producing approximately 6 million tons of spent coffee grounds (SCG) annually, which are often discarded in landfills. SCG contains 12–16% dry basis oil, which can be recovered in var…
View article: Deep Learning Approach for Automatic Heartbeat Classification
Deep Learning Approach for Automatic Heartbeat Classification Open
Arrhythmia is an irregularity in the rhythm of the heartbeat, and it is the primary method for detecting cardiac abnormalities. The electrocardiogram (ECG) identifies arrhythmias and is one of the methods used to diagnose cardiac issues. T…
Evaluation of the economic viability of essential oil production from spent coffee grounds Open
Coffee consumption generates substantial amounts of spent coffee grounds (SCG), a residue with a high lipid content (12-16%) and significant potential for valorization. This study evaluates the economic feasibility of producing essential o…
View article: Neural Hierarchical Interpolation Time Series (NHITS) for Reservoir Level Multi-Horizon Forecasting in Hydroelectric Power Plants
Neural Hierarchical Interpolation Time Series (NHITS) for Reservoir Level Multi-Horizon Forecasting in Hydroelectric Power Plants Open
Energy planning in systems heavily influenced by hydroelectric power is based on assessing the availability of water in the future. In Brazil, based on the soil moisture active passive, the National Electricity System Operator defines elec…
View article: Spatiotemporal Wind Energy Forecasting: A Comprehensive Survey and a Deep Equilibrium-Based Case Study With StemGNN
Spatiotemporal Wind Energy Forecasting: A Comprehensive Survey and a Deep Equilibrium-Based Case Study With StemGNN Open
Accurate spatiotemporal wind energy forecasting is essential for ensuring grid stability and maximizing the efficiency of renewable energy systems. This paper addresses the challenge of modeling the complex spatial and temporal dependencie…
View article: Audio-Based Engine Fault Diagnosis with Wavelet, Markov Blanket, ROCKET, and Optimized Machine Learning Classifiers
Audio-Based Engine Fault Diagnosis with Wavelet, Markov Blanket, ROCKET, and Optimized Machine Learning Classifiers Open
Engine fault diagnosis is a critical task in automotive aftermarket management. Developing appropriate fault-labeled datasets can be challenging due to nonlinearity variations and divergence in feature distribution among different engine k…
View article: Hypertuned temporal fusion transformer for multi-horizon time series forecasting of dam level in hydroelectric power plants
Hypertuned temporal fusion transformer for multi-horizon time series forecasting of dam level in hydroelectric power plants Open
This paper addresses the challenge of predicting dam level rise in hydroelectric power plants during floods and proposes a solution using an automatic hyperparameters tuning temporal fusion transformer (AutoTFT) model. Hydroelectric power …
View article: Random Convolutional Kernel Transform with Empirical Mode Decomposition for Classification of Insulators from Power Grid
Random Convolutional Kernel Transform with Empirical Mode Decomposition for Classification of Insulators from Power Grid Open
The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolut…
View article: Random Convolutional Kernel Transform with Empirical Mode Decomposition for Medium Voltage Insulator Classification based on Ultrasound Sensor
Random Convolutional Kernel Transform with Empirical Mode Decomposition for Medium Voltage Insulator Classification based on Ultrasound Sensor Open
The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolut…
View article: Optimized hybrid ensemble learning approaches applied to very short-term load forecasting
Optimized hybrid ensemble learning approaches applied to very short-term load forecasting Open
The significance of accurate short-term load forecasting (STLF) for modern power systems' efficient and secure operation is paramount. This task is intricate due to cyclicity, non-stationarity, seasonality, and nonlinear power consumption …
View article: Decoding Electroencephalography Signal Response by Stacking Ensemble Learning and Adaptive Differential Evolution
Decoding Electroencephalography Signal Response by Stacking Ensemble Learning and Adaptive Differential Evolution Open
Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities regarding external stimuli, and its signals compose a nonlinear dynamical system. There are many difficulties associated with EEG analysis. For example, …
View article: Video-Based Human Activity Recognition Using Deep Learning Approaches
Video-Based Human Activity Recognition Using Deep Learning Approaches Open
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people’s day-to-day lives. Multiple people and things may be seen acting in the …
View article: Group Method of Data Handling Using Christiano–Fitzgerald Random Walk Filter for Insulator Fault Prediction
Group Method of Data Handling Using Christiano–Fitzgerald Random Walk Filter for Insulator Fault Prediction Open
Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time…
View article: Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model
Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model Open
The predictive maintenance of electrical machines is a critical issue for companies, as it can greatly reduce maintenance costs, increase efficiency, and minimize downtime. In this paper, the issue of predicting electrical machine failures…
View article: Structure Optimization of Ensemble Learning Methods and Seasonal Decomposition Approaches to Energy Price Forecasting in Latin America: A Case Study about Mexico
Structure Optimization of Ensemble Learning Methods and Seasonal Decomposition Approaches to Energy Price Forecasting in Latin America: A Case Study about Mexico Open
The energy price influences the interest in investment, which leads to economic development. An estimate of the future energy price can support the planning of industrial expansions and provide information to avoid times of recession. This…
View article: Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction
Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction Open
Insulators installed outdoors are vulnerable to the accumulation of contaminants on their surface, which raise their conductivity and increase leakage current until a flashover occurs. To improve the reliability of the electrical power sys…
View article: Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices
Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices Open
The cost of electricity and gas has a direct influence on the everyday routines of people who rely on these resources to keep their businesses running. However, the value of electricity is strongly related to spot market prices, and the ar…
View article: Beta-hCG Test Demand Forecasting Using Stacking Ensemble-Learning and Machine Learning Approaches
Beta-hCG Test Demand Forecasting Using Stacking Ensemble-Learning and Machine Learning Approaches Open
Demand forecasting is essential for decision-making, since these forecasts are important inputs for strategic management decisions. In this context, the contribution of this study is to propose a hybrid forecasting framework that combines …