In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. ...

This systematic review aims to (i) evaluate functional near infrared spectroscopy (fNIRS) walking study design in young adults, older adults and people with Parkinson's disease (PD); (ii) examine signal processing techniques ...

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized ...

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a ...

The aim of this study is to analyze dual-task effects on free and adaptive gait in Alzheimer's disease (AD) patients. Nineteen elders with AD participated in the study. A veteran neuropsychiatrist established the degree ...

The aim of this study is to analyze dual-task effects on free and adaptive gait in Alzheimer's disease (AD) patients. Nineteen elders with AD participated in the study. A veteran neuropsychiatrist established the degree ...

Modern robotic systems are increasingly powerful in terms of sensor fusion and mobility. Present technological progress allows advanced robots to cope progressively much better also with complex environments such as those ...

In this article we characterize inverse M-matrices and potentials whose inverses are supported on trees. In the symmetric case we show they are a Hadamard product of tree ultrametric matrices, generalizing a result by ...

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and ...