Papers by Demostenes Rodriguez
Wireless Access Point Positioning Optimization
2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2019
This work presents the development of a wireless Access Point (AP) placement software that uses m... more This work presents the development of a wireless Access Point (AP) placement software that uses microwave signal propagation models. We use the Simulated Annealing metaheuristic, to improve the signal coverage according to the physical features of the architectural floor plan. In the experiments, a Graphics Processing Unit (GPU) with CUDA is used to parallelize the simulations, speeding up the runtime required. It is worth noting that our software makes possible to test the provisions of APs without the operational cost of having to move them physically. It proposes a spatial arrangement of APs that provides a greater coverage with usable signal intensity within the simulated environment. Using a limited amount of APs, the test case results showed that it is possible to obtain a significant improvement in the coverage of the Wi-Fi signal by adjusting the APs positions to the metaheuristic proposed solution. In addition, our software is capable of performing simulations with an increasing number of APs if the current quantity is not enough to achieve better quality and signal coverage.
Análise afetiva de frases extraídas das redes sociais
As Redes Sociais atuais estao repletas de informacoes sobre todo e qualquer assunto, as pessoas e... more As Redes Sociais atuais estao repletas de informacoes sobre todo e qualquer assunto, as pessoas expressam suas opinioes e consequentemente sentimentos em cada frase postada ou compartilhada. Este capitulo pretende mostrar ao usuario a importância de se compreender e estudar a analise de sentimentos e tambem a analise afetiva de uma pessoa a fim de extrair informacoes, criticas e sugestoes implicitas e explicitas nos comentarios das pessoas nas Redes Sociais. As Redes Sociais e um ambiente rico de informacoes e neste mini-curso mostraremos conceitos, funcionamento e exemplos de casos de uso, comprovando a utilidade atual da analise afetiva das frases das pessoas contidas na Internet.
Monitoring and Classification of Emotions in Elderly People
2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2019
Daily, people have access to various multimedia content, that can change their emotional state an... more Daily, people have access to various multimedia content, that can change their emotional state and it can cause an increase in their heart rate. These emotional changes are troubling in the elderly people. Thus, this work aims to classify emotions by machine learning and monitor the emotions of the elderly through the measurement of heart rate, using portable sensors of low cost and easily to use. For this, a framework is implemented, which presents to the user messages of attention and danger according to emotion and heart rate when video contents are presented to the elderly people. Also, the audio transcription of the videos are performed and the sentiment analysis is performed. Thus, when detecting a sudden increase in heart rate and the video presents a negative sentiment polarity, then the proposed solution presents a video of calm or happy content, according to the user's pre-registered preference. The experimental results showed that the classification system performed by a deep learning model obtained values of 97% of accuracy for classifying the disgust emotion and the heart rate level decreased with the proposed framework. Additionally, 93.75% of the users considered the system efficient.
Journal of communications software and systems, 2020
Current implementations of 5G networks consider higher frequency range of operation than previous... more Current implementations of 5G networks consider higher frequency range of operation than previous telecommunication networks, and it is possible to offer higher data rates for different applications. On the other hand, atmospheric phenomena could have a more negative impact on the transmission quality. Thus, the study of the transmitted signal quality at high frequencies is relevant to guaranty the user ́s quality of experience. In this research, the recommendations ITU-R P.838-3 and ITU-R P.676-11 are implemented in a network scenario, which are methodologies to estimate the signal degradations originated by rainfall and atmospheric gases, respectively. Thus, speech signals are encoded by the AMR-WB codec, transmitted and the perceptual speech quality is evaluated using the algorithm described in ITU-T Rec. P.863, mostly known as POLQA. The novelty of this work is to propose a non-intrusive speech quality classifier that considers atmospheric phenomena. This classifier is based on ...
Melhora de uma métrica de qualidade de vídeo utilizando o parâmetro correspondente ao tipo de conteúdo de vídeo
Journal of Signal Processing Systems, 2021
The SARS-CoV-2 virus causes a respiratory disease in humans, known as COVID-19. The confirmatory ... more The SARS-CoV-2 virus causes a respiratory disease in humans, known as COVID-19. The confirmatory diagnostic of this disease occurs through the real-time reverse transcription and polymerase chain reaction test (RT-qPCR). However, the period of obtaining the results limits the application of the mass test. Thus, chest X-ray computed tomography (CT) images are analyzed to help diagnose the disease. However, during an outbreak of a disease that causes respiratory problems, radiologists may be overwhelmed with analyzing medical images. In the literature, some studies used feature extraction techniques based on CNNs, with classification models to identify COVID-19 and non-COVID-19. This work compare the performance of applying pre-trained CNNs in conjunction with classification methods based on machine learning algorithms. The main objective is to analyze the impact of the features extracted by CNNs, in the construction of models to classify COVID-19 and non-COVID-19. A SARS-CoV-2 CT data-set is used in experimental tests. The CNNs implemented are visual geometry group (VGG-16 and VGG-19), inception V3 (IV3), and EfficientNet-B0 (EB0). The classification methods were k-nearest neighbor (KNN), support vector machine (SVM), and explainable deep neural networks (xDNN). In the experiments, the best results were obtained by the EfficientNet model used to extract data and the SVM with an RBF kernel. This approach achieved an average performance of 0.9856 in the precision macro, 0.9853 in the sensitivity macro, 0.9853 in the specificity macro, and 0.9853 in the F1 score macro.
IEEE Access, 2019
Communication service providers use specialized solutions to evaluate the quality of their servic... more Communication service providers use specialized solutions to evaluate the quality of their services. Also, different mechanisms that increase network robustness are incorporated in current communication systems. One of the most accepted techniques to improve transmission performance is the MIMO system. In communication services, voice quality is important to determine the user's quality of experience. Nowadays, different speech quality assessment methods are used, one of them is the parametric method that is used for network planning purposes. The ITU-T Rec. G107.1 is the most accepted model for wide-band communication systems. However, it does not consider the degradations occurring in a wireless network nor the quality improvement, caused by the MIMO systems. Thus, we propose a speech quality model, based on wireless parameters, such as signal-to-noise ratio, Doppler shift, MIMO configurations, and different modulation schemes. Also, real speech signals encoded by 3 operation modes of the AMR-WB codec are used in test scenarios. The resulting speech samples were evaluated by the algorithm described in ITU-T Rec. P.862.2, which scores are used as a reference. With these results, a wireless function, named I W −M that relates the wireless network parameters with speech quality is proposed and inserted into the wide-band E-model algorithm. It is worth noting that the main novelty of the proposed I W −M is the consideration of the quality improvement incorporated by MIMO systems with different antenna array configurations. The performance validation results demonstrated that the inclusion of I W −M values into the R global score determined a reliable model, reaching a Pearson correlation coefficient and a normalized RMSE of 0.976 and 0.144, respectively. INDEX TERMS Speech quality, wireless communications, MIMO systems, antenna arrays, fading channels, parametric models, E-model.
IEEE Access, 2017
Social networks have a large amount of data available, but often, people do not provide some of t... more Social networks have a large amount of data available, but often, people do not provide some of their personal data, such as age, gender, and other demographics. Although the sentiment analysis uses such data to develop useful applications in people's daily lives, there are still failures in this type of analysis, either by the restricted number of words contained in the word dictionaries or because they do not consider the most diverse parameters that can influence the sentiments in a sentence; thus, more reliable results can be obtained, if the users profile information and their writing characteristics are considered. This research suggests that one of the most relevant parameter contained in the user profile is the age group, showing that there are typical behaviors among users of the same age group, specifically, when these users write about the same topic. A detailed analysis with 7000 sentences was performed to determine which characteristics are relevant, such as, the use of punctuation, number of characters, media sharing, topics, among others; and which ones can be disregarded for the age groups classification. Different learning machine algorithms are tested for the classification of the teenager and adult age group, and the deep convolutional neural network had the best performance, reaching a precision of 0.95 in the validation tests. Furthermore, in order to validate the usefulness of the proposed model for classifying age groups, it is implemented into the enhanced sentiment metric (eSM). In the performance validation, subjective tests are performed and the eSM with the proposed model reached a root mean square error and a Pearson correlation coefficient of 0.25 and 0.94, respectively, outperforming the eSM metric, when the age group information is not available. INDEX TERMS Social network services, sentiment analysis, machine learning, text analysis, artificial neural networks, deep network.
This paper presents a method for determining the quality of a Voice over IP communication using m... more This paper presents a method for determining the quality of a Voice over IP communication using machine learning techniques. The solution proposed uses historical values of network parameters and communication quality in order to train the different learning algorithms. After that, these algorithms are able to find the quality of the Voice over IP communication based on network parameters of a specific period of time. Intelligent and other machine learning algorithms take as input a baseline file that contains some values of network parameters and voice coding, associating an index quality for each scenario according to ITU-T Recommendation G.107. The tests were performed in an emulated network environment, totally isolated and controlled with real traffic of voice and realistic IP network parameters. The quality ratings obtained for the learning algorithms in all the scenarios were corroborated with the results of the algorithm of ITU-T Recommendation P.862. The results show the reliability of the four learning algorithms used on the tests: Decision Trees (J.48), Neural Networks (Multilayer Perceptron), Sequential Minimal Optimization (SMO) and Bayesian Networks (Naive). The highest value of reliability for determining the quality of the Voice over IP communications was 0.98 with the use of the Decision Trees Algorithm. These results demonstrate the validity of the method proposed.
Impact of FEC codes on speech communication quality using WB E-model algorithm
2019 Wireless Days (WD), 2019
In current communication systems, forward Error Correction (FEC) codes are used to decrease the i... more In current communication systems, forward Error Correction (FEC) codes are used to decrease the information losses in the transmission channel to improve the signal quality in the reception point. The speech quality is affected by many factors being packet losses one of the most important. Currently, there are different speech quality assessment methods; for planning purposes, E-model algorithm is the most representative. However, it does not consider wireless network characteristics and techniques. Based on this fact, the main contribution of this work is to adapt the wide-band (WB) E-model algorithm to be able to evaluate the impact of FEC codes on speech quality. For this purpose, a function named GFECx(Ms,SNR) is proposed that quantifies the quality gain reached by FEC codes at different wireless channel conditions. This function is inserted into Ie,eff,WB impairment factor of the WB E-model algorithm. Experimental results demonstrated that the proposed solution gets a high corr...
O Uso da Rede Neural Convolucional como Classificador de Emoções em um Sistema de Recomendação de Música
Atualmente, as redes sociais tem sido utilizadas por seus usuarios e exploradas por mecanismos de... more Atualmente, as redes sociais tem sido utilizadas por seus usuarios e exploradas por mecanismos de sistemas de medicao de qualidade e recomendacao de produtos e servicos. Os Sistemas de Recomendacao (RS) utilizaram os dados das redes sociais e, em paralelo, aplicaram o sentimento e a analise afetiva em tais dados. No entanto, ainda ha uma preocupacao em aumentar a precisao do sentimento e a analise afetiva. Este artigo apresenta uma RS, que extrai os textos dos usuarios das redes sociais e sugere estilos musicais baseados na analise de sentimentos por abordagem lexical e baseados na analise afetiva atraves da aprendizagem de maquina. O algoritmo de Convolutional Neural Network utilizado para a classificacao da emocao de felicidade, tristeza, raiva, medo, repulsa e surpresa apresentou uma precisao maior do que a encontrada em trabalhos relacionados. Os resultados da classificacao do F-Measure foram de 0,98 e 0,96 para a emocao de tristeza e raiva, respectivamente. Alem disso, a RS foi...
Coherent detection-based photonic radar for autonomous vehicles under diverse weather conditions
PLOS ONE
Autonomous vehicles are regarded as future transport mechanisms that drive the vehicles without t... more Autonomous vehicles are regarded as future transport mechanisms that drive the vehicles without the need of drivers. The photonic-based radar technology is a promising candidate for delivering attractive applications to autonomous vehicles such as self-parking assistance, navigation, recognition of traffic environment, etc. Alternatively, microwave radars are not able to meet the demand of next-generation autonomous vehicles due to its limited bandwidth availability. Moreover, the performance of microwave radars is limited by atmospheric fluctuation which causes severe attenuation at higher frequencies. In this work, we have developed coherent-based frequency-modulated photonic radar to detect target locations with longer distance. Furthermore, the performance of the proposed photonic radar is investigated under the impact of various atmospheric weather conditions, particularly fog and rain. The reported results show the achievement of significant signal to noise ratio (SNR) and rec...
Quantifying the Quality Improvement of MIMO Transmission Systems in VoIP Communication
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
Currently, Voice over IP (VoIP) communication service is widely used mainly because its lower cos... more Currently, Voice over IP (VoIP) communication service is widely used mainly because its lower cost. However, the quality of a VoIP communication is lower than a fixed-line communication due to network degradations. In this context, the objective of this work is to evaluate the quality of voice communications that undergo degradations in the wireless interface, and how MIMO technology helps to improve the voice signal quality. For this, a simulator named WVoIPSim is built, in which different modulation schemes, an error correction coding and different noise levels in wireless channel are implemented. The resulting speech signal, at the receiver, is analyzed by the ITU-T Recommendations P.862 and P.563, in which P.862 is used as reference. Experimental results show that there is a high correlation between MIMO system configurations and speech quality scores. Based on these results, different MIMO configurations for different network conditions is proposed in order to guarantee a MOS score higher than 4.0.
A Recommendation System for Shared-Use Mobility Service
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
Nowadays, shared mobility service is a trend in many countries. It tends to grow even more becaus... more Nowadays, shared mobility service is a trend in many countries. It tends to grow even more because of its low cost, the mitigation of both traffic and pollution, and due to the spreading of several shared-use mobility applications on mobile devices. As seen in other services, the success is based on the satisfaction level attained by users. Hence, if a ride is shared between people with similar preferences, users will feel more comfortable and safer. However, finding users with similar preferences is still a challenge in shared-use mobility services. In this context, this research shows that using some basic user information, such as gender, age, and relationship, extracted from Online Social Networks(OSN), and also some preferences, it is possible to determine if the user wants to share a vehicle with people with specific characteristics. Thus, as contribution, it is possible to classify users of similar preferences, automatically, to improve their ride experience. The classification was performed through machine learning algorithms, in which a Discriminative Restricted Boltzmann Machine(DRBM) algorithm reaches a correct classified instance of 94.5% and F-Measure of 0.93 for the option of sharing a ride with a person with similar hobby. Then, a Recommendation System(RS) is proposed, which efficiency is compared with a basic RS; they reached a Pearson Correlation Coefficient of 0.96 and 0.79, respectively; highlighting the importance of considering user preferences. Also, it is important to note that this study can be extended for other sharing services.
Improving a Parametric Model for Speech Quality Assessment in Wireless Communication Systems
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
Telecommunication operators need tools to evaluate and improve the quality of the their services ... more Telecommunication operators need tools to evaluate and improve the quality of the their services offered. In the case of telephony services, the speech quality perceived by the users is relevant. There are different speech quality assessment methods, one of them is the parametric method that is generally used in network planning. The ITU-T Rec. G107, and its recent updates, is the most representative parametric method. However, it does not consider the impairments occurred in a wireless channel. In this context, we propose the inclusion of parameters, such as fading channel model, signal-to-noise ratio (SNR), and maximum Doppler shift using different modulation schemes. Several wireless communication scenarios were simulated using actual speech samples as input. Then, the impairment speech samples were evaluated by an intrusive signal-based method described in ITU-T Rec. P.862.2, which results are used as ground-truth. Experimental results demonstrated that there is a high correlation between wireless channel parameters and mean opinion score (MOS) index. Thus, an impairment wireless function, namedIw is proposed and added to the E-model wide-band algorithm. Performance validation test results demonstrated thatIw represents a reliable wireless degradation model, reaching a Pearson correlation coefficient (PCC) and a normalized RMSE (NRMSE) of 0.973 and 0.085, respectively.
IEEE Access
People use Online Social Networks (OSNs) to express their opinions and feelings about many topics... more People use Online Social Networks (OSNs) to express their opinions and feelings about many topics. Depending on the nature of an event and its dissemination rate in OSNs, and considering specific regions, the users' behavior can drastically change over a specific period of time. In this context, this work aims to propose an event detection system at the early stages of an event based on changes in the users' behavior in an OSN. This system can detect an event of any subject, and thus, it can be used for different purposes. The proposed event detection system is composed of the following main modules: (1) determination of the user's location, (2) message extraction from an OSN, (3) topic identification using natural language processing (NLP) based on the Deep Belief Network (DBN), (4) the user behavior change analyzer in the OSN, and (5) affective analysis for emotion identification based on a tree-convolutional neural network (tree-CNN). In the case of public health, the early event detection is very relevant for the population and the authorities in order to be able take corrective actions. Hence, the new coronavirus disease (COVID-19) is used as a case study in this work. For performance validation, the modules related to the topic identification and affective analysis were compared with other similar solutions or implemented with other machine learning algorithms. In the performance assessment, the proposed event detection system achieved an accuracy higher than 0.90, while other similar methods reached accuracy values less than 0.74. Additionally, our proposed system was able to detect an event almost three days earlier than the other methods. Furthermore, the information provided by the system permits to understand the predominant characteristics of an event, such as keywords and emotion type of messages. INDEX TERMS Event detection, online social networks, affective analysis, natural language processing, COVID-19.
IEEE Access
Currently, with the increasing number of devices connected to the Internet, search for network vu... more Currently, with the increasing number of devices connected to the Internet, search for network vulnerabilities to attackers has increased, and protection systems have become indispensable. There are prevalent security attacks, such as the Distributed Denial of Service (DDoS), which have been causing significant damage to companies. However, through security attacks, it is possible to extract characteristics that identify the type of attack. Thus, it is essential to have fast and effective security identification models. In this work, a novel Intrusion Detection System (IDS) based on the Tree-CNN hierarchical algorithm with the Soft-Root-Sign (SRS) activation function is proposed. The model reduces the training time of the generated model for detecting DDoS, Infiltration, Brute Force, and Web attacks. For performance assessment, the model is implemented in a medium-sized company, analyzing the level of complexity of the proposed solution. Experimental results demonstrate that the proposed hierarchical model achieves a significant reduction in execution time, around 36%, and an average detection accuracy of 0.98 considering all the analyzed attacks. Therefore, the results of performance evaluation show that the proposed classifier based on Tree-CNN is of low complexity and requires less processing time and computational resources, outperforming other current IDS based on machine learning algorithms.
Iris image quality assessment based on ISO/IEC 29794-6:2015 standard
Brazilian Journal of Development
CT-FastNet: Detecção de COVID-19 a partir de Tomografias Computadorizadas (TC) de Tórax usando Inteligência Artificial
Brazilian Journal of Development
Anais de XXXIV Simpósio Brasileiro de Telecomunicações
Resumo-Nos dias de hoje, a Voz sobre IP (VoIP)é um dos serviços mais populares em comunicação de ... more Resumo-Nos dias de hoje, a Voz sobre IP (VoIP)é um dos serviços mais populares em comunicação de voz. No entanto, existem muitos fatores que afetam a qualidade geral de uma comunicações VoIP, porque o sinal de vozé transmitido através de canais cabeados ou sem fio, sofrendo diferentes tipos de degradações. Em canais de comunicações cabeados e sem fio, os pacotes perdidos e o desvanecimento afetam o sinal de voz. A avaliação da qualidade da vozé muito importante para garantir a satisfação dos usuários; assim, a precisão nas métricas de qualidade de vozé importante. Neste artigo, diferentes cenários de degradações com perdas de pacotes e modelos de desvanecimento são avaliados, e a qualidade do voz medida, para cada cenário,é determinada usando o ITUT-T P.862. Os resultados experimentais são usados para modelar uma métrica não intrusiva, chamada MOS p , a qual teve uma avaliação de desenpenho satisfatório, atingindo um erro máximmo e um PCC de 0,33 e 97,25%, respectivamente. Além disso, a métrica proposta pode ser usada em serviços de comunicações reais de voz, porqueé uma métrica não intrusiva.
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Papers by Demostenes Rodriguez