Browsing by Author "Palacio Baus, Kenneth Samuel"

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A general process for the semantic annotation and enrichment of electronic program guides
(Springer Verlag, 2019) Gonzalez Toral, Hernan Santiago; Espinoza Mejía, Jorge Mauricio; Palacio Baus, Kenneth Samuel; Saquicela Galarza, Víctor Hugo
Electronic Program Guides (EPGs) are usual resources aimed to inform the audience about the programming being transmitted by TV stations and cable/satellite TV providers. However, they only provide basic metadata about the TV programs, while users may want to obtain additional information related to the content they are currently watching. This paper proposes a general process for the semantic annotation and subsequent enrichment of EPGs using external knowledge bases and natural language processing techniques with the aim to tackle the lack of immediate availability of related information about TV programs. Additionally, we define an evaluation approach based on a distributed representation of words that can enable TV content providers to verify the effectiveness of the system and perform an automatic execution of the enrichment process. We test our proposal using a real-world dataset and demonstrate its effectiveness by using different knowledge bases, word representation models and similarity measures. Results showed that DBpedia and Google Knowledge Graph knowledge bases return the most relevant content during the enrichment process, while word2vec and fasttext models with Words Mover’s Distance as similarity function can be combined to validate the effectiveness of the retrieval task.
a relaying graph and special strong product for zero-error problems in primitive relay channels
(Institute of Electrical and Electronics Engineers Inc., 2018) Palacio Baus, Kenneth Samuel; Palacio Baus, Kenneth Samuel
A primitive relay channel (PRC) has one source (S) communicating a message to one destination (D) with the help of a relay (R). The link between R and D is considered to be noiseless, of finite capacity, and parallel to the link between S and (R,D). Prior work has established, for any fixed number of channel uses, the minimal R-D link rate needed so that the overall S-D message rate equals the zero-error single-input multiple output outer bound (Problem 1). The zero-error relaying scheme was expressed as a coloring of a carefully defined 'relaying compression graph'. It is shown here that this relaying compression graph for n channel uses is not obtained as a strong product from its n = 1 instance. Here we define a new graph, the 'primitive relaying graph' and a new 'special strong product' such that the n-channel use primitive relaying graph corresponds to the n-fold special strong product of the n = 1 graph. We show how the solution to Problem 1 can be obtained from this new primitive relaying graph directly. Further study of this primitive relaying graph has the potential to highlight the structure of optimal codes for zero-error relaying. Â© 2018 IEEE.
Achievable error exponents for the two-way parallel DMC
(Institute of Electrical and Electronics Engineers, 2021) Devroye, Natasha ; Palacio Baus, Kenneth Samuel
We investigate error exponent regions for the parallel two-way DMC in which each terminal sends its own message and provides feedback to the other terminal. Various error exponents are presented in different rate-region regimes based on the relative rates and zero-error capacities of both directions. The schemes employed are extensions of error exponents for one-way DMCs with noiseless, rate-limited and noisy feedback
Achievable error exponents of one-way and two-way AWGN channels
(2019) Palacio Baus, Kenneth Samuel; Devroye, Natasha
Achievable error exponents for the one-way with noisy feedback and two-way AWGN channels are derived for the transmission of a finite number of messages using fixed block length , under the almost sure (AS) and the expected block (EXP) power constraints. In the one-way setting under noisy AWGN feedback, it is shown that under the AS constraint and when the feedback link is much stronger than the direct link, active feedback leads to a larger gain over the non-feedback error exponent than passive feedback. Under the EXP constraint, a previously known error exponent for the transmission of two messages is generalized to any arbitrary but finite number of messages . In the two-way setting, where each user has its own message to send in addition to (possibly) aiding in the transmission of feedback for the opposite direction, error exponent regions are defined and derived for the first time for the AWGN two-way channel under both AS and EXP power constraints. It is shown that feedback or interaction may lead to error exponent gains in one direction, possibly at the expense of a decrease in the error exponents attained in the other direction. The relationship between and supported by our achievability strategies is explored.
Adquisición y análisis de señales cerebrales utilizando el dispositivo MindWave
(Universidad de Cuenca, 2014) Torres, Felipe; Sánchez, Christian; Palacio Baus, Kenneth Samuel; Universidad de Cuenca; Dirección de Investigación de la Universidad de Cuenca; DIUC
Brain activity can be monitored through electroencephalography and used as a bioelectric indicator. This paper shows how a low cost device can be used in developing brain-computer interface based applications. The obtained results show that the MindWave device can be used for EEG signal acquisition, and that the Wavelet transform can be employed to improve the signal representation in order to apply artificial intelligence algorithms and pattern recognition techniques to classify brain responses.
An Approach to Experiment Reproducibility Through MLOps and Semantic Web Technologies
(IEEE, 2023) Seaman Mora, Daniel Andres ; Palacio Baus, Kenneth Samuel; Saquicela Galarza, Víctor Hugo; Peñafiel Mora, David Marcelo; Seaman Mora, Daniel Andres
This article addresses the challenge of reproducing machine learning (ML) experiments by integrating processes based on MLOps and semantic technologies. The inherent complexity of experimentation in scientific research hinders reproducibility through conventional methods, which has led to the need to automate processes. In this work, a solution has been developed allowing the execution of ML experiments of other researchers and their reproducibility. The use of semantic technologies allows the complete description of the experiment, including the data and resources necessary for its execution. The approach proposed in this work contributes to the automation of the experimentation phases based on MLOps, demonstrating how it can be used to reproduce experiments and offer a solution to the complexity of experimentation in scientific research. The effectiveness of the solution proposed in this work is evaluated by means of a survey-based analysis carried out among researchers who currently use manual processes to perform machine learning experiments. The results indicate that manual processing is prone to errors and not scalable regarding the size and complexity of most experiments. Moreover, the solution proposed in this work, which combines MLOps-based processes and semantic technologies, has been well received by researchers and considered to significantly improve the efficiency, reproducibility, and scalability of machine learning experimentation.
An error exponent for the AWGN channel with decision feedback and lattice coding
(Institute of Electrical and Electronics Engineers, 2022) Palacio Baus, Kenneth Samuel; Devroye, Natasha
Arquitectura IoT para la automatización agrícola: captura del conocimiento ancestral y gestión en entornos de conectividad limitada
(Universidad de Cuenca, 2025-09-25) Orellana Salinas, Juan Diego; Pacurucu Llivichuzhca, Carlos Samuel; Zúñiga Prieto, Miguel Ángel; Palacio Baus, Kenneth Samuel
AAgriculture is a fundamental sector in developing countries such as Ecuador, where it is still practiced in a traditional way with limited access to technologies that optimize production. IoT-based solutions have shown potential to automate tasks such as irrigation, fertilization, and environmental monitoring; however, they often rely on constant connectivity and energy supply, which limits their effectiveness in rural areas with deficient infrastructure. Moreover, these solutions usually focus solely on automation, without considering mechanisms that preserve the ancestral knowledge of farmers. This work aimed to design a distributed software architecture for IoT applications in agricultural contexts with limited connectivity, oriented toward task monitoring and the preservation of ancestral knowledge. The proposal includes: (1) detecting agricultural practices through environmental data captured by sensors, (2) recording farmers’ decisions and techniques, and (3) correlating both sources to digitalize ancestral knowledge, validate patterns through machine learning, and generate adaptive recommendations that integrate traditional wisdom with precision agriculture. The methodology applied was RUP, and the architecture was documented using Kruchten’s 4+1 views model, also applying SOLID principles. A prototype was implemented with Flutter and Isar for the mobile application, Angular for the web environment, RabbitMQ for asynchronous messaging, Spring Boot with PostgreSQL for the central server, and a local node developed in Python on Raspberry Pi. The results demonstrate autonomy under intermittent connectivity, fault tolerance, scalability, energy efficiency, and a modular, resilient, and replicable solution that promotes technological equity and sustainability in rural contexts.
Characterizing artifacts in RR stress test time series
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2016-08-16) Astudillo Salinas, Darwin Fabián; Medina Molina, Ruben; Palacio Baus, Kenneth Samuel; Solano Quinde, Lizandro Damián; Wong De Balzan, Sara
Electrocardiographic stress test records have a lot of artifacts. In this paper we explore a simple method to characterize the amount of artifacts present in unprocessed RR stress test time series. Four time series classes were defined: Very good lead, Good lead, Low quality lead and Useless lead. 65 ECG, 8 lead, records of stress test series were analyzed. Firstly, RR-time series were annotated by two experts. The automatic methodology is based on dividing the RR-time series in non-overlapping windows. Each window is marked as noisy whenever it exceeds an established standard deviation threshold (SDT). Series are classified according to the percentage of windows that exceeds a given value, based upon the first manual annotation. Different SDT were explored. Results show that SDT close to 20% (as a percentage of the mean) provides the best results. The coincidence between annotators classification is 70.77% whereas, the coincidence between the second annotator and the automatic method providing the best matches is larger than 63%. Leads classified as Very good leads and Good leads could be combined to improve automatic heartbeat labeling.
CinC Challenge 2013: Comparing three algorithms to extract fetal ECG
(SPIE, 2015-11-17) Loja, J; Astudillo Salinas, Darwin Fabián; Medina Molina, Ruben; Palacio Baus, Kenneth Samuel; Velecela, E; Wong De Balzan, Sara
This paper reports a comparison between three fetal ECG (fECG) detectors developed during the CinC 2013 challenge for fECG detection. Algorithm A1 is based on Independent Component Analysis, A2 is based on fECG detection of RS Slope and A3 is based on Expectation-Weighted Estimation of Fiducial Points. The proposed methodology was validated using the annotated database available for the challenge. Each detector was characterized in terms of its performance by using measures of sensitivity, (Se), positive predictive value (P+) and delay time (td). Additionally, the database was contaminated with white noise for two SNR conditions. Decision fusion was tested considering the most common types of combination of detectors. Results show that the decision fusion of A1 and A2 improves fQRS detection, maintaining high Se and P+ even under low SNR conditions without a significant tdincrease.
Clasificación automática de señales para comunicaciones inalámbricas basada en técnicas de inteligencia artificial
(Universidad de Cuenca, 2025-09-24) Pardo Castro, Carlos Andrés; Pérez Vargas, Juan Pablo; Solano Quinde, Lizandro Damián; Palacio Baus, Kenneth Samuel
This work addresses the identification of digital modulation schemes under realistic chan- nel conditions—multipath fading, additive white Gaussian noise (AWGN), and carrier phase offset—across six formats: BPSK, QPSK, 16-QAM, cross-32-QAM, 64-QAM, and cross-128- QAM; a complementary analysis with 256-QAM is also included to assess performance under higher constellation orders. To capture channel variability, scenarios with different signal-to- noise ratio (SNR) levels, numbers of propagation paths, and phase-offset values were gene- rated using the TorchSig toolkit; the resulting baseband in-phase/quadrature (I–Q) signals fed three neural-network architectures trained and evaluated in supervised classification tasks. Finally, a voting-based ensemble that combines the top k models from each network is pro- posed, yielding consistent gains in correct classification probability (PCC) across all evaluated scenarios.
Comparison of the performance and energy consumption index of model-based controllers
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2016-10-12) Minchala Ávila, Luis Ismael; Palacio Baus, Kenneth Samuel; Ortiz, J.P; Valladolid, J.D
This paper presents a comparison of the performance of different control algorithms in two types of systems; one exhibiting fast dynamics and the other slow dynamics. The first control system regulates the speed of a DC motor, while the second control system regulates the temperature of an electrical heater. This systems' performance comparison pretends to evaluate the energy consumption, as well as the controllers' transient response in order to identify the best control strategy for each system. System models are obtained through the responses to a pseudorandom binary signal (PRBS) and the least squares fit method using an auto-regressive model with an exogenous variable (ARX). The implemented control algorithms used in this study are: Pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR). A detailed analysis of the performance and energy consumption index is performed, that allow the categorization of the control strategies in accordance with their performance.
Current challenges of interactive digital television
(Institute of Electrical and Electronics Engineers Inc., 2018) Palacio Baus, Kenneth Samuel; Mejía Pesántez, Piedad Magali; Muñoz Guillén, Lissette Maritza; Espinoza Mejía, Jorge Mauricio
This article presents a high level overview of the current challenges that Interactive Digital Television involves due to the changes in user's behaviour under the current TV watching experience. We present a short review of multiple works found in the literature which have addressed specific issues that arise on converting an only-watching setting onto an interactive experience. Moreover, we have envisioned a system architecture that evidence how second screen accompanying devices, such as mobile phones or tablets, can be used to facilitate the interactivity process from the technical and operative viewpoints. In particular, this architecture supports innovative interactive applications for automatic ad recognition utilizing a second screen device as a friendly user interface.
Desarrollo y validación de algoritmos para el estudio de la variabilidad de la frecuencia cardíaca en adultos mayores
(2015) Parra Orellana, Freddy Andres; Wong de Balzan, Sara; Palacio Baus, Kenneth Samuel
This work is part of the project: Heart Rate Variability (HRV) and Insulin Sensibility among the Senior Population of Cuenca (Variabilidad de la Frecuencia Cardiaca (VFC) y Sensibilidad a la Insulina en la Población Adulta Mayor de Cuenca), funded and promoted by the Prometo Program and the Research Direction of the University of Cuenca (Dirección de Investigación de la Universidad de Cuenca – DIUC). The main goal of this thesis was to develop algorithms aimed to study the Heart Rate Variability. The tasks performed in this work include: i) the acquisition of SCP-ECG electrocardiographic registers from a senior population set, ii) the development of a platform aimed to integrate ECG registers with clinic and demographic information of studied subjects; iii) ECG processing by making use of the Pan-Tompkins QRS detector and artifact filtering in order to obtain RR series, and iv) the application of non-parametric methods (PSD and Hamming) and parametric methods (Burg) for temporal and spectral estimation, in addition to temporal parameter (SDRR, SMRRD) computation and frequency parameter (LF,HF, LF/HF) computation from the HRV. The development of this project makes use of a Graphic User Interface (GUI) called UCUENCAViewer ANALISIS VFC, which will allow researchers to analyze senior population’s HRV. Additionally, this tool will be available for teaching purposes and able to be used in future research.
Diseño de una arquitectura de Middleware para la evolución de aplicaciones en el entorno del internet de las cosas (IoT)
(Universidad de Cuenca, 2024-09-23) Soriano Eusebio, Alberto Carlo; Zúñiga Prieto, Miguel Ángel; Palacio Baus, Kenneth Samuel
Smart environments enhance industrial and domestic processes through IoT, optimizing efficiency and sustainability, yet they face challenges in interoperability, modularity, and scalability due to technological diversity and the lack of regulations. Standardizing protocols is key to overcoming these obstacles and facilitating innovation. This paper proposes a software architecture that guides the creation of middleware for interacting with IoT devices. These middleware applications simplify the interaction between IoT devices and applications, enabling efficient implementation and operation in heterogeneous environments. The developed middleware will provide two main benefits: facilitating code implementation and managing device interaction during execution in dynamic environments. A modular architecture based on the microkernel was designed, incorporating design patterns such as Strategy, Factory, and Publish-Subscribe to ensure modularity, scalability, and adaptability in heterogeneous technological environments. Evaluation through a case study demonstrated that this architecture is efficient and effective in addressing IoT challenges, providing a useful framework for future developers and researchers in the creation of IoT applications. In the case study, a software prototype based on this architecture was developed, and tests were conducted that validated its efficiency, scalability, and fault tolerance. The results confirmed that the proposal effectively manages the interaction between IoT applications and devices, meeting high standards of functionality and quality.
Diseño e Implementación de una red de comunicación de emergencia para el Campus Balzay
(Universidad de Cuenca, 2025-09-29) Chango Cuenca, Eduardo Andrés; Astudillo Salinas, Darwin Fabián; Palacio Baus, Kenneth Samuel
This work presents the design and implementation of an emergency communication network at the Balzay campus, within the framework of the SHAYA 2.0 project aimed at violence prevention. IoT technology was employed, specifically LoRaWAN, chosen for its low energy consumption, long range, and reliable coverage, enabling the installation of wireless physical buttons that send alerts when activated. The system was evaluated using an adaptive burst transmission strategy that improves message reception even in environments with obstacles. Energy consumption was optimized, achieving a sleep current of 580 µA, ensuring an autonomy exceeding six months. Communication tests reached a 100% success rate in critical areas, validated with metrics such as SNR and RSSI. Implemented as a pilot at the Balzay campus, the prototype provides a robust solution for alert transmission.
Enriching Electronic Program Guides using semantic technologies and external resources
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2014-09-15) Saquicela Galarza, Víctor Hugo; Alban Bermeo, Humberto Marcelo; Espinoza Mejía, Jorge Mauricio; Palacio Baus, Kenneth Samuel
Electronic Program Guides (EPGs) describe broadcast programming information provided by TV stations. However, users may obtain more information when these guides have been enriched. The main contribution of this work is to present an automation process for EPG's information enrichment through the use of semantic technologies and external resources. Among the several resources involved in the enrichment process, the following can be mentioned : ontologies, web services, semantic repositories and natural language processing techniques.
Enriching electronic program guides using semantic technologies and external resources
(2014-09-15) Saquicela Galarza, Víctor Hugo; Espinoza Mejía, Jorge Mauricio; Palacio Baus, Kenneth Samuel; Alban, H.
Electronic Program Guides (EPGs) describe broadcast programming information provided by TV stations. However, users may obtain more information when these guides have been enriched. The main contribution of this work is to present an automation process for EPG's information enrichment through the use of semantic technologies and external resources. Among the several resources involved in the enrichment process, the following can be mentioned : ontologies, web services, semantic repositories and natural language processing techniques.
Error exponents of parallel two-way discrete memoryless channels using variable length coding
(Institute of Electrical and Electronics Engineers Inc., 2019) Palacio Baus, Kenneth Samuel; Asadi, Meysam; Devroye, Natasha
Achievable error exponents for two-way parallel discrete memoryless channels (DMC) using variable block length coding (VLC) are presented. First, Forney's erasure decoding error exponent is shown to be achievable for both directions simultaneously. Next, for some rate-pairs, it is shown that the error exponent of the direction with a smaller capacity may be further increased by allocating feedback resources to it in the other direction, at the price of a decreased error exponent for the other terminal. The presented two-way communication scheme builds upon Draper-Sahai's one-way DMC achievability scheme with noisy feedback under VLC. Both achievable error exponent regions demonstrate that the use of VLC and interaction between the terminals may benefit both directions' error exponents over fixed block length and feedback free transmission.1.
Evaluación de métodos de corrección radiométrica y geométrica de una cámara de campo de visión amplio
(Universidad de Cuenca, 2025-09-24) Palaguachi Dután, Felipe Sebastián; León Guanoquiza, Franklin Josué; Andrade Rodas, Juan Manuel; Palacio Baus, Kenneth Samuel
This work evaluates the application of geometric and radiometric correction techniques on sky images captured with wide-field cameras, with the aim of mitigating distortions introduced by wide-angle lenses (140° and 180°) and improving the quality of these images for analysis in computer vision. The main objective of this work is to obtain accurate representations of sky conditions, which are essential for applications such as short-term photovoltaic forecasting. A comprehensive review of the state of the art is presented, exploring geometric models such as Kannala-Brandt, Scaramuzza, UCM, EUCM, and Mei, as well as radiometric methods including HDR image generation using Debevec, Mitsunaga, and Robertson techniques, including vignetting correction using approaches by Gao, Lopez-Fuentes, and Zheng. Comparative experiments have been designed to evaluate the performance of these methods on synthetic and real images, using metrics such as PSNR, SSIM, RPE, and radiometric uniformity. The results highlight that the Kannala-Brandt model excels in the correction of synthetic images, while EUCM and Mei offer greater accuracy in real scenarios; in the radiometric domain, the Debevec technique preserves key HDR details, and the Lopez-Fuentes method optimizes vignetting correction. Finally, the implications of these findings for sky image enhancement are discussed, and future lines of research are proposed, such as the development of hybrid models and the expansion of datasets, with an independent focus on their application for photovoltaic prediction studies.