In the past few years, Internet of Things (IoT) devices have evolved faster and use these is exceedingly increasing to make our daily activities easier than ever. However, numerous security flaws persist on IoT due fact that majority them lack memory computing resources necessary for adequate operations. As a result, are affected by variety attacks. A single attack network systems or can lead significant damages in data privacy. machine-learning techniques be applied detect this paper,...

Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking the multifactorial nature of injuries. This study introduces an automated identification prediction approach using machine learning, leveraging GPS data player-specific parameters. A sample 34 male players from a Portuguese first-division team was...

In a classical classification process, automatic sleep apnea detection involves creating and selecting the features, using prior knowledge, apply them to classifier. A different approach is applied in this paper, where Deep Belief Network used for feature extraction, without domain-specific then same network of apnea. The was created by stacking Restricted Boltzmann Machines. first two layers are autoencoder type last layer soft-max type. initial weights calculated unsupervised learning and,...

Obstructive sleep apnea (OSA) is a common disorder characterized by interrupted breathing during sleep. Because of the cost, complexity, and accessibility issue related to polysomnography, gold standard test for detection, automation diagnostic based on simpler method desired. Several signals can be used such as airflow electrocardiogram. However, reduction normally leads decrease in blood oxygen saturation level (SpO2). This signal usually measured pulse oximeter, sensor that cheap,...

The number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic continues, with new variants emerging. Therefore, to prevent virus from spreading, must be diagnosed soon possible. COVID-19 has had a devastating impact on people’s health and economy worldwide. For detection, reverse transcription-polymerase chain reaction testing benchmark. However, this test takes long time necessitates lot laboratory resources. A trend emerging address these limitations regarding use...

This study focuses on improving sentiment analysis in restaurant reviews by leveraging transfer learning and transformer-based pre-trained models. work evaluates the suitability of deep models for analyzing Natural Language Processing tasks Portuguese. It also explores viability utilizing edge devices tasks, considering their computational limitations resource constraints. Specifically, we employ bidirectional encoder representations from transformers robustly optimized BERT approach, two...

Abstract Wind direction nowcasting is crucial in various sectors, particularly for ensuring aviation operations and safety. In this context, the TELMo (Time-series Embeddings from Language Models) model, a sophisticated deep learning architecture, has been introduced work enhanced wind-direction nowcasting. Developed by using three years of data multiple stations complex terrain an international airport, incorporates horizontal u (east–west) v (north–south) wind components to significantly...

Specific information about types of appliances and their use in a specific time window could help determining details the electrical energy consumption information. However, conventional main power meters fail to provide any One best ways solve these problems is through non-intrusive load monitoring, which cheaper easier implement than other methods. developing classifier for deducing what kind are used at home difficult assignment, because system should identify appliance as fast possible...

This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, location known its complex patterns. By using data from network of six meteorological stations and deep learning techniques, the produced is capable predicting speed direction up to 30-minute ahead with 1-minute temporal resolution. The optimized architecture demonstrated robust predictive performance across all forecast horizons. For most challenging task,...

The purpose of the research is to evaluate different human emotions through Electroencephalogram (EEG) signal and receive information about internal changes brain state. paper presents detection emotion based on some salient features EEG signal. For this purpose, seven emotional states have been specified such as relax, thought, memory related, motor action, pleasant, fear, enjoying music. Several signals collected for these analyzed using frequency transform statistical measures. Different...

Repetitive respiratory disturbance during sleep is called Sleep Apnea Hypopnea Syndrome and causes various diseases. Different features classifiers have been used by different researchers to detect apnea. This study undertaken identify the better performing blood oxygen saturation subset using an Artificial Neural Network classifier for detection. A database of 8 subjects with one-minute annotation test proposed system. The optimized system has seven chosen from a total set sixty-one...

Sleep related disorders can severely disturb the quality of sleep. Among these disorders, obstructive sleep apnea (OSA) is highly prevalent and commonly undiagnosed. Polysomnography considered to be gold standard exam for OSA diagnosis. Even though this multi-parametric test provides accurate results, it time consuming, labor-intensive, expensive. A non-invasive easy self-assemble home monitoring device was developed address issues. The perform diagnosis at patient's a specialized technician...

The gold standard for assessment of sleep quality is the polysomnography, where physiological signals are used to generate both quantitative and qualitative measurements. Despite production highly accurate results, polysomnography a complex, uncomfortable, expensive process, inaccessible large group population. Home monitoring devices were developed address these issues, fitting growing perspective health care focusing on prevention wellness. objective this paper was develop an algorithm...

The electrocardiogram (ECG) has significant clinical importance for analyzing most cardiovascular diseases. ECGs beat morphologies, durations, and amplitudes vary from subject to diseases Therefore, ECG morphology-based modeling long-standing research interests. This work aims develop a simplified model based on minimum number of parameters that could correctly represent morphology in different cardiac dysrhythmias. A simple mathematical the sum two Gaussian functions is proposed. However,...