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Computation
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Bioinspiration: The Path from Engineering to Nature
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Bioinspiration: The Path from Engineering to Nature

A special issue of Computation (ISSN 2079-3197).

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 16878

Special Issue Editors

Dr. Juan Luis Crespo-Mariño

E-Mail Website
Guest Editor
LIANA Lab (IA Lab for Natural Sciences), Department of Mechatronics Engineering, Tecnológico de Costa Rica, Cartago 30101, Costa Rica
Interests: artificial neural networks; evolutionary computation; AI-assisted design and modelling
Special Issues, Collections and Topics in MDPI journals
Prof. Andrés Segura-Castillo

E-Mail Website
Guest Editor
Technological Research and Innovation Laboratory (LIIT), Universidad Estatal a Distancia, Sabanilla, Costa Rica
Interests: systemic inquiry; complex modeling; technology management

Special Issue Information

Dear Colleagues,

Bioinspiration, understood as the use of biological processes for inspiration in engineering and computational designs, has become a widespread approach for both the engineer and the computational scientist to study, model, and resolve complex issues. Technological advances, such as the increasing affordability of high-performance computational resources, massive, fast, and accessible storage capacities, high-speed communication networks, along with a growing and vibrant international practitioner community, make the field an attractive opportunity to develop innovative solutions to the increasingly complex and uncertain issues humanity is facing today, which are impossible to face by means of classical or analytical paradigms.

Furthermore, it has also been recognized that bioinspired approaches stimulate synergy among scientific disciplines. Multi- and transdisciplinary work has become essential for the advancement of this area. Researchers from different knowledge fields can contribute toward unified goals, sharing their perspectives through discussion, interaction, and collaboration, which leads to bioinspired knowledge discovery and dissemination. Such processes enrich scientists’ respective areas of interest and open new possibilities for their studies.

It is with this horizon in mind that we have launched this Special Issue. Published works are expected to be the result of multi- and transdisciplinary efforts, which present innovative findings beyond each expert’s specific knowledge area. We look forward to contributions that not only propose new bioinspired engineering and computational methods and solutions but are exemplary of an effective and rewarding collaboration between colleagues from diverse areas that will continue to contribute to the growth of the field.

Prof. Dr. Juan Luis Crespo-Mariño
Prof. Andrés Segura-Castillo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • signal and image detection, acquisition, analysis, and processing
  • social network analysis and modeling
  • pattern recognition for biological and related signals
  • bioinformatics, biocomputing, and computational systems biology
  • data mining and machine learning
  • healthcare informatics
  • robotics
  • biomedical devices
  • machine learning in agriculture
  • biodiversity informatics
  • visual analytics for biological information
  • high performance computing for health and life sciences
  • models of biological learning
  • brain–machine interfaces

Published Papers (5 papers)

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Research

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17 pages, 1830 KiB  
Article
A Comparative Study on Denoising Algorithms for Footsteps Sounds as Biometric in Noisy Environments
by Ronald Caravaca-Mora, Carlos Brenes-Jiménez and Marvin Coto-Jiménez
Computation 2022, 10(8), 133; https://doi.org/10.3390/computation10080133 - 3 Aug 2022
Viewed by 1476
Abstract
Biometrics is the automated identification of a person based on distinctive characteristics, such as fingerprints, face, voice, or the sound of footsteps. This last characteristic has significant challenges considering the background noise present in any real-life application, where microphones would record footsteps sounds [...] Read more.
Biometrics is the automated identification of a person based on distinctive characteristics, such as fingerprints, face, voice, or the sound of footsteps. This last characteristic has significant challenges considering the background noise present in any real-life application, where microphones would record footsteps sounds and different types of noise. For this reason, it is crucial to consider not only the capacity of classification algorithms for recognizing a person using foostetps sounds, but also at least one stage of denoising algorithms that can reduce the background sounds before the classification. In this paper we study the possibilities of a two-stage approach for this problem: a denoising stage followed by a classification process. The work focuses on discovering the proper strategy for applying combinations of both stages for specific noise types and levels. Results vary according to the type and level of noise, e.g., for White noise at signal-to-noise ratio level, accuracy can increase from 0.96 to 1.00 by applying deep learning based-filters, but the same option does not benefit the cases of signals with low level natural noises, where Wiener filtering can increase accuracy from 0.6 to 0.77 at the highest level of noise. The results represent a baseline for developing real-life implementations of footstep biometrics. Full article
(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)
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14 pages, 7605 KiB  
Article
Rapid Detection of Cardiac Pathologies by Neural Networks Using ECG Signals (1D) and sECG Images (3D)
by Evelyn Aguiar-Salazar, Fernando Villalba-Meneses, Andrés Tirado-Espín, Daniel Amaguaña-Marmol and Diego Almeida-Galárraga
Computation 2022, 10(7), 112; https://doi.org/10.3390/computation10070112 - 30 Jun 2022
Cited by 5 | Viewed by 2514
Abstract
Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health [...] Read more.
Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health services or the time the public health system takes to refer the patient to a cardiologist. In addition, the variety of cardiac pathologies (more than 20 types) is a problem in diagnosing the disease. On the other hand, surface electrocardiography (sECG) is a little-explored technique for this diagnosis. sECGs are three-dimensional images (two dimensions in space and one in time). In this way, the signals were taken in one-dimensional format and analyzed using neural networks. Following the transformation of the one-dimensional signals to three-dimensional signals, they were analyzed in the same sense. For this research, two models based on LSTM and ResNet34 neural networks were developed, which showed high accuracy, 98.71% and 93.64%, respectively. This study aims to propose the basis for developing Decision Support Software (DSS) based on machine learning models. Full article
(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)
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17 pages, 1517 KiB  
Article
An Experimental Study on Speech Enhancement Based on a Combination of Wavelets and Deep Learning
by Michelle Gutiérrez-Muñoz and Marvin Coto-Jiménez
Computation 2022, 10(6), 102; https://doi.org/10.3390/computation10060102 - 20 Jun 2022
Cited by 7 | Viewed by 3165
Abstract
The purpose of speech enhancement is to improve the quality of speech signals degraded by noise, reverberation, or other artifacts that can affect the intelligibility, automatic recognition, or other attributes involved in speech technologies and telecommunications, among others. In such applications, it is [...] Read more.
The purpose of speech enhancement is to improve the quality of speech signals degraded by noise, reverberation, or other artifacts that can affect the intelligibility, automatic recognition, or other attributes involved in speech technologies and telecommunications, among others. In such applications, it is essential to provide methods to enhance the signals to allow the understanding of the messages or adequate processing of the speech. For this purpose, during the past few decades, several techniques have been proposed and implemented for the abundance of possible conditions and applications. Recently, those methods based on deep learning seem to outperform previous proposals even on real-time processing. Among the new explorations found in the literature, the hybrid approaches have been presented as a possibility to extend the capacity of individual methods, and therefore increase their capacity for the applications. In this paper, we evaluate a hybrid approach that combines both deep learning and wavelet transformation. The extensive experimentation performed to select the proper wavelets and the training of neural networks allowed us to assess whether the hybrid approach is of benefit or not for the speech enhancement task under several types and levels of noise, providing relevant information for future implementations. Full article
(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)
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16 pages, 858 KiB  
Article
Magnetic Trails: A Novel Artificial Pheromone for Swarm Robotics in Outdoor Environments
by Juan Carlos Brenes-Torres, Francisco Blanes and José Simo
Computation 2022, 10(6), 98; https://doi.org/10.3390/computation10060098 - 15 Jun 2022
Cited by 3 | Viewed by 2270
Abstract
Swarm robotics finds inspiration in nature to model behaviors, such as the use of pheromone principles. Pheromones provide an indirect and decentralized communication scheme that have shown positive experimental results. Real implementations of pheromones have suffered from slow sensors and have been limited [...] Read more.
Swarm robotics finds inspiration in nature to model behaviors, such as the use of pheromone principles. Pheromones provide an indirect and decentralized communication scheme that have shown positive experimental results. Real implementations of pheromones have suffered from slow sensors and have been limited to controlled environments. This paper presents a novel technology to implement real pheromones for swarm robotics in outdoor environments by using magnetized ferrofluids. A ferrofluid solution, with its deposition and magnetization system, is detailed. The proposed substance does not possess harmful materials for the environment and can be safely handled by humans. Validation demonstrates that the substance represents successfully pheromone characteristics of locality, diffusion and evaporation on several surfaces in outdoor conditions. Additionally, the experiments show an improvement over the chemical representation of pheromones by using magnetic substances and existing magnetometer sensor technologies, which provide better response rates and recovery periods than MOX chemical sensors. The present work represents a step toward swarm robotics experimentation in uncontrolled outdoor environments. In addition, the presented pheromone technology may be use by the broad area of swarm robotics for robot exploration and navigation. Full article
(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)
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Review

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15 pages, 273 KiB  
Review
Swarm Robotics: Simulators, Platforms and Applications Review
by Cindy Calderón-Arce, Juan Carlos Brenes-Torres and Rebeca Solis-Ortega
Computation 2022, 10(6), 80; https://doi.org/10.3390/computation10060080 - 24 May 2022
Cited by 13 | Viewed by 6482
Abstract
This paper presents an updated and broad review of swarm robotics research papers regarding software, hardware, simulators and applications. The evolution from its concept to its real-life implementation is presented. Swarm robotics analysis is focused on four aspects: conceptualization, simulators, real-life robotics for [...] Read more.
This paper presents an updated and broad review of swarm robotics research papers regarding software, hardware, simulators and applications. The evolution from its concept to its real-life implementation is presented. Swarm robotics analysis is focused on four aspects: conceptualization, simulators, real-life robotics for swarm use, and applications. For simulators and robots, a detailed comparison between existing resources is made. A summary of the most used swarm robotics applications and behaviors is included. Full article
(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)
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