We researched cross-modal statistical learning conducting to experiments: a behavioural one and a neuroimaging one. In the analysis of the later we used neural decoding with temporal generalization.

In this paper, we present an effective computational strategy to design high-performance decentralized controllers with partial local-state information for vibration control of large building structures. Specifically, the ...

We develop a method to compute a basis of the associated order in a Hopf Galois structure H of the ring of integers O_L of an extension of number or p-adic fields L/K. We state and prove a necessary and sufficient condition ...

One still open question in the area of research of multi-layer feedforward neural networks is concerning the number of neurons in its hidden layer(s). Especially in real life applications, this problem is often solved by ...

Telecommunication operators are increasingly integrating computational infrastructure into their networks at different location levels, including the network edge. This makes a highly distributed processing environment a ...

We present a flexible, general, and efficient approach for implementing thermodynamic phase equilibria information (in the form of sets of physical parameters) into geophysical and geodynamic studies. The approach is based ...

The paper develops a method, called bounding regenerative transformation, for the computation with numerical stability and well-controlled error of bounds for the interval availability distribution of systems modeled by ...

The Pd/CeO2 system behaves as an efficient precatalyst for the Suzuki–Miyaura cross-coupling under mild conditions (298 K, in air) in ethanol/water. A broad range of aryl bromides, including those deactivated, and ...

Mining itemsets is a central task in data mining, both in the batch and the streaming paradigms. While robust, efficient, and well-tested implementations exist for batch mining, hardly any publicly available equivalent ...