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Developing electroencephalogram (EEG) based brain-computer interface (BCI) systems is challenging. In this study, we analyzed natural grasp actions from EEG. Ten healthy subjects participated in this experiment. They executed and imagined…

Human-Computer Interaction · Computer Science 2020-02-06 Jeong-Hyun Cho , Ji-Hoon Jeong , Dong-Joo Kim , Seong-Whan Lee

Computing the grain boundary (GB) counterparts to bulk phase diagrams represents an emerging research direction. Using a classical embrittlement model system Ga-doped Al alloy, this study demonstrates the feasibility of computing…

Materials Science · Physics 2022-01-20 Chongze Hu , Yanwen Li , Zhiyang Yu , Jian Luo

When re-structuring patient cohorts into so-called population graphs, initially independent data points can be incorporated into one interconnected graph structure. This population graph can then be used for medical downstream tasks using…

Social and Information Networks · Computer Science 2023-09-20 Tamara T. Mueller , Sophie Starck , Leonhard F. Feiner , Kyriaki-Margarita Bintsi , Daniel Rueckert , Georgios Kaissis

Electroencephalogram (EEG) based brain-computer interface (BCI) systems are useful tools for clinical purposes like neural prostheses. In this study, we collected EEG signals related to grasp motions. Five healthy subjects participated in…

Human-Computer Interaction · Computer Science 2020-05-12 Jeong-Hyun Cho , Ji-Hoon Jeong , Seong-Whan Lee

Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations…

Machine Learning · Computer Science 2022-05-11 Jurijs Nazarovs , Ronak R. Mehta , Vishnu Suresh Lokhande , Vikas Singh

We study 1D Hamilton systems with homogeneous power law potential and their statistical behaviour, assuming the microcanonical distribution of the initial conditions and describing its change under monotonically increasing time-dependent…

Chaotic Dynamics · Physics 2015-06-19 Dimitris Andresas , Marko Robnik

The dual-fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations,…

Strongly Correlated Electrons · Physics 2017-08-02 Jan Gukelberger , Evgeny Kozik , Hartmut Hafermann

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

Multidimensional efficiency maps are commonly used in high energy physics experiments to mitigate the limitations in the generation of large samples of simulated events. Binned multidimensional efficiency maps are however strongly limited…

High Energy Physics - Experiment · Physics 2020-05-19 C. Badiali , F. A. Di Bello , G. Frattari , E. Gross , V. Ippolito , M. Kado , J. Shlomi

Breaking of ensemble equivalence between the microcanonical ensemble and the canonical ensemble may occur for random graphs whose size tends to infinity, and is signaled by a non-zero specific relative entropy of the two ensembles. In [3]…

Statistical Mechanics · Physics 2018-08-22 Andrea Roccaverde

We consider the problem of estimating the difference between two functional undirected graphical models with shared structures. In many applications, data are naturally regarded as high-dimensional random function vectors rather than…

Machine Learning · Statistics 2019-11-19 Boxin Zhao , Y. Samuel Wang , Mladen Kolar

We made a comparative analysis of numerical methods for multidimensional optimization. The main parameter is a number of computations of the test function to reach necessary accuracy, as it is computationally "slow". For complex functions,…

Instrumentation and Methods for Astrophysics · Physics 2013-10-09 Ivan L. Andronov , Maria G. Tkachenko

A multicanonical formalism is introduced to describe statistical equilibrium of complex systems exhibiting a hierarchy of time and length scales, where the hierarchical structure is described as a set of nested "internal heat reservoirs"…

Statistical Mechanics · Physics 2012-11-15 Domingos S. P. Salazar , Giovani L. Vasconcelos

Motor imagery classification is of great significance to humans with mobility impairments, and how to extract and utilize the effective features from motor imagery electroencephalogram(EEG) channels has always been the focus of attention.…

Signal Processing · Electrical Eng. & Systems 2021-09-10 Yan Li , Ning Zhong , David Taniar , Haolan Zhang

We study the distribution of the number of (non-backtracking) periodic walks on large regular graphs. We propose a formula for the ratio between the variance of the number of $t$-periodic walks and its mean, when the cardinality of the…

Mathematical Physics · Physics 2015-03-19 Idan Oren , Uzy Smilansky

We review the paradigm of holographic dark energy (HDE), which arises from a theoretical attempt of applying the holographic principle (HP) to the dark energy (DE) problem. Making use of the HP and the dimensional analysis, we derive the…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-24 Shuang Wang , Yi Wang , Miao Li

Normal and anomalous diffusion are ubiquitous in many complex systems [1] . Here, we define a time and space generalized diffusion equation (GDE), which uses fractional-time derivatives and transformed d-path Laplacian operators on…

Physics and Society · Physics 2022-02-02 Fernando Diaz-Diaz , Ernesto Estrada

Ergodicity, this is to say, dynamics whose time averages coincide with ensemble averages, naturally leads to Boltzmann-Gibbs (BG) statistical mechanics, hence to standard thermodynamics. This formalism has been at the basis of an enormous…

Statistical Mechanics · Physics 2009-11-10 Constantino Tsallis , Celia Anteneodo , Lisa Borland , Roberto Osorio

Holographic dark energy (HDE) describes the vacuum energy in a cosmic IR region whose total energy saturates the limit of avoiding the collapse into a black hole. HDE predicts that the dark energy equation of the state transiting from…

Cosmology and Nongalactic Astrophysics · Physics 2021-01-04 Wei-Ming Dai , Yin-Zhe Ma , Hong-Jian He

Node role explainability in complex networks is very difficult, yet is crucial in different application domains such as social science, neurosciences or computer science. Many efforts have been made on the quantification of hubs revealing…

Neurons and Cognition · Quantitative Biology 2023-02-01 Lucrezia Carboni , Michel Dojat , Sophie Achard