David Zabala-Blanco

Universidad Católica del Maule | UCM · Departamento de Computación e Industrias

Society uses precious gems like diamonds for many specific purposes, but it has always been complex to measure their value. For this reason, we will use the Extreme Learning Machine (ELM) to estimate diamond prices using a popular database, which contains 53,943 round-cut diamonds. The results show an optimal accuracy for both standard and regulari...

Finding the best configuration of a neural network's hyper-parameters may take too long to be feasible using an exhaustive search, especially when the cardinality of the search space has a big combinatorial number of possible solutions with various hyper-parameters. This problem is aggravated when we also need to optimize the parameters of the neur...

This paper introduces the adaptation of the Aquila Optimizer (AO) metaheuristic to optimize the hyperparameters of the Extreme Learning Machine (ELM). The AO algorithm is a metaheuristic based on swarm intelligence that optimizes the objective function by simulating the hunting behavior of aquilas. The ELM belongs to the family of single hidden lay...

On the one hand, visible light communication (VLC) based on light-emitting diode (LED) technology offers not only lighting but also communication for various applications such as short-range wireless access, the Industrial Internet of Things (IIoT), vehicular networks (VN)s, among others. On the other hand, experimentation is the final and determin...

Climate change has had a significant impact on honey bee production. For instance, droughts affect the availability of bees' food resources. Consequently, one emerging line of research involves the application of machine learning to model honey production. This paper presents a bibliographic review of machine learning research aimed at predicting h...

Climate change has had a significant impact on honey bee production. For instance, droughts affect the availability of bees' food resources. Consequently, one emerging line of research involves the application of machine learning to model honey production. This paper presents a bibliographic review of machine learning research aimed at predicting h...

Research on wireless communication in water environments is gaining attention due to its relevance in enabling and supporting new applications under the Underwater Internet of Things (UIoT) umbrella. Visible Light Communication (VLC) is one of the emerging communication technologies with the potential to contribute to this domain, especially concer...

Early detection of antibiotic resistance is a crucial task, especially for vulnerable patients under prolonged treatments with a single antibiotic. To solve this, machine learning approaches have been reported in the state of art. Researchers have used MALDI-TOF MS in order to predict antibiotic resistance and/or susceptibility in bacterial samples...

Dear Colleagues, Machine Learning (ML) is commonly defined as the scientific field that studies algorithms and statistical models to give computer systems the ability to learn without being explicitly programmed, typically focusing on a specific task. One of the limits of learning algorithms lies in that the best models are not necessarily those g...

Over the past few years, there has been a growing interest in indoor positioning systems that use Visible Light Communication (VLC) technology in conjunction with light-emitting diodes (LEDs). These systems have become popular because of their ability to provide high bandwidth, and it is anticipated that wireless communication may expand into the v...

This article investigate the deployment of effective communication networks for smart IoT-based smart patient monitoring in medical facilities, advocating for the adoption of Visible Light Communication (VLC) technology. Initially, the physical scenario is analyzed, taking into account factors such as line-of-sight (LOS) and nonline-of-sight (NLOS)...

This study aims to enhance the efficiency of Visible Light Communication (VLC) channels and contribute to the reduction of carbon emissions in underground communications by leveraging Polar Codes and Multiresolution Analysis (MRA). It uses a specific configuration of frozen bits for the implementation of Polar codes. Additionally, it integrates the...

Epilepsy affects millions worldwide, making timely seizure detection crucial for effective treatment and enhanced well-being. Electroencephalogram (EEG) analysis offers a non-intrusive solution, but its visual interpretation is prone to errors and requires a lot of time. Many existing works focus solely on achieving competitive levels of accuracy w...

Context: YOLO (You Look Only Once) is an algorithm based on deep neural networks with real-time object detection capabilities. This state-of-the-art technology is widely available, mainly due to its speed and precision. Since its conception, YOLO has been applied to detect and recognize traffic signs, pedestrians, traffic lights, vehicles, and so o...

This paper proposes a new system based on the Industrial Internet of Things (IIoT) for the monitoring of Mobile Health (m-Health) of workers in the underground mining industry. The proposed architecture uses a hybrid model in data transmission. Visible Light Communication (VLC) is used for downlink because of its narrow coverage, which aids in work...

In recent years, some novel methods have been developed for the detection of diseases based on biomedical signals. In this article, a method for the automated detection of epilepsy seizures is presented by analyzing electroencephalogram (EEG) signals based on the wavelet transform. In the first step, the EEG signals are pre-processed with the Savit...

In this paper, a smart subband system for speaker counting is proposed by scattered microphone array (SMA) and using direction of arrival (DOA) estimation with adaptive eigenvalue decomposition (AED). Firstly, the recorded signals by central array are divided into subbands by using gammatone filter bank. Then, the adaptive generalized cross-correla...

Using biometric systems for individual identification is an alternative that provides excellent data security since this technology uses unique and distinctive information about a person. Palm vein recognition has been raised as an efficient technique for detecting people without compromising data security because vein structures are under the skin...

This document addresses a study that aims to simplify and automate the counting and analysis of biological samples, specifically pathogens cultivated in Petri dishes. The study focuses on the use of computer vision techniques and technologies such as OpenCV, Jetson Nano, 5G, and FSO to achieve this goal. The document explains the methodology used,...

The importance of studying visible light communications (VLC) systems is present today and growing each day due to the possibilities of higher data rates, security, and various applications. In this manuscript, we study the behavior of the channel frequency response (CFR) considering different configurations of parameters and distances in an experi...

The protection of planet Earth, its inhabitants, and all living beings requires the identification of potentially dangerous objects, the simulation of impacts with Earth, and the mitigation of such threats. This research proposes the use of ELMs to distinguish between potentially dangerous objects and those that are not. The ELMs applied in this st...

Chilean wine is one of the most consumed in the global market due to its excellent quality and wide variety of grape crops throughout the country, with Chile being the largest exporter of wine in the southern hemisphere. The characterization of wine quality is of vital importance for this industry, as the valuation of this product in the market dep...

Underground mining visible light communication (UM-VLC) is a promising solution to ensure the well-being of workers and facilitate their work. However, underground conditions present a significant divergence from widely studied indoor environments due to irregular walls, light scattering, and user mobility. The rough environmental conditions of und...

Memory analysis is critical to detecting malicious processes, as it can capture various characteristics and behaviors. However, although it is a field in full research, there are still some major obstacles in malware detection, such as optimizing the detection rate and countering advanced malware obfuscation. Since advanced malware uses obfuscation...

Determining the potability of water for consumption is crucial for human health. To assess the water quality, levels of minerals and ions are measured, such as pH, hardness, sodium, chloramines, sulfate, conductivity, organic carbon, tri-halomethanes, and turbidity. To achieve this more efficiently and accurately, techniques of Machine Learning (ML...

Contactless biometric technologies such as palm vein recognition have gained more relevance in the present and immediate future due to the COVID-19 pandemic. Since certain soft biometrics like gender and age can generate variations in the visualization of palm vein patterns, these soft traits can reduce the penetration rate on large-scale databases...

Currently, cardiovascular diseases are the leading cause of human death according to the World Health Organization. Their prediction allows doctors to indicate preventive measures to their patients and perform procedures on time. In this research, the performance of different Extreme Learning Machine (ELM)-based algorithms applied to the binary cla...

Optical Fiber Radio (RoF) systems based on OFDM meet the needs of high transmission and reception speeds, as well as offering greater reliability in the system. These systems are exposed to various disturbances, such as the thermal and shot noise of the photodetector, the amplified emission of optical links, and the relative phase intensity in the...

This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address...

Speech processing algorithms, especially sound source localization (SSL), speech enhancement, and speaker tracking are considered to be the main fields in this application. Most speech processing algorithms require knowing the number of speakers for real implementation. In this article, a novel method for estimating the number of speakers is propos...

The fingerprint comes to be the most popular and utilized biometric for identifying persons owing to its bio-invariant characteristic, precision, as well as easy acquisition. A sub-system of an identification system is the classification stage in order to diminish the penetration rate and computational complexity. Actually, there are many formal in...

In this work, we introduce the use of a weighted extreme learning machine (ELM) to give an automated predictive value to mass spectrometry data. In specific, the data obtained with Matrix-Assisted Laser DesorptioMonization-Time of Flight (MALDI-TOF) technique are explored for balanced and unbalanced dataset scenarios, and compared with benchmarking...

The fingerprint is one of the most popular and used biometric traits for the identification of people, due to its bio-invariant characteristic, precision, and easy acquisition. One of the stages in the identification of fingerprints is classification, this has the objective of reducing the search times and the computational cost in the databases. C...

This paper presents a web application to control personnel access to a work area without contact; this makes it ideal to help combat the Covid-19 health emergency. For its implementation, deep learning and computer vision techniques have been used for face detection and recognition. The system consists of four phases, the first one aimed at detecti...

This research paper proposes a communication system that can be applied in diagnosis through medical imaging. The objective is to spot abnormalities in breasts with a high level of precision, allowing for diagnostics in the early stages of potential breast cancer. The system was theoretically modeled and simulated with the help of computational cal...

Background noise, interference from other speakers and reverberation cause impairments to the target speech in a real-time indoor environment. Through an audiovisual speech enhancement system, it is possible to simultaneously exploit the acoustic and visual modalities to localize the target speaker and apply source separation and beamforming algori...

Cloud Radio Access Network systems with mmWave Massive MIMO framework can be considered as a potential candidate for next generation wireless communications due to its promise of increased spectral efficiency and distributed signal processing capability. State-of-the-art compressive sensing algorithms like sparse Bayesian learning can exploit the i...

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms a...

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms a...

Cloud Radio Access Network systems with mm-Wave Massive MIMO framework can be considered as a potential candidate for next generation wireless communications due to its promise of increased spectral efficiency and distributed signal processing capability. State-of-the-art compressive sensing algorithms like sparse Bayesian learning can exploit the...

This research presents an application of the Deep Learning technology in the development of an automatic system detection of traffic signs of Ecuador. The development of this work has been divided into two parts, i) in first a database was built with regulatory and preventive traffic signs, taken in urban environments from several cities in Ecuador...

Biometric identification systems play an essential role in multiple application areas, such as banking services, e-government, and public security, among others. Particularly, palm vein recognition is considered an emerging technology from the last decade, avoiding forgery possibilities and presenting high identification reliability and accuracy. S...

Diseases in agricultural crops are a risk for fruit productivity and quality. Chile is a fruit exporting country; that needs the development of technologies for diseases prevention and treatment. Farmers have been exploring how to use Artificial Intelligence to solve problems. Nowadays, deep artificial intelligence models have a great performance....

Fingerprint classification comes to be a relevant guarantee for efficient as well as accurate fingerprint identification, in particular in the case of dealing with one-to-many fingerprint identification. Nevertheless, owing to massive intraclass variability, insignificant inter-class variability, and perturbations, the current fingerprint classific...

Visible light communication (VLC) is considered an enabling technology for future 6G 1 wireless systems. Among the many applications in which VLC systems are used, one of them are harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links....

Underground Mining (UM) is a harsh environment that involves multiple threats to worker safety and needs adequate wireless communications to ensure worker well-being and optimize miner efficiency. While radio frequency signals can be used to manage such tasks, several limitations exist to its potential, as multiple phenomena affect their quality. T...

Visible Light Communications (VLC) have generated great interest in the scientific community in the last five years due to their great adaptation to harsh environments. Among the scenarios that can benefit from the advantages ofvVLC systems are Underground Mining (UM) tunnels. However,vthe physical phenomena and the irregularity of this environment...

Wireless communication systems working in millimeter-wave (mmWave) frequency bandsoffer higher bandwidths than traditional radio frequency schemes. This technology allows multibeamsteering and data multiplexing with the help of massive multiple-input multiple-output (MIMO) systems.However, supporting large bandwidths at mmWave frequencies is challe...

Underground Mining (UM) is a hostile industry that generally requires a wireless communication system as a cross-cutting axis for its optimal operation. Therefore, in the last five years, it has been shown that, in addition to radio-frequency-based communication links, wireless optical communications, such as Visible Light Communication (VLC), can...

Underground mining (UM) is an industry worldwide known for its hostile work environment; therefore, a proper communication system is essential to preserve the miners’ safety. However, the irregular features of UM tunnels as well as their environment prone to electromagnetic interference make it difficult to implement traditional wireless communicat...

Orthogonal frequency-division multiplexing (OFDM) is widely being used in different wide band technologies. Due to the nature of OFDM, the transmitted OFDM symbol is the superposition of several orthogonal subcarriers. This generates a high peak-to-average power ratio (PAPR), which degrades the overall system performance. In this manuscript, a new...

Technologies used in wireless access telecommunications networks, particularly those of mobile telephony, are constantly advancing, achieving this through the development of new techniques and methods that allow reaching an adequate level in very important aspects for a communication system. This article presents the extreme learning machine (ELM)...

Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article...

Analytical expressions of the statistical distribution of the underground mining visible light communication (UM-VLC) square-channel gain are derived considering scattering, shadowing, and a random position and orientation of the receiver. These expressions are employed to compute the system’s bit error probability (BEP) considering shot and therma...

This paper presents a neuromorphic spectrum occupancy learning using convolutional neural networks and long short-term memory, in a cognitive radio enabled cloud radio access system. Cloud radio access networks can prove useful in future generation wireless communication systems, because of their distributed signal processing capability. Owing to i...

Visible light communication (VLC) systems have numerous applications in harsh environments, such as underground mining. However, the irregular tunnel features, the random orientation of the optical components, physical phenomena such as shadowing and scattering, as well as the inherent generation of non-linearities of the optical signal greatly aff...

As Internet Service Providers (ISPs) integrate the fifth generation (5G) technology standard for cellular broadband systems, they may face bursts of network traffic due to the future numerous connections. In this sense, our paper is focused on predicting traffic peaks via deep learning techniques, such as Recurrent Neural Network (RNN), Long Short-...

Radio-over-fiber orthogonal frequency division multiplexing (RoF-OFDM) technology is negatively affected by laser phase noise and chromatic dispersion optical fiber. These impairments normally generate inter-carrier interference (ICI). An extreme learning machine (ELM)-based receiver for RoF-OFDM schemes is proposed to diminish the ICI effect. The...

In order to reduce the search time and computational complexity of an identification system, the classification procedure is a vital task. In this regard, gender classification and age estimation aim to reduce the number of comparisons, especially on large-scale databases for biometric recognition purposes. During the last decade, palm vein recogni...

For years, it has been a great challenge for Internet Service Providers (ISP) to predict traffic load or future demand, since each bit of traffic is an economic cost to operators. Additionally, more and more users are adopting the different telecommunication services as well as the ISP must provide more bandwidth and reliability. In this sense, the...

Power conversion efficiency (PCE) is one of, if not, the most important metric in energy conversion systems, it predicts the energy output of a device, given its input. In radio frequency (RF) energy harvesting (EH) devices, the energy in electromagnetic (EM) waves is captured and turned into a stable low power energy source for various uses, a key...

Due to the coronavirus pandemic and the lack of an automatic COVID-19 diagnostic system to relieve congestion in health centers and to support the traceability of this disease, this article exposes the implementation of algorithms for automatic diagnosis of lung diseases such as COVID-19 and Pneumonia from chest X-rays (CXR) through GLCM and HOG fe...

Mobile/wireless networks aim to support diverse services with numerous and sophisticated requirements, such as energy efficiency, spectral efficiency, negligible latency, robustness against time and frequency selective channels, low hardware complexity, among others. From the central station to the base stations, radio-over-fiber orthogonal frequen...