• Exploring Interpretable AI Methods for ECG Data Classification 

      Ojha, Jaya; Haugerud, Hårek; Yazidi, Anis; Lind, Pedro (Chapter, 2024)
      We address ECG data classification, using methods from explainable artificial intelligence (XAI). In particular, we focus on the extended performance of the ST-CNN-5 model compared to established mod- els. The model ...
    • EyeT4Empathy: Dataset of foraging for visual information, gaze typing and empathy assessment 

      Lencastre, Pedro; Bhurtel, Samip; Yazidi, Anis; Mello, Gustavo Borges Moreno E; Denysov, Sergiy; Lind, Pedro (Scientific Data;9, Article number: 752 (2022), Peer reviewed; Journal article, 2022-12-03)
      We present a dataset of eye-movement recordings collected from 60 participants, along with their empathy levels, towards people with movement impairments. During each round of gaze recording, participants were divided into ...
    • Frequency-band based synthetic EEG generation 

      Rahman, Md Mahbubur (Master thesis, 2024)
      Electroencephalography (EEG) is a key technology in brain research because it offers non-invasive, high-temporal resolution information about the brain's electrical activity. This technology is now widely used in clinical ...
    • Gearbox Anomaly Detection In Wind Turbines Using Classical Machine Learning 

      Tran, Duy Cong (Master thesis, 2024)
      The primary goal of this master thesis is to develop a data-driven model that can classify or predict the anomalies of wind turbines’ gearboxes by applying machine learning techniques. Firstly, the thesis reviews the ...
    • Generating realistic eye-tracking data with Transformers 

      Naval Ruiz, Arnau (Master thesis, 2023)
      Eye-gaze forecasting is a field with a significant number of applications, such as User Interface analysis or improving self-driving cars. Despite its importance, this type of data can be hard to come by due to laws ...
    • Heterogeneities in electricity grids strongly enhance non-Gaussian features of frequency fluctuations under stochastic power input 

      Wolff, Matthias; Schmietendorf, Katrin; Lind, Pedro; Kamps, Oliver; Peinke, Joachim; Maass, Philipp (Chaos;Volume 29, Issue 10, Journal article; Peer reviewed, 2019-10-08)
      Stochastic feed-in of fluctuating renewable energies is steadily increasing in modern electricity grids, and this becomes an important risk factor for maintaining power grid stability. Here, we study the impact of wind ...
    • How Fast Can We See? An Eye-Tracking Study on Perceiving High-Frequency Stimuli 

      Mathema, Rujeena (Master thesis, 2024)
      The exploration of human cognition has fascinated philosophers and scientists for centuries. With the advent of high-frequency computer monitors, it's now possible to present quickly vanishing visual stimuli and investigate ...
    • Identifying Autism Gaze Patterns in Five-Second Data Records 

      Lencastre, Pedro; Lotfigolian, Maryam; Lind, Pedro (Peer reviewed; Journal article, 2024)
      One of the most challenging problems when diagnosing autism spectrum disorder (ASD) is the need for long sets of data. Collecting data during such long periods is challenging, particularly when dealing with children. This ...
    • Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol 

      Haraldsen, Ira Hebold; Hatlestad-Hall, Christoffer; Marra, Camillo; Renvall, Hanna; Maestú, Fernando; Acosta-Hernández, Jorge; Alfonsin, Soraya; Andersson, Vebjørn; Anand, Abhilash; Ayllón, Victor; Babic, Aleksandar; Belhadi, Asma; Birck, Cindy; Bruña, Ricardo; Caraglia, Naike; Carrarini, Claudia; Christensen, Erik; Cicchetti, Americo; Daugbjerg, Signe; Di Bidino, Rossella; Diaz-Ponce, Ana; Drews, Ainar; Giuffrè, Guido Maria; Georges, Jean; Gil-Gregorio, Pedro; Gove, Dianne; Govers, Tim M.; Hallock, Harry; Hietanen, Marja; Holmen, Lone; Hotta, Jaakko; Kaski, Samuel; Khadka, Rabindra; Kinnunen, Antti S.; Koivisto, Anne M.; Kulashekhar, Shrikanth; Larsen, Denis; Liljeström, Mia; Lind, Pedro; Marcos Dolado, Alberto; Marshall, Serena; Merz, Susanne; Miraglia, Francesca; Montonen, Juha; Mäntynen, Ville; Øksengård, Anne Rita; Olazarán, Javier; Paajanen, Teemu; Peña, José M.; Peña, Luis; Peniche, Daniel lrabien; Sanz Perez, Ana; Radwan, Mohamed; Ramírez-Toraño, Federico; Rodríguez-Pedrero, Andrea; Saarinen, Timo; Salas-Carrillo, Mario; Salmelin, Riitta; Sousa, Sonia; Suyuthi, Abdillah; Toft, Mathias; Toharia, Pablo; Tveitstøl, Thomas; Tveter, Mats; Upreti, Ramesh; Vermeulen, Robin J.; Vecchio, Fabrizio; Yazidi, Anis; Rossini, Paolo Maria (Peer reviewed; Journal article, 2023)
      More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain ...
    • Interactive evolution of artificial life art 

      Dumo, Glare Eugenio (ACIT;2022, Master thesis, 2022)
      In this thesis, we designed and presented an interface which is used for creating art using tools from artificial intelligence and artificial life. The interface is used for conducting two different experiments, one for ...
    • Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark 

      Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Peer reviewed; Journal article, 2023)
      Reservoir computing with cellular automata (ReCAs) is a promising concept by virtue of its potential for effective hardware implementation. In this paper, we explore elementary cellular automata rules in the context of ...
    • jumpdiff: A Python Library for Statistical Inference of Jump-Diffusion Processes in Observational or Experimental Data Sets 

      Rydin Gorjão, Leonardo; Witthaut, Dirk; Lind, Pedro (Journal of Statistical Software;, Peer reviewed; Journal article, 2023)
      We introduce a Python library, called jumpdiff, which includes all necessary functions to assess jump-diffusion processes. This library includes functions which compute a set of non-parametric estimators of all contributions ...
    • Lévy Flight Model of Gaze Trajectories to Assist in ADHD Diagnoses 

      Papanikolaou, Christos; Sharma, Akriti; Lind, Pedro; Lencastre, Pedro (Peer reviewed; Journal article, 2024)
      Theprecisemathematicaldescriptionofgazepatternsremainsatopicofongoingdebate, impacting the practical analysis of eye-tracking data. In this context, we present evidence supporting the appropriateness of a Lévy flight ...
    • A Markov-chain model for assessing heatwaves and droughts in Iberian Peninsula 

      Takyi, Ebenezer; Lind, Pedro; Russo, Ana (Chapter; Peer reviewed; Conference object; Journal article, 2024)
      The Iberian Peninsula subregion is known for the increasing frequency and intensity of heatwaves and drought conditions, but a comprehensive understanding of the statistical dependencies between these events is still ...
    • Mathematical insights into eye gaze dynamics of autistic children 

      Lotfigolian, Maryam (Master thesis, 2023)
      Early detection and diagnosis of Autism Spectrum Disorder (ASD) is crucial for effective intervention and improved outcomes. Eye-tracking technology offers a non-invasive and objective method for detecting autism symptoms, ...
    • A Model for Assessing the Quantitative Effects of Heterogeneous Affinity in Malaria Transmission along with Ivermectin Mass Administration 

      Sequeira, Joao; Louca, Jorge; Mendes, Antonio; Lind, Pedro (Applied Sciences;Volume 10 / Issue 23, Journal article; Peer reviewed, 2020-12-04)
      Using an agent-based model of malaria, we present numerical evidence that in communities of individuals having an affinity varying within a broad range of values, disease transmission may increase up to 300%. Moreover, our ...
    • Modeling Wind-Speed Statistics beyond the Weibull Distribution 

      Lencastre, Pedro; Yazidi, Anis; Lind, Pedro (Peer reviewed; Journal article, 2024)
      While it is well known that the Weibull distribution is a good model for wind-speed measurements and can be explained through simple statistical arguments, how such a model holds for shorter time periods is still an open ...
    • Modeling Wind-Speed Statistics beyond the Weibull Distribution 

      Rego Lencastre e Silva, Pedro; Yazidi, Anis; Lind, Pedro (Energies;, Peer reviewed; Journal article, 2024)
      While it is well known that the Weibull distribution is a good model for wind-speed measurements and can be explained through simple statistical arguments, how such a model holds for shorter time periods is still an open ...
    • Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes? 

      Rego Lencastre e Silva, Pedro; Gjersdal, Marit; Gorjão, Leonardo Rydin; Yazidi, Anis; Lind, Pedro (Peer reviewed; Journal article, 2023)
      The usage of generative adversarial networks (GAN)s for synthetic time-series data generation has been gaining popularity in recent years with applications from finance to music composition and processing of textual ...
    • A mutual information approach on fNIRS functional connectivity network 

      Romero, Sergio Alejandro Sotres (ACIT;2021, Master thesis, 2021)
      The functional near-infrared spectroscopy (fNIRS), as a brain imaging modality, is a versatile technique for understanding brain activity processes at the level of the brain cortex. The use of this technology facilities ...