This study investigates facial emotion recognition in individuals with Down syndrome (DS) using Action Units (AUs) extracted with OpenFace 2.0 and evaluated with ML (Decision Tree, KNN, SVM) and DL (FCNN, 1D-CNN) models. We introduce an intensity-aware AU selection method that identifies a compact and informative subset, and show that preserving moderate-intensity cues is critical for DS. A DS-trained 1D-CNN achieves 94.98

This research presents the validation of a novel software application designed to recognize primary emotions in individuals with Down syndrome (DS), to support therapeutic interventions through artificial intelligence. The research addresses the need for innovative technological tools that assist therapists in real-time emotional assessment during therapy sessions. The study’s objective was to validate the application’s effectiveness, reliability, and therapeutic usefulness in recognizing five spontaneous emotions (happiness, anger, sadness, surprise, and neutrality) in individuals with DS attending a specialized care institution. The study followed ethical protocols approved by the Ethics Committees in Colombia and Ecuador to achieve this. Data was collected during therapy sessions, and three research hypotheses were formulated to evaluate the application’s performance. Structural Equation Modeling (SEM), using SmartPLS, was employed to analyze the relationships between observed emotional responses and the system’s feedback. The results demonstrated that the application accurately identified the targeted emotions in real time, and 94% of participating therapists positively assessed its usefulness in clinical settings. This validation confirms that the software can provide valuable input for therapists, enabling the design of tailored strategies that address the emotional needs of individuals with DS. The findings support the growing evidence supporting integrating machine learning and deep learning technologies into therapeutic tools for vulnerable populations.

This research introduces an algorithm that automatically detects five primary emotions in individuals with Down syndrome: happiness, anger, sadness, surprise, and neutrality. The study was conducted in a specialized institution dedicated to caring for individuals with Down syndrome, which allowed for collecting samples in uncontrolled environments and capturing spontaneous emotions. Collecting samples through facial images strictly followed a protocol approved by certified Ethics Committees in Ecuador and Colombia. The proposed system consists of three convolutional neural networks (CNNs). The first network analyzes facial microexpressions by assessing the intensity of action units associated with each emotion. The second network utilizes transfer learning based on the mini-Xception architecture, using the Dataset-DS, comprising images collected from individuals with Down syndrome as the validation dataset. Finally, these two networks are combined in a CNN network to enhance accuracy. The final CNN processes the information, resulting in an accuracy of 85.30% in emotion recognition. In addition, the algorithm was optimized by tuning specific hyperparameters of the network, leading to a 91.48% accuracy in emotion recognition accuracy, specifically for people with Down syndrome.

In this article, the statistical behavior of the activation intensities of the action units that represent the micro-expressions of the facial expressions for four main emotions, happiness, anger, sadness, and surprise, is analyzed. Based on the results obtained, the distribution of each unit of action is modeled through probability density functions, which will allow the creation of an infinity of random samples, which contribute to emotion evaluation processes and especially to artificial intelligence techniques that require a high number of samples for their training processes.

The Covid-19 pandemic changed the course of activities, both work and education in the world, migrating to the requirement of virtual platforms and videoconferencing tools, such as Zoom, Google Meet, Jitsi Meet, among others. This generated a globalized and digital culture of learning, activities in congresses, and even business meetings using videoconferences. This new scenario creates uncertainty, especially in educators, due to the level of attention they are receiving from students through virtual classes and other scenarios where they want to evaluate the emotions created in the people who receive them information virtual written description intended to provide factual informationally. For this reason, to support different video conferencing platforms or other audiovisual media, a tool is presented that captures video in real-time. It automatically recognizes the emotions expressed by people using deep learning tools, happiness, sadness, surprise, anger, fear, disgust, and neutral emotions. The initial training and validation system is based on the CK+ Dataset that contains images distributed by emotions. This tool was developed for the WEB in Python Flask, which in addition to automatic recognition in real-time, generates statistics of the emotions of the people evaluated with 75% accuracy. To validate the tool, videoconferencing programs were used, the emotions of a group of students were evaluated, and open videos were available online on YouTube. With this study, it was possible to re-know the emotions of the people who attended the class, which allows the teacher to take measures if the students do not carry out the planned activities.

This article presents a study based on evaluating different techniques to automatically recognize the basic emotions of people with Down syndrome, such as anger, happiness, sadness, surprise, and neutrality, as well as the statistical analysis of the Facial Action Coding System, determine the symmetry of the Action Units present in each emotion, identify the facial features that represent this group of people. First, a dataset of images of faces of people with Down syndrome classified according to their emotions is built. Then, the characteristics of facial micro-expressions (Action Units) present in the feelings of the target group through statistical analysis are evaluated. This analysis uses the intensity values of the most representative exclusive action units to classify people’s emotions. Subsequently, the collected dataset was evaluated using machine learning and deep learning techniques to recognize emotions. In the beginning, different supervised learning techniques were used, with the Support Vector Machine technique obtaining the best precision with a value of 66.20%. In the case of deep learning methods, the mini-Xception convolutional neural network was used to recognize people’s emotions with typical development, obtaining an accuracy of 74.8%.

The television programming rating represents, as a percentage, the number of households or viewers who find the television turned on a given channel, program, day, and time. In this project, a rating meter was implemented for the international ISDB-T system based on the analysis of the Program Specific Information tables and Service Information tables of the Transport Stream that carries the information of the television channels and the content of the Electronic Programming Guide, whose data is recorded in a database implemented for this purpose, where the viewer does not need to interact or answer questions about the programming. The implemented prototype uses a full-seg ISDB-T receiver to capture the signal from the air and obtain the transport flow. For the information processing, an interface was designed in Java that evaluates the flow based on the service tables, event information, time offset, and the descriptors that describe information about each event. The data with the name of the channel, name of the program, type of service, start and end time are recorded in the database and automatically generate the rating report. The tests were carried out with the reception of open television channels in the city of Quito in Ecuador.

Being part of the so-called “Pacific Ring of Fire” and “Belt of Low Pressure,” Ecuador is located in one area most likely to suffer seismic, volcanic, and hydrometeorological threats, which make it possible to catalog as a country with a high vulnerability. For this reason, the use of alert systems such as Emergency Warning Broadcasting System EWBS is necessary for the face of one of these threats, which can be implemented in analog and digital broadcast signals such as Digital Terrestrial Television. In an emergency, the receivers compatible with the EWBS are currently the decoders or digital televisions that include this system. They turn on automatically and emit a visual and audible alert signal that gives time to the population to act more quickly to an event. This article presents the design proposal of a receiver that replicates the warning emergency alert EWBS for digital terrestrial television with the ISDB-Tb standard, through an institutional telephone PBX, implementing an IP telephony server that receives the EWBS system and replicates it to landlines, infocast systems, and mobile phones connected to it, thus avoiding a percentage of losses in the economic and human fields.

This article presents an analysis based on Action Units of the facial expressions of four basic emotions in people with Down Syndrome, such as: happiness, sadness, anger and surprise, taking as a reference the Facial Action Coding System, proposed by Paul Ekman, which is based on the universal study of the movements of the muscles of the face, used in some research in people with typical development. For the present study, the action units represent the feature extraction phase of a dataset of images of people with Down syndrome, extracted from the open access website. The tool used to obtain the features of the microexpressions for the action units was Open Face 2.0, which has open source for the development of research topics. Additionally, the statistics that most closely approximated the activation of the Action Units were obtained with their respective equations, using the probability density function, evaluated by the Kullback Leibler Divergence. The statistics obtained in this article made it possible to identify the activation of action units of some emotions that are not found in the literature, such as: AU20 in happiness, sadness and anger; AU15 and AU9 in anger that will be the basis for projecting new research on algorithms for the recognition of emotions in people with Down syndrome through the face.

This article presents an analysis of the performance of Non-Uniform Constellations, also known as Ultra-Multilevel, corresponding to the Digital Modulation of Quadrature Amplitude (QAM), obtained through the optimization of conventional M-QAM Constellations of order M = 16, 64, 256 1024 and 4096, from the Bit-Interleaved Coded Modulation (BICM). To estimate the behavior of a modulated bit stream with these Constellations, two metrics were used: the Signal to Noise ratio (SNR), and the Probability of bit error. Two possible scenarios for a Communications Channel were considered. The first case corresponds to a Channel with Gaussian White Additive Noise (AWGN), and the second case to an AWGN Channel that has been affected by Fading. Channel simulation was performed based on the statistical models of probability distribution, Gaussian and Rayleigh. The results for each case were obtained with the Monte Carlo method. The performance results of the Conventional QAM Constellations with the results of the Non-Uniform QAM Constellations were compared, and it is determined which of them behave optimally with each value of a wide range of SNR values.

The world's elderly population has been increasing at an impressive rate in the last decades. Under this context, the aging process typically requires personalized care services for each individual. In the last few years, the Ecuadorian Government through its public policy has intended to guarantee the well-being of people from birth to death; however, there have not been enough social programs or opportunities for older people in order to achieve their wellbeing. This fact gets worse when their families abandon older adults and therefore find themselves alone in total helplessness. Even more, there are few public nursing homes to help and take care of them in their last years of life. This work presents a care model with the insertion of ICT, implemented in a public Nursing Home with limited human and economic resources located in the Valley of Los Chillos, Ecuador. The primary objective was to enhance the well-being of around 50 older people. The study used ICT for surveillance, assistance, and control; helping with the perception of a better life, addressing both physical and psychological states of elders.

This project presents the analysis and performance evaluation for digital terrestrial television transmitter stations for mobile broadcasting using ISDB-T standard over AWGN and fading channel. A main broadcast transmitter with a secondary transmitter has been evaluated. The second station works with a lower power regarding the main broadcast transmitter, for this project with a 100:1 ratio. Under this scenario, two working options has been defined: (i) both stations transmit the same information, where the secondary station was considered as a repeater station, and (ii) both stations transmit different information, building an environment of co-channel interference. The performance by the bit error rate as a function of the receiver location was presented. The simulation and theoretical results show the improvement or deterioration of the signal, respectively to the working options stablished for the ISDB-T standard's A layer in order to validate repeater stations for digital terrestrial television mobile broadcasting.

This paper analyzes the reverse link performance of wireless networks in presence of co-channel interference on AWGN and Rayleigh fading channels and M-QAM modulation schemes. Simple and precise close-form analytic expressions for mean symbol error probability are derived. The proposed expressions of the analytic model developed to evaluate the performance of those systems are verified by the results of computer simulations.

This article presents a mobility application of navegation directed to people with visual deficiency and disability. Visually disabled people cope with daily challenges in mobility and in their automony. VOICE-TOUCH GPS is an application that has two forms in order to interact with them. The first one lets the person use a smartphone with touch screen to have an auditory feedback. The second one interacts by means of a synthesizer which generates a text by voice and vice-versa. The application presents a graphic interface easy to use along with the help of a GPS. It will help the user know the latest location, the nearest bus stop, buses routes, make phone calls and send messages predetermined to the location. Furthermore, this article presents the functions of the application, requirements of functioning, social impact and the results obtained in people with total and partial visual deficiency in Ecuador.

The present article describes the creation of a MPEG-2 Transport Stream (TS)/Broadcast Transport Stream (BTS) Analyzer for Digital Television. This analyzer recognizes TS and BTS files in a decimal or hexadecimal format and it shows the components of the PSI (Program Service Information)/SI (Service Information) Tables, such as: Program Association Table (PAT), Program Map Table (PMT), Network Information Table (NIT), and Service Descriptor Table (SDT); in the case of the BTS files it also shows the content of the Transmission and Multiplexing Configuration (TMCC) table. The software has a package search system where you can look for a package through his PID (Program Identification) number or his package number. It also allows surfing between all the packages or the packages with the same PID number.

This paper presents the development and evaluation of PICTOAPRENDE, which is an interactive software designed to improve oral communication. Additionally, it contributes to the development of children and youth who are diagnosed with autism spectrum disorder (ASD) in Ecuador. To fulfill this purpose initially analyzes the intervention area where the general characteristics of people with ASD and their status in Ecuador is described. Statistical techniques used for this evaluation constitutes the basis of this study. A section that presents the development of research-based cognitive and social parameters of the area of intervention is also shown. Finally, the algorithms to obtain the measurements and experimental results along with the analysis of them are presented.

The current paper introduces software, named Celina, that integrates the three ISDB-Tb standard functional blocks: Source coding block, multiplex block and transmission coding block. Celina allows to generate the MPEG-2 Transport Stream and transmit it by controlling the modulator DekTec DTU-215 functionalities. Therefore, users can manipulate transmission parameters and can broadcast the Transport Stream previously generated through a Radio Frequency channel. The first stage of the project uses bit level operations which perform the audio and video coding. The EWBS descriptor and the ISDB-Tb program-specific information tables are generated and implemented during the multiplex block. The second stage of the project handles a dynamic-link library, developed on C++, which utilize the most important DTU-215 modulator features. All of this features are embed in an easy- to-manage, scalable, Java graphic interface application.

This paper describes the PICTOAPRENDE application, which is designed to improve verbal communication and development of personal autonomy in children and youth with moderate autism spectrum disorder (ASD) in Ecuador. PICTOAPRENDE is an application on Android platform, which provides options to children and young people to learn basic routines, emergency numbers and more. Facilitating integration into society through the use of digital communicators and pictograms. The area of intervention presents basic concepts related to ASD, as well as various problems both in behavior and in the development of the beneficiary population. Finally impact measurement was performed in a large sample reaching important results for research.

This article presents on analytical performance analyzes about QPSK, 16QAM and 64 QAM modulations and error correcting codes defined in ISDB-T system over AWGN channels. Simple and precise close-form analytic expressions related to byte error probability for the transport stream layer, as a function of the energy per modulated symbol for Viterbi hard and soft decision decoding are derived. The proposed expressions of the analytic model developed to evaluate the performance of the ISDB-T system are verified by the results of computer simulations.