Search · four archives
Search · four archives
18 papers · ranked by Valyu relevance
Navid Entezari, Zakieh Hassanzadeh, Fariba Bahrami, Ahmad Kalhor
Motor skill acquisition involves dynamic co-adaptation of brain and behavior, yet the temporal coupling between neural and kinematic processes during learning remains unclear. Traditional analyses often treat the brain and behavior independently, potentially overlooking their interactive dynamics. In this study, we…
Hanhuai Zhu, Jingjing Huang, Zhi-Xi Wang, Shao-Ming Fei
Recurrence Plot (RP) is a method employed to analyze the periodicity, chaoticity, and nonlinear characteristics of complex systems. Quantum Principal Component Analysis (QPCA), on the other hand, achieves dimensionality reduction of sample data using density matrices based on quantum circuits. We improve the distance…
M Ashwin Ganesh, Akhil Aravind, Balasundaram Mohan, Saptarshi Basu
- Mesoscale combustor flame regimes analyzed from both dynamical systems and statistical standpoints. - Recurrence Quantification and Statistical-Spectral analyses on experimentally acquired signals revealed interesting physical insights into their evolution dynamics. - Recurrence plots, Phase plots and Scalograms…
Huan Zhao, Liangyuan Li, Junxiao Xie, Junyi Cao + 3 more
Introduction Parkinson's disease (PD) is a typical neurodegenerative disorder characterized by progressive motor impairments. Gait analysis offers a promising avenue for non-invasive PD diagnosis, yet extracting discriminative features from gait signals remains challenging. Methods This study proposed an intelligent…
Ayşenur Hatipoğlu, Ersen Yılmaz, Ying Zheng, Ke Zhang + 2 more
Accurate anomaly detection in rotating machinery under noisy conditions remains challenging in Prognostics and Health Management (PHM). Existing deep learning autoencoders and attention mechanisms rely primarily on data-driven similarity measures and fail to explicitly incorporate nonlinear dynamical characteristics of…
Hyun-Gee Jei, Caleb J. Armstrong, Farzan Sasangohar
Modern command, control, communications, computers, cyber, intelligence, surveillance, and reconnaissance (C5ISR) environments place substantial attentional demands on mission commanders. Failures in attention allocation in these high-risk settings can have severe operational consequences. This study investigates the…
Cyril Chatain, Sofiane Ramdani, Nicolas Paleiron, Fanny Cucchietti Waltz + 3 more
According to the “loss of complexity” theory, aging and disease are expected to reduce complexity of physiological outputs, thereby limiting the system’s adaptability. However, it remains unclear whether this concept applies to the neuromuscular system in people with chronic obstructive pulmonary disease (pwCOPD). This…
Atef Abdelkader, Haiqa Ehsan, Adil Jhangeer, Ewa Korzeniewska
In this work, we explore a piezoelectric neuron model in deterministic perturbations and stochastic forcing due to its use in mechanically driven sensing systems and neuromorphic sensor design. The model comprises of fast activation and slow recovery behaviors and constitutes a multiscale excitable system, converting…
Daiju Ikawa, Akito Miura, Kohei Miyata, Kazutoshi Kudo
Manual support and interpersonal interaction can enhance postural stability during upright standing, yet it remains unclear how tactile and visual interactions influence the temporal organization of postural control. We used a 2 × 2 factorial design manipulating interpersonal touch (Touch vs. No Touch) and partner…
Krzysztof Kęcik, Marcin Sałata, Waris Nawaz Khan, Nitin Saini
This paper presents a comprehensive analysis of the flute grinding process in end cutters, focusing on the influence of machining parameters on recurrence indicators. Recurrence quantification analysis (RQA) was employed to assess the dynamic behavior, regularity, and predictability of the process. Based on…
Tomasz Szołdra, Matheus S. Palmero, Peter Schmelcher
Observables of out-of-equilibrium quantum many-body systems display complex temporal behavior that encodes the underlying physical mechanisms but typically resists straightforward interpretations. We introduce recurrence analysis - a nonlinear time-series analysis framework long established for classical dynamical…
Norbert Marwan
Recurrence quantification analysis (RQA) is a widely used tool for studying complex dynamical systems, but its standard implementation requires computationally expensive calculations of recurrence plots (RPs) and line length histograms. This study introduces strategies to compute RQA measures directly from time series…
Himadri S Samanta
Digital biomarkers for depression have largely relied on static acoustic descriptors, pooled summary statistics, or conventional machine learning representations. Such approaches may miss nonlinear temporal organization embedded in conversational vocal dynamics. We hypothesized that depression is associated with…
Tuan D. Pham
Cross-domain analysis of spatial transcriptomics is challenging because tissues from different organs, diseases and experimental platforms exhibit distinct cellular compositions, spatial organisations and technical biases, making direct comparison of tissue states difficult. Existing methods primarily focus on domain…
Christos Chatzis, David Horner, Rasmus Bro, Ann-Marie Malby Schoos + 2 more
Temporal multivariate data is ubiquitous in many domains, for instance, being collected over time at planned visits (every few months/years) in longitudinal cohorts, or every few minutes/hours in challenge tests. The analysis of such data often focuses on revealing the underlying temporal patterns common across…
Davide Gheza, Michael C. Freund, Thea R. Zalabak, Wouter Kool
How can humans manage multiple sources of information competing for attention? To approach this question, we adopted a multi-dimensional task-set interference paradigm that requires individuals to handle distractions from three independent dimensions. Behavioral results suggest that people track prior interference from…
Authors not listed
We present an updated version of a priori computational intelligence, a methodology that integrates semi-empirical Quantum Mechanics calculations with supervised machine learning to predict optimal reaction conditions without prior extensive experimental work. First, the synergy between semi-empirical calculations and…
Nazila Ahmadi Daryakenari, Seyed Kamaleddin Setaredan
Schizophrenia (SZ) is a chronic and complex mental disorder associated with neurobiological deficits. The complexity and heterogeneity of schizophrenia symptoms pose challenges for objective diagnosis, which is currently based on behavioral and clinical manifestations. Furthermore, other psychiatric disorders such as…