Most single-domain proteins show cooperative unfolding transitions at equilibrium: the cooperativity of protein folding makes it difficult to populate non-native protein structures [1,2]. Nevertheless, protein folding intermediates are known to exist [1,2] and alternative protein conformations have been demonstrated by numerous methods [2-41. A long-standing problem is how to populate non-nativ...

The paper discusses a multi-agent system for robot-soccer. The system consists of a supervisory controller, and controllers for attack, defense and goalie robots. Real time vector field based path planning, Petri-net theory and Q-learning technique are used in the design. Robot-soccer system has a dynamic environment. A soccer robot has to take an appropriate decision based on environment situa...

Reliable cell segmentation and classification from biomedical images is a crucial step for both scientific research and clinical practice. A major challenge for more robust segmentation and classification methods is the large variations in the size, shape and viewpoint of the cells, combining with the low image quality caused by noise and artifacts. To address this issue, in this work we propos...

Incremental Net Pro (IncNet Pro) with local learning feature and statistically controlled growing and pruning of the network is introduced. The architecture of the net is based on RBF networks. Extended Kalman Filter algorithm and its new fast version is proposed and used as learning algorithm. IncNet Pro is similar to the Resource Allocation Network described by Platt in the main idea of the e...

This article describes an application of competitive associative net called CAN2 to plane extraction from 3D range images measured by a laser range finer (LRF). The CAN2 basically is a neural net which learns efficient piecewise linear approximation of nonlinear functions, and in this application it is utilized for learning piecewise planner (linear) surfaces from the range data. As a result of...

P3 is an application designed for teaching Petri nets within a course on Architecture and Organization of Computers (AOC). Existing Petri net software implements different Petri net concepts, but does not give full support for learning their basic postulates. The idea of P3 is to enable learning Petri nets in a more obvious and quicker way in order to use them for hardware modeling. Therefore, ...

Previous algorithms for supervised sequence learning are based on dynamic recurrent networks. This paper describes alternative gradient-based systems consisting of two feed-forward nets which learn to deal with temporal sequences by using fast weights: The rst net learns to produce context dependent weight changes for the second net whose weights may vary very quickly. The method o ers a potent...

This paper discusses different feature selection methods and CO2 flux data sets with a varying quality-quantity balance for the application of Random Forest model to predict daily fluxes at 250 m spatial resolution Rur catchment area in western Germany between 2010 2018. Measurements from eddy covariance stations ecosystem types, remotely sensed vegetation MODIS, COSMO-REA6 reanalysis were used...

In this paper a neural network for solving partial differential equations is described. The activation functions of the hidden nodes are the radial basis functions (RBF) whose parameters are learnt by a two-stage gradient descent strategy. A new growing RBF-node insertion strategy with different RBF is used in order to improve the net performances. The learning strategy is able to save computat...