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Performance assessment of population-based multiobjective optimization algorithms using composite indicators
Get PDFThe performance of population-based multiobjective
optimization algorithms is usually evaluated using indicators
assessing the quality of the approximation set generated according
to convergence, cardinality, spread, and uniformity (the
combination of the last two known as diversity). Since not all
quality indicators can capture all these properties, we propose
to aggregate already-existing indicators into a single measure
informing about the algorithm’s performance from a general
perspective. To synthesize the desired quality indicators, we build
three composite quality indicators (weak, strong, and mixed)
based on the reference point approach. This approach enables
the use of desirable value ranges for the aggregated quality
indicators, defined by aspiration and reservation levels, that
allow knowing which algorithms perform better, within, or worse
than the desired limits. Each of the composite quality indicators
proposed enables a different compensation degree among the
aggregated indicators, and their joint use permits a deep insight
into the algorithms’ performance. In addition, we show that
the weak and mixed composite indicators are Pareto-compliant,
and the strong one is weakly Pareto-compliant if at least one
of the aggregated indicators is Pareto-compliant. Finally, we
demonstrate the benefits of our proposal when comparing many
population-based algorithms on three-, five-, and eight-objective
optimization problems.Funding for open access charge: Universidad de Málaga/CBUA
A decision framework for privacy-preserving synthetic data generation
No full textAccess to realistic data is essential for various purposes, including training machine learning models, conducting simulations, and supporting data-driven decision making across diverse domains. However, the use of real data often raises significant privacy concerns, as it may contain sensitive or personal information. Generative models have emerged as a promising solution to this problem by generating synthetic datasets that closely resemble real data. Nevertheless, these models are typically trained on original datasets, which carries the risk of leaking sensitive information. To mitigate this issue, privacy-preserving generative models have been developed to balance data utility and privacy guarantees. This paper examines existing generative models for synthetic tabular data generation, proposing a taxonomy of solutions based on the privacy guarantees they provide. Additionally, we present a decision framework to aid in selecting the most suitable privacy-preserving generative model for specific scenarios, using privacy and utility metrics as key selection criteria.Funding for open access charge: Universidad de Málaga / CBU
Comparing analytically propulsion by pitching and heaving flexible foils near the first two natural modes
Get PDFAn analytical formulation is provided that describes the first two natural modes of the
fluid–structure interaction of an incompressible current with a pitching and heaving
flexible plate. The objective is twofold: first, to present a general derivation of analytical
expressions for the lift, moment and the flexural moments exerted by an inviscid flow on
a pitching and heaving plate whose deformation is general enough that the coupling of
the flexural moments with the structural equations allows solving analytically the first two
natural modes of the system; second, to analyse the propulsion performance of the foil
when actuated near the first two natural frequencies. For the second purpose, one also
needs the thrust force generated through the motion and the general deformation of the
foil considered, which is analytically derived using the linearized vortex impulse theory,
extending and systematizing previous works. The analytical expressions, once viscous
effects are taken into consideration through nonlinear transverse damping and offset drag
coefficients, are compared with small-amplitude available experimental data, discussing
their limitations. It is found that low stiffness pitching and heaving are quite different,
with a pitching flexible foil only generating thrust near the second resonant frequency,
whereas heaving always generates thrust, with the maximum slightly below the second
natural frequency. Maximum thrust for large stiffness pitching is around the first natural
frequency. The maximum efficiency occurs at frequencies close to the first natural mode
if the foil is sufficiently rigid, but it is not related to the natural frequencies as the rigidity
decreases.Funding for open access charge: Universidad de Málag
Distribution pattern and biochemical variability of Irish invasive seaweed across a spatial gradient
Get PDFThis study updates the distribution of seaweed invasive alien species (IAS) in Ireland and demonstrates the natural spatial variation of their phenolic compounds and fatty acid profiles, coupled with an assessment of biomass availability. We examined the intertidal area of 68 coastal locations and detected the presence of six IAS, but abundant populations (30–50 % cover) were only recorded for Sargassum muticum in some western and southern locations along the Irish coast. However, the fact that so many invasive species were widely distributed represents a dormant threat to Irish coastal ecosystems. Regarding distribution, we detected a spatial expansion of Colpomenia peregrina and Codium fragile, while a contraction was recorded for S. muticum and Asparagopsis armata. Undaria pinnatifida represents a recent introduction, and Gracilaria vermiculophylla is spreading to new locations in the south and west. In general, saturated fatty acid content was high in C. fragile and C. peregrina samples, and higher monounsaturated fatty acid content occurred in the latter. Sargassum muticum and G. vermiculophylla presented more polyunsaturated fatty acids and n-3 fatty acids (together with C. fragile). Statistical analyses showed that, for to S. muticum, higher water temperatures decreased metabolite content in all areas sampled, and higher concentrations of metabolites were generally found in northern populations. However, biomass was not abundant at these sites, which poses challenges facing valorisation of these natural resources. This study provides important baseline information of fatty acid profiles and phenolic content of Irish IAS, an essential preliminary step in industrial sourcing of marine bioactive metabolites.Funding for open access charge: Universidad de Málaga / CBU
Integrating energy consumption in the development of serverless applications
No full textContext:
The increasing environmental impact of Information and Communication Technologies (ICTs), particularly the energy consumption associated with serverless applications, necessitates the development of methodologies to optimize energy efficiency. This study addresses the need for energy-aware design and runtime adaptation in serverless architectures.
Objective:
To develop and validate a methodology that integrates energy monitoring into the development and runtime management of serverless applications, thereby enabling significant reductions in energy consumption while maintaining functionality.
Methods:
A new version of FUSPAQ, a framework for the optimization of serverless applications, was developed. This version incorporates tools like Kepler for real-time energy monitoring and employs an energy-aware orchestration mechanism to dynamically select energy-efficient function configurations. Validation was conducted through a facial recognition case study and benchmark experiments, comparing energy consumption across different scenarios with and without the proposed adaptations.
Results:
The enhanced FUSPAQ framework successfully integrated energy consumption metrics into the decision-making process for function selection and runtime adaptation. Benchmark tests confirmed the scalability of the solution, with energy-efficient outcomes even in complex applications.
Conclusion:
The study highlights the potential of integrating energy-aware practices in serverless applications, presenting a scalable and practical approach to reducing their environmental footprint. By leveraging tools like Kepler and frameworks like FUSPAQ, developers can achieve significant energy savings without compromising application performance. This work contributes to the advancement of Green Software Engineering by emphasizing runtime energy adaptation in Function-as-a-Service (FaaS) architectures.Funding for open access charge: Universidad de Málaga / CBU
Addressing significant challenges for animal detection in camera trap images: a novel deep learning-based approach.
Get PDFWildlife biologists increasingly use camera traps for monitoring animal populations. However,
manually sifting through the collected images is expensive and time-consuming. Current deep learning
studies for camera trap images do not adequately tackle real-world challenges such as imbalances
between animal and empty images, distinguishing similar species, and the impact of backgrounds on
species identification, limiting the models’ applicability in new locations. Here, we present a novel
two-stage deep learning framework. First, we train a global deep-learning model using all animal
species in the dataset. Then, an agglomerative clustering algorithm groups animals based on their
appearance. Subsequently, we train a specialized deep-learning expert model for each animal group to
detect similar features. This approach leverages Transfer Learning from the MegaDetectorV5 (YOLOv5
version) model, already pre-trained on various animal species and ecosystems. Our two-stage deep
learning pipeline uses the global model to redirect images to the appropriate expert models for final
classification. We validated this strategy using 1.3 million images from 91 camera traps encompassing
24 mammal species and used 120,000 images for testing, achieving an F1-Score of 96.2% using expert
models for final classification. This method surpasses existing deep learning models, demonstrating
improved precision and effectiveness in automated wildlife detection
Los medios de comunicación ante la desinformación: inteligencia artificial, discursos de odio, teorías de la conspiración y verificación
Get PDFLa obra está en acceso abierto en la colección Open Access de la editorial y que todos los autores están de acuerdo. Enlace: https://doi.org/10.36151/TLB_9788411839358La desinformación se ha convertido en una de las mayores preocupaciones de las sociedades democráticas. Los bulos y los contenidos manipulados representan desde hace tiempo una amenaza universal para la libertad, la democracia e, incluso, la salud, como se vio durante la pandemia por el COVID- 19. El consumo informativo en la era digital, en un entorno en el que conviven los medios de comunicación con fuentes anónimas, falsas o no especializadas en redes sociales, junto con los nuevos desafíos que trae la inteligencia artificial, convierte este fenómeno en un objeto de estudio muy significativo en la actualidad. Por ello, este libro analiza el fenómeno de los desórdenes informativos desde una perspectiva amplia, tomando en consideración diferentes ámbitos como el periodístico, sociológico y jurídico.
Teniendo presente la relevancia del derecho a la información como eje vertebrador del Estado de Derecho, la obra disecciona el poder de la desinformación en variados espacios como el judicial, científico o político, así como los nuevos escenarios que impone la inteligencia artificial o el auge de los discursos de odio y las teorías de la conspiración. A partir de este diagnóstico, este libro examina las posibles soluciones para este fenómeno: desde el establecimiento de un robusto marco normativo comunitario que luche contra los bulos hasta la labor que realizan las denominadas agencias de verificación.
Los autores y autoras de los diferentes capítulos que conforman este libro son investigadores y docentes universitarios y profesionales de reconocido prestigio del sector de la comunicación. De este modo, se aúnan el carácter académico con la visión del día a día de los creadores de información especializada.Junta de Andalucí
Oxidative electrochemical depolymerization of lignin using highly active self-standing electrocatalysts prepared by electrospinning of lignin
Get PDFElectrooxidative depolymerization of lignin enables obtaining renewable value-added chemicals under soft operation conditions. However, current nickel foam electrodes do not fully utilize their active phase. In this study, non-woven mats consisting of metal-containing carbon nanofibers were prepared by electrospinning of lignin and Ni, Co and/or Pd solutions. These mats, without further processing and additives, were tested as self-standing electrodes in the electrooxidative depolymerization of alkaline kraft lignin solution using a filter press electrolyzer at room temperature. The fibrillar electrocatalyst containing 10 % wt of Ni (CFNi10) showed the most promising results, producing i) up to 77 % of oxygen-rich depolymerized lignin solid, ii) a water-soluble fraction yield up to 19.8 % wt iii) total vanillin yield of 1.1 % wt, using specific charges as low as 250 C/glignin, outperforming the commercial nickel foam electrode, and iv) full reusability. Consequently, the activity of the process is improved, while the amount of nickel deployed on the electrochemical cell is notably decreased from 30 down to 0.3 mg/cm2. The results of the present paper also demonstrate that lignin electrochemical depolymerization needs to be promoted by reactive oxygen species and/or in-situ generation of hydrogen peroxide.Funding for open access charge: Universidad de Málaga / CBUA.
The authors wish to thank MICINN (TED-2021-131324B-C21 at MCIN/AEI/10.13039/501100011033, “Next GenerationEU”/PRTR) and Junta de Andalucía (UMA18-FEDERJA-110) for financial support. M.G.R. acknowledges the assistance of MICINN through an FPU Grant (FPU18/01402)
L'educazione e la formazione dinamica per l'inclusione socio-lavorativa dei giovani
Get PDFLa formazione, oggi più che mai, è uno strumento fondamentale per garantire non solo l'integrazione lavorativa dei giovani, ma anche per fornire loro le competenze necessarie per prosperare in un mondo in rapida evoluzione. Nel contesto attuale, in cui in Spagna il tasso di disoccupazione giovanile raggiunge il 28,36% e la percentuale di giovani con contratti temporanei è tra le più alte d'Europa, diventa evidente l'urgenza di adottare misure formative efficaci. L'educazione dinamica, mirata a rispondere alle esigenze del mercato del lavoro, non solo aumenta le possibilità di accesso al lavoro per i giovani, ma offre loro una via per costruire un futuro più stabile e meno precario