João Paulo Teixeira

Polytechnic Institute of Bragança | IPB · Departamento de Eletrotecnia

During the coronavirus disease 2019 (COVID-19) pandemic, various research disciplines collaborated to address the impacts of severe acute respiratory syndrome coronavirus-2 infections. This paper presents an interpretability analysis of a convolutional neural network-based model designed for COVID-19 detection using audio data. We explore the input...

Tourism destinations depend deeply on the contribution of residents, who play a crucial role as stakeholders. Obtaining insight into their perspectives is crucial for the success of the tourism industry. Hence, this study aimed to understand how residents in the cross-border region of the Iberian Meseta Reserve perceive tourism in their land. From...

In this study, we explore the capabilities of speaker recognition technology for biometric authentication developing speaker recognition-based access control systems and serving as a resource for future research and improvements in secure and efficient speaker identification solutions. We focused on developing and evaluating machine learning and de...

The market for Wearable Health Monitoring Systems (WHMS) has grown together with the demand for devices that offer greater medical reliability and lower cost. This study introduces a wearable system comprising conditioning blocks for electrocardiogram and surface electromyogram signals, an analog-to-digital converter, and wireless data transmission...

Using acoustic analysis to classify and identify speech disorders non-invasively can reduce waiting times for patients and specialists while also increasing the accuracy of diagnoses. In order to identify models to use in a vocal disease diagnosis system, we want to know which models have higher success rates in distinguishing between healthy and p...

The paper presents the comparison of accuracy in the Speech Emotion Recognition task using the Hamming and Hanning windows for framing the speech and determining the spectrogram to be used as input of a convolutional neural network. The detection of between 4 and 10 emotional states was tested for both windows. The results show significant differen...

This paper provides some comparisons of Automatic Speech Recognition (ASR) services for Portuguese that were developed in the scope of the Safe Cities project. ASR technology has enabled bi-directional voice-driven interfaces, and its demand in Portuguese is evident due to the language’s global prominence. However, the transcription process has com...

Natural parks and protected areas have been a significant subject of tourism studies. Understanding the image that visitants have of these areas is important to the planning process, and the analysis of online reviews is a methodology used in different investigations. TripAdvisor is the most used review aggregator in these studies. In this context,...

Pitch training is an important exercise for classical singers. This paper presents a Visual Feedback Technology (VFT) time system to improve pitch tuning. The objective is to present the developed helpful tool that allows in a didactic way to tune the voice and show the user the error due to the comparison between the voice produced and the target...

Voice pathologies are widespread in society. However, the exams are invasive and uncomfortable for the patient, depending on the doctor’s experience doing the evaluation. Classifying and recognizing speech pathologies in a non-invasive way using acoustic analysis saves time for the patient and the specialist while allowing analyzes to be objective...

Satisfaction is a widely studied issue in tourism as it provides an understanding of the performance of a tourism destination's offer, highlighting the most important features considered by tourists. The growth in tourism demand in natural areas also makes it an important factor in identifying visitor satisfaction, as sustainable planning of these...

Schizophrenia is a mental illness that affects an estimated 21 million people worldwide. The literature establishes that electroencephalography (EEG) is a well-implemented means of studying and diagnosing mental disorders. However, it is known that speech and language provide unique and essential information about human thought. Semantic and emotio...

The harmonic parameters Autocorrelation, Harmonic to Noise Ratio (HNR), and Noise to Harmonic Ratio are related to vocal quality, providing alternative measures of the harmonic energy of a speech signal. They will be used as input resources for an intelligent medical decision support system for the diagnosis of speech pathology. An efficient algori...

Purpose This study is dedicated to critically analysing research addressing human resource management (HRM) and the adoption of artificial intelligence (AI) with the purpose of driving development in the field of human resources (HR) at the strategic and managerial level. Design/methodology/approach A systematic literature review (SLR) was conduct...

This Special Issue was honored with six contribution papers embracing the subject of tourism forecasting [...]

In this work, research was done to understand what is needed to build a database to recognise emotions through speech. Some features that can highlight a good success rate for emotion recognition through speech were investigated. Also studied were some characteristics (symptoms) that can be associated with a specific emotional state. On the other h...

The use of wearable devices to monitor vital signs has become something usual, at the same time, here are an increasing demand in improving signal accuracy with a low power consumption. This work presents a conditioning circuit for electrocardiogram and surface electromyogram signals in a reliable way alongside filter and gain modules developed on...

Classifying and recognizing voice pathologies non-invasively using acoustic analysis saves patient and specialist time and can improve the accuracy of assessments. In this work, we intend to understand which models provide better accuracy rates in the distinction between healthy and pathological, to later be implemented in a system for the detectio...

In this article, a statistical analysis of the Harmonic to Noise Ratio (HNR) parameter was performed using the boxplot tool in the SPSS software, using the Cured Database with 901 individuals (707 pathological and 194 control) to create relevant groups, enabling the automatic identification of these dysfunctions. We analyzed whether the HNR paramet...

Accurate predictions of time series are increasingly required to support judgments in a variety of decisions. Several predictive models are available to support these predictions, depending on how each field offers a data variety with varied behavior. The use of artificial neural networks (ANN) at the beginning of the COVID-19 pandemic was signific...

For a food to be considered functional it is necessary to prove that it has microorganisms in its composition. In order to determine the presence of microorganisms in a food, laboratory analyzes can be carried out using of Petri dishes, which must pass through an incubation period, to then manually count the number of bacterial colonies that are pr...

Background Governments in Latin America are constantly facing the problem of managing scarce resources to satisfy alternative needs, such as housing, education, food, and healthcare security. Those needs, combined with increasing crime levels, require financial resources to be solved. Objective The objective of this review was to characterizar the...

During the outbreak of COVID-19 pandemic, several research areas joined efforts to mitigate the damages caused by SARS-CoV-2. In this paper we present an interpretability analysis of a convolutional neural network based model for COVID-19 detection in audios. We investigate which features are important for model decision process, investigating spec...

Background and aims: Laparoscopic and endoscopic cooperative surgery (LECS) combines advantages of endoscopy and laparoscopy in order to resect upper gastrointestinal lesions. Our aim was to evaluate the efficacy and safety of LECS in patients with EGJ (esophagogastric junction), gastric and duodenal lesions, as well as to compare LECS with pure e...

Background: Alzheimer's Disease (AD) stands out as one of the main causes of dementia worldwide and it represents around 65% of all dementia cases, affecting mainly elderly people. AD is composed of three evolutionary stages: Mild Cognitive Impairment (MCI), Mild and Moderate AD (ADM) and Advanced AD (ADA). It is crucial to create a tool for assis...

Speech provides a natural way for human–computer interaction. In particular, speech synthesis systems are popular in different applications, such as personal assistants, GPS applications, screen readers and accessibility tools. However, not all languages are on the same level when in terms of resources and systems for speech synthesis. This work co...

Vocal acoustic analysis is becoming a useful tool for the classification and recognition of laryngological pathologies. This technique enables a non-invasive and low-cost assessment of voice disorders, allowing a more efficient, fast, and objective diagnosis. In this work, ANN and SVM were experimented on to classify between dysphonic/control and v...

The new Coronavirus, responsible for the COVID-19 disease, is the most discussed topic in the current days, and the forecast numbers of new cases and deaths are the most important source of data in governmental decision-making. The present work presents a prediction model with two different approaches concerning the input data, by using Artificial...

Vietnam has experienced a tourism expansion over the last decade, proving itself as one of the top tourist destinations in Southeast Asia. The country received more than 18 million international tourists in 2019, compared to only 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and incomes for Vietnam’s tour...

Schizophrenia is a chronic mental illness, characterized by the loss of the notion of reality, failing to distinguish it from the imaginary. It affects the patient in life’s major areas, such as work, interpersonal relationships, or self-care, and the usual treatment is performed with the help of anti-psychotic medication, which targets primarily t...

The use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation proced...

The use of Artificial Neural Networks (ANN) is a great contribution to medical studies since the application of forecasting concepts allows the analysis of future diseases propagations. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures...

This work proposes the application of a new electroencephalogram (EEG) signal processing tool - the lacsogram - to characterize the Alzheimer's disease (AD) activity and to assist on its diagnosis at different stages: Mild Cognitive Impairment (MCI), Mild and Moderate AD (ADM) and Advanced AD (ADA). Statistical analyzes are performed to lacstral di...

The World's health systems are now facing a global problem known as Alzheimer's disease (AD) that mainly affects the elderly. The goal of this work is to perform a classification methodology skilled with Artificial Neural Networks (ANN) to improve the discrimination accuracy amongst patients at AD different stages comparatively to the state-of-art....

Alzheimer's Disease (AD) is considered one of the most debilitating illness in modern societies and the leading cause of dementia. This study is a new approach to detect early AD Electroencephalogram (EEG) temporal events in order to improve early AD diagnosis. For that, Self-Organized Maps (SOM) were used, and it was found that there are sequences...

Atrial fibrillation (AF) is the most common cardiac anomaly and one that potentially threatens human life. Due to its relation to a variation in cardiac rhythm during indeterminate periods, long-term observations are necessary for its diagnosis. With the increase in data volume, fatigue and the complexity of long-term features make analysis an incr...

In data mining problems, the high dimensionality of the input features can affect the performance of the process. In this way, the features selection methods appear as a solution to the problems encountered when analyzing databases with large dimensions. This article presents the implementation of the Pearson’s linear correlation, ReliefF, Welch’s...

With the accelerated spread of COVID-19 worldwide and its potentially fatal effects on human health, the development of a tool that effectively describes and predicts the number of infected cases and deaths over time becomes relevant. This makes it possible for administrative sectors and the population itself to become aware and act more precisely....

The cardiovascular electrocardiogram signal presents noises that include low and high frequency components that interfere in the automatic identification and classification of the QRS peaks, P and T wave. Pre-processing techniques based on moving average and detrend function was used to smooth the ECG signal and remove local tendencies. Noise filte...

The Artificial Neural Network (ANN) is a computer technique that uses a mathematical model to represent a simpler form of the biologic neural structure. It is formed by many processing units and its intelligent behavior comes from the iterations between these units. One application of the ANN is for time series prediction algorithms, where the netw...

Schizophrenia is a complex and disabling mental disorder estimated to affect 21 million people worldwide. Electroencephalography (EEG) has proven to be an excellent tool to improve and aid the current diagnosis of mental disorders such as schizophrenia. The illness is comprised of various disabilities associated with sensory processing and percepti...

Jitter is an acoustic parameter used as input for intelligent systems for the diagnosis of speech related pathologies. This work has the objective to improve an algorithm that allows to extract vocal parameters, and thus improve the accuracy measurement of absolute jitter parameter. Some signals were analyzed, where signal to signal was compared in...

Identifying plant species is an important activity in specie control and preservation. The identification process is carried out mainly by botanists, consisting of a comparison of already known specimens or using the aid of books, manuals or identification keys. Artificial Neural Networks have been shown to perform well in classification problems a...

This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from...

Sports tourism is an economic and social activity that crosses sport and tourism, in which the economic tourist activity prevails over the sport experience. The main objective of the present work is to evaluate the importance of sport events for the tourism development of a region, in this case the cycling race tour Volta a Portugal, in the municip...

Introduction Colorectal cancer is one of the neoplasms with the greatest social impact. Given the great molecular heterogeneity and diversity of pathophysiological mechanisms, it is difficult to define prognostic factors that could guide therapy. Objectives To identify the molecular prognostic factors that may be of interest in clinical practice a...

Background: Accelerated globalisation has substantially contributed to the rise of emerging markets worldwide. The G7 and Emerging Markets Seven (EM7) behaved in significantly different macroeconomic ways before, during, and after the 2008 Global Crisis. Average real GDP growth rates remained substantially higher among the EM7, while unemployment...

Voice synthesis systems are popular in different applications, such as personal assistants, GPS applications, screen readers and accessibility tools. Voice provides an natural way for human-computer interaction. However, not all languages are in the same level when accounting resources and systems for voice synthesis. This work consists of the crea...

Background: Accelerated globalization has substantially contributed to the rise of emerging markets worldwide. The G7 and Emerging Markets Seven (EM7) behaved in significantly different macroeconomic ways before, during, and after the 2008 Global Financial Crisis. Average real GDP growth rates remained substantially higher among the EM7, while unem...

The paper deals with India’s Medical tourism analysis and forecasting, applying two time series forecasting models, for monthly data spreading over 2014 to 2017. Medical tourism worldwide and particularly in India is on rise. Figures of medical tourist arrivals in India for 2014, 2015 and 2016 denotes a significant growth. Several measures have bee...

Vocal acoustic analysis is becoming a useful tool for the classification and recognition of laryngological pathologies. This technique enables a non-invasive and low-cost assessment of voice disorders, allowing a more efficient, fast, and objective diagnosis. In this work, ANN and SVM were experimented on to classify between dysphonic/control and v...

This paper presents a methodology for winding stator fault detection of induction motors, using an external search coil, which is a noninvasive technique and can be applied during motor operation. The dispersion magnetic flux of the motor operating in abnormal conditions induces a voltage in the search coil that differs from a reference pattern cor...

This study examined the differences in health spending within the World Health Organization (WHO) Europe region by comparing the EU15, the EU post-2004, CIS, EU Candidate and CARINFONET countries. The WHO European Region (53 countries) has been divided into the following sub-groups: EU15, EU post-2004, CIS, EU Candidate countries and CARINFONET cou...

Bees are insects that attack, to protect the hive, when they feel threatened. The main objective in this paper was to build an electronic device capable of repelling bees. Thus, a study of the hearing thresholds, of honey bees, has been developed to find out the frequencies range are most sensitive. This knowledge can be important to identify a fre...

This paper describes the construction and organization of a database of speech parameters extracted from a speech database. This article intends to inform the community about the existence of this database for future research. The database includes parameters extracted from sounds produced by patients distributed among 19 diseases and control subje...

The classification of pathological diseases with the implementation of concepts of Deep Learning has been increasing considerably in recent times. Among the works developed there are good results for the classification in sustained speech with vowels, but few related works for the classification in continuous speech. This work uses the German Saarb...

In some of the processes used in data analysis, such as the recognition of pathologies and pathological subjects, the presence of anomalous instances in the dataset is an unfavorable situation that can lead to misleading results. This article presents a function that implements the identification of anomalies in dataset using the boxplot and standa...

As the sports betting industry and technology have grown on a large scale, predicting the outcome of a sports match using technologies approach is now crucial. In fact, humans have a certain limitation when processing a large set of information. However, Artificial Intelligence techniques can overcome this issue. Furthermore, sports have a great am...

The objective of the article is to investigate the evolution of the application of Artificial Intelligence (AI) in the area of Human Resources (HR). It presents a panorama of the research that used AI in the area of HR, through the quantitative descriptive analysis of journals and proceedings, registered in the base of the Library of Online Knowled...

The World's health systems are now facing a global problem known as Alzheimer's disease (AD) that mainly affects the elderly. The goal of this work is to perform a classification methodology skilled with Artificial Neural Networks (ANN) to improve the discrimination accuracy amongst patients at AD different stages comparatively to the state-of-art....

Harmonic to Noise Ratio (HNR) measures the ratio between periodic and non-periodic components of a speech sound. It has become more and more important in the vocal acoustic analysis to diagnose pathologic voices. The measure of this parameter can be done with Praat software that is commonly accept by the scientific community has an accurate measure...

The diagnosis of pathologies using vocal acoustic analysis has the advantage of been noninvasive and inexpensive technique compared to traditional technique in use. In this work the SVM were experimentally tested to diagnose dysphonia, chronic laryngitis or vocal cords paralysis. Three groups of parameters were experimented. Jitter, shimmer and HNR...