Article
Computer Science, Information Systems
Mingjie Sun, Jimin Xiao, Eng Gee Lim, Yao Zhao
Summary: In this paper, a cycle-free pipeline method is proposed to tackle the weakly referring expression grounding task. It uses a region describer network to predict textual description for each candidate region and selects a result region based on the similarity between the predicted description and the query sentence. A self-paced learning mechanism is also designed to avoid the drift issue during the warm-up period of optimization. The proposed method achieves higher average accuracy compared with previous state-of-the-art methods on RefCOCO and RefCOCO+ datasets.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Physics, Multidisciplinary
Kiriil Kovalenko, Irene Sendina-Nadal, Nagi Khalil, Alex Dainiak, Daniil Musatov, Andrei M. Raigorodskii, Karin Alfaro-Bittner, Baruch Barzel, Stefano Boccaletti
Summary: The paper introduces a mechanism for generating synthetic simplicial complexes that display desired statistical properties observed in the real world, and can be straightforwardly extended to higher-order structures. The model constructs networks with scale-free degree distribution and bounded or scale-free generalized degree distribution through preferential and/or nonpreferential attachment mechanisms, providing analytical control of scaling exponents to construct synthetic complexes with desired statistical properties.
COMMUNICATIONS PHYSICS
(2021)
Article
Physics, Applied
Kensaku Chida, Akira Fujiwara, Katsuhiko Nishiguchi
Summary: This study converted Gaussian-distributed voltage noise into the non-equilibrium free energy of a nanometer-scale dot connected to an electron reservoir. By analyzing electron counting statistics, the energy transported into the dot as well as changes in internal energy and effective temperature were quantitatively analyzed in the noise-induced non-equilibrium steady state. It was confirmed that the rectification effect caused by the asymmetry with respect to electron motion direction is the origin of the increase in internal energy of the dot. The information obtained in this study clarifies the relationship between the non-equilibrium dynamics of a nanodevice and applied noise, providing a means to evaluate device operation using noise as a resource.
APPLIED PHYSICS LETTERS
(2023)
Article
Physics, Fluids & Plasmas
Nikita Frolov, Alexander Hramov
Summary: This paper explores the extension of self-organized bistability (SOB) on scale-free networks under coupling constraints. The study finds that SOB on scale-free networks originates from facilitated criticality and replicates extreme properties of epileptic seizure recurrences.
Article
Computer Science, Information Systems
Jinlong Ma, Junfeng Zhang, Yongqiang Zhang
Summary: A new gravitation path routing strategy is proposed in this paper, which aims to improve network traffic capacity by selecting optimal paths based on the gravitational centrality of nodes. Simulation results show that this strategy is more effective than a previous efficient routing strategy proposed by Yan et al.
Article
Physics, Fluids & Plasmas
Bartlomiej Dybiec, Karol Capala, Jakub Barbasz
Summary: The theory of stochastic processes and first-passage time theory are used to analyze noise-induced escape kinetics. The study finds that there is a set of favorable rope lengths for the shortest climbing times, and experienced climbers can decrease their climbing time by using longer ropes.
Article
Mathematics, Interdisciplinary Applications
Wenyue Zhang, Peiming Shi, Mengdi Li, Dongying Han, Yinghang He, Fengshou Gu, Andrew Ball
Summary: This paper proposes an adaptive bearing fault diagnosis method based on modulation periodic stochastic pooling networks (MPSPN) under unknown faults. By using the normalized least-mean-square (NLMS) algorithm, an adaptive weight allocation scheme is derived. Simulation and experimental results demonstrate that the MPSPN system can effectively diagnose unknown faults in bearings and significantly improve the signal-to-noise ratio (SNR) of the diagnostic output.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Multidisciplinary Sciences
Kevin B. Wood, Andrea Comba, Sebastien Motsch, Tomas S. Grigera, Pedro R. Lowenstein
Summary: This article investigates collective behavior in glioblastoma using time-resolved tracking of individual cells. The results show weakly polarized motion at the population level, with unexpected correlations in velocities over long distances. The study also proposes a data-driven maximum entropy model that captures statistical features of the experimental data. These findings suggest that glioblastoma assemblies may exhibit scale-free correlations and be near a critical point.
Article
Computer Science, Artificial Intelligence
Xiaoshuan Shi, Zhenhua Guo, Kang Li, Yun Liang, Xiaofeng Zhu
Summary: Noisy labels can significantly degrade the performance of convolutional neural networks (CNNs). This paper proposes a novel self-paced resistance framework to resist corrupted labels, using the memorization effect of CNNs and a resistance loss to update the model parameters. Extensive experiments demonstrate the superior performance of this framework on noisy-label data.
PATTERN RECOGNITION
(2023)
Article
Engineering, Electrical & Electronic
Mustafa A. Kishk, Mohamed-Slim Alouini
Summary: The reconfigurable intelligent surfaces (RIS) technology enhances the coverage probability of cellular networks by providing extra indirect line-of-sight (LoS) links through equipping obstacles with RISs. The deployment of RISs significantly improves the coverage regions of base stations (BSs), but the density of RISs required increases as the density of obstacles increases to ensure that the ratio of blind-spots to the total area is below 10^(-5).
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2021)
Article
Mathematics, Applied
Yuncheng Xu, Xiaojun Sun, Hua Hu
Summary: This study presents a stochastic SIQR epidemic model with demographics and non-monotone incidence rate on scale-free networks, incorporating stochastic perturbations to death rate. Mathematical analysis and numerical simulations have been conducted to prove the existence of a unique global positive solution, sufficient conditions for disease extinction, and the existence of ergodic stationary distribution. The results provide insights into the dynamics of epidemics considering various factors such as contact heterogeneity, quarantine measures, demographics, and random environments.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2022)
Article
Physics, Multidisciplinary
Qian Cheng, Yuangen Yao, Min Li, Zhouchao Wei, Ming Yi
Summary: This paper investigates the impact of memory effects on the logic operation of the Set-Reset latch and presents experimental results using harmonic-driven operation in a nonlinear fractional-order two-well potential system. The study reveals that certain harmonic driving forces can eliminate the memory effects, enabling the system to form a stable logic gate and implement logical vibrational resonance (LVR).
EUROPEAN PHYSICAL JOURNAL PLUS
(2022)
Article
Mathematics, Applied
Rundong Zhao, Qiming Liu, Meici Sun
Summary: The study introduces a new stochastic SIQS model for studying the impact of random environments during disease spread on scale-free networks. Global positive solutions are proven to exist, and sufficient conditions for disease extinction and persistence are established by constructing appropriate stochastic Lyapunov functions. The analysis results are verified through numerical simulations, and improvements are made on previous research findings.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2022)
Article
Physics, Multidisciplinary
Marcus V. Alves Ribeiro, Aurel Jurjiu, Mircea Galiceanu
Summary: The relaxation dynamics of a new type of hyperbranched polymer networks constructed using a degree distribution specific to scale-free networks are studied. The topology of the networks is controlled by three parameters: gamma, K-min, and K-max. The influence of these parameters and the stiffness parameter q on the relaxation quantities is investigated. Various scaling behaviors are observed in the dynamical quantities for different combinations of the parameters.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Wenfei Yang, Tianzhu Zhang, Zhendong Mao, Yongdong Zhang, Qi Tian, Feng Wu
Summary: This paper proposed an end-to-end Multi-Scale Structure-Aware Network (MSA-Net) for weakly supervised temporal action detection, which explores both the global and local structure information to effectively learn discriminative structure aware representations for robust and complete action detection. Extensive experimental results on two benchmark datasets demonstrate that MSA-Net outperforms state-of-the-art methods.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Mathematics, Applied
Uros Barac, Matjaz Perc, Marko Gosak
Summary: We investigate collective failures in biologically realistic networks with coupled excitable units using the FitzHugh-Nagumo model. We examine different factors such as coupling strength, bifurcation distances, and aging scenarios that contribute to collective failure. Our findings show that targeting high-degree nodes for inactivation leads to the longest global activity in the network, consistent with previous results. However, we also demonstrate that the most efficient strategy for collective failure depends on both coupling strength and the distance from the bifurcation point to oscillatory behavior.
Article
Mathematics, Interdisciplinary Applications
Tugba Palabas, Joaquin J. Torres, Matjaz Perc, Muhammet Uzuntarla
Summary: An increasing amount of evidence suggests that astrocytes, an abundant type of glial cells in the nervous system, not only support neurons structurally and metabolically, but also modulate neuronal and synaptic functions. However, their role in information processing, especially in the presence of noise, remains unclear. This study investigates the phenomenon of stochastic resonance in neuronal dynamics and shows that astrocytes can enhance the detection of weak signals in the presence of noise, indicating their potential role in noisy neuronal information processing.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Atiyeh Bayani, Sajad Jafari, Hamed Azarnoush, Fahimeh Nazarimehr, Stefano Boccaletti, Matjaz Perc
Summary: Transitions from incoherent to coherent dynamical states can be observed in various real-world networks, and they can be explosive or continuous. The nature of the transition changes depending on the initial conditions, and the critical coupling strength for explosive synchronization also depends on the initial conditions.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Wen-Jing Li, Zhi Chen, Jun Wang, Luo-Luo Jiang, Matjaz Perc
Summary: Relationships in social networks change over time due to factors such as mobility and preferences for moral behavior, which affect cooperation in collaborative networks. Individuals tend to move towards sites with high degrees, resulting in networks with higher average degrees and promoting cooperation. However, excessive mobility can lead to network structure dilution and well-mixed conditions. Optimal network reciprocity and robust cooperation require limited mobility, and similar patterns may apply to other forms of moral behavior.
CHAOS SOLITONS & FRACTALS
(2023)
Editorial Material
Mathematics, Interdisciplinary Applications
Marcos G. E. da Luz, Celia Anteneodo, Nuno Crokidakis, Matjaz Perc
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Applied
Mahtab Mehrabbeik, Sajad Jafari, Riccardo Meucci, Matjaz Perc
Summary: This paper studies the synchronization of globally coupled identical laser models via linear and nonlinear forms of diffusive couplings. The results show that complete synchronization can be achieved in laser models under linear diffusive function but not under nonlinear diffusive function. Multistability is observed in different network states such as cluster synchronization, chimera, and solitary states.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Multidisciplinary Sciences
Atefeh Ahmadi, Sourav Roy, Mahtab Mehrabbeik, Dibakar Ghosh, Sajad Jafari, Matjaz Perc
Summary: This paragraph discusses the duopoly Stackelberg model in game theory, where a leader and a follower firm compete in the market to maximize profit. Real-world markets can exhibit chaotic behaviors and unpredictable changes. Taking into account the heterogeneity of the firms, a Stackelberg model with heterogeneous players and marginal costs is proposed. The equilibrium points, including the Nash equilibrium, are calculated and their stability is analyzed. Different parameters are explored to understand the dynamics through bifurcation diagrams, Lyapunov exponents spectra, and Kaplan-Yorke dimension. By combining state feedback and parameter adjustment methods, the chaotic solutions of the model are tamed and it converges to the Nash equilibrium.
Article
Multidisciplinary Sciences
Arthur A. B. Pessa, Matjaz Perc, Haroldo V. Ribeiro
Summary: Cryptocurrencies are the latest innovation in finance, with significant impact on social, technological, and economic aspects. Previous research has focused on a few cryptocurrencies and ignored the influence of cryptocurrency age and market capitalization on price returns. This study comprehensively investigates large price variations in over 7000 digital currencies and explores whether price returns change with cryptocurrency market growth. The findings show that price returns follow power-law distributions and positive returns are more likely than negative ones. Furthermore, changes in power-law exponents are often related to cryptocurrency age and market capitalization or only to age, indicating the complex nature of cryptocurrency price movements.
SCIENTIFIC REPORTS
(2023)
Article
Physics, Multidisciplinary
I. Samoylenko, D. Aleja, E. Primo, K. Alfaro-Bittner, E. Vasilyeva, K. Kovalenko, D. Musatov, A. M. Raigorodskii, R. Criado, M. Romance, D. Papo, M. Perc, B. Barzel, S. Boccaletti
Summary: A wealth of evidence shows that real-world networks have the small-world property and most social networks exhibit the six degrees of separation, where individuals are within six connections of each other. However, the reason behind the ultrasmall-world organization of social networks is still unknown. This study demonstrates that the six degrees of separation is a feature of equilibrium state in networks, where individuals balance their aspiration for centrality and the costs of forming and maintaining connections.
Article
Computer Science, Interdisciplinary Applications
Burhaneddin Izgi, Murat Ozkaya, Nazim Kemal Ure, Matjaz Perc
Summary: In this paper, a novel machine learning-driven framework for solving large-scale zero-sum matrix games is proposed. The framework combines the estimations from the extended matrix norm method and the payoff matrix, and provides rapid estimation of the game value through a neural network architecture. Experimental results demonstrate that the framework can accurately predict the values for games with up to 50 strategies, and real-time solution predictions can be obtained after the network training, making it useful for real-world applications.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Bartu Yesilkaya, Ebru Sayilgan, Yilmaz Kemal Yuce, Matjaz Perc, Yalcin Isler
Summary: We propose a manifold learning framework to classify SSVEP data by reducing the number of features and comparing lower dimensional matrices with well-known machine learning algorithms. Among five manifold learning methods and nine machine learning algorithms, Principal Component Analysis shows the best classifier performance and achieves the highest accuracy when combined with the Naive Bayes classifier for a 7-class classification problem.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Neurosciences
Murside Degirmenci, Yilmaz Kemal Yuce, Matjaz Perc, Yalcin Isler
Summary: In recent studies, researchers in the field of Brain-Computer Interface (BCI) have focused on Motor Imagery tasks, specifically on the classification of Electroencephalogram (EEG) signals. The study investigates the effect of statistical significance-based feature selection on the classification of Motor Imagery EEG signals, using various time-domain, frequency-domain, time-frequency domain, and non-linear parameters. By analyzing the results, it is found that the statistical significance-based feature selection approach improves the classifier performance in Motor Imagery task classification.
FRONTIERS IN HUMAN NEUROSCIENCE
(2023)
Article
Multidisciplinary Sciences
Andre S. S. Sunahara, Arthur A. B. Pessa, Matjaz Perc, Haroldo V. V. Ribeiro
Summary: This study investigates the COVID-19 pandemic in the city of Maringa, Brazil, and finds that despite prompt and robust interventions, cases increased exponentially during the early spread of the disease. Non-pharmaceutical interventions had a significant impact on controlling the pandemic, but the city's measures were primarily reactive. Maringa faced six waves of cases, with the third and fourth waves being the deadliest and overwhelming the local healthcare system. The study highlights the heterogeneities in the spread and impact of the disease compared to the national context and other similarly sized cities. Importance rating: 8 out of 10.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Sourav Roy, Sayantan Nag Chowdhury, Srilena Kundu, Gourab Kumar Sar, Jeet Banerjee, Biswambhar Rakshit, Prakash Chandra Mali, Matjaz Perc, Dibakar Ghosh
Summary: In this study, we use the prisoner's dilemma game to investigate the intricate interplay between ecological and evolutionary processes. We consider delays and explore how these delays can affect prosocial behavior. Analytical calculations and numerical simulations show that delays can lead to oscillations, and by incorporating altruistic free space and punishment as factors, we examine their impact on population and community dynamics. Depending on parameter values and initial strategies, our eco-evolutionary model can exhibit cyclic dominance or chaotic behavior, emphasizing the importance of complex dynamics for the management and conservation of ecological communities. This research contributes to a broader understanding of group decision-making and moral behavior in multidimensional social systems.
SCIENTIFIC REPORTS
(2023)
Article
Physics, Fluids & Plasmas
Kaipeng Hu, Pengyue Wang, Junzhou He, Matjaz Perc, Lei Shi
Summary: This study investigates the interactions among individuals in different populations, finding that interactions across multiple populations can promote the evolution of cooperation depending on the level of interaction asymmetry. If interactions within and between populations are symmetric, the presence of multiple populations alone can promote the evolution of cooperation. Asymmetric interactions can further promote cooperation but at the expense of the coexistence of competing strategies.
