Crawler robot kinematics modeling by using a two-wheeled approach

The aim of this paper is to analyze the kinematics of a small crawler robot. A mathematical model of kinematics based on a two-wheeled approach is proposed. This model is experimentally verified using vision-based motion measurements of a crawler vehicle equipped with encoders and a remote control system. It is assumed that the vehicle moves along a few curves with different angular speeds of its wheels. Based on the model of motion and the values of these speeds, numerical simulations are investigated. The results obtained from numerical and experimental validation are presented and discussed. The comparison delivered some important conclusions.

     

A quadratic boundedness approach to a neural network-based simultaneous estimation of actuator and sensor faults

Neural Computing and Applications - The paper is devoted to the problem of a neural network-based robust simultaneous actuator and sensor faults estimator design for the purpose of the fault...     

Evolutionary Algorithm Integrating Stress Heuristics for Truss Optimization

The optimal truss design using problem-oriented evolutionary algorithm is presented in the paper. The minimum weight structures subjected to stress and displacement constraints are searched. The discrete design variables are areas of members, selected from catalogues of available sections. The integration of the problem specific knowledge into the optimization procedure is proposed. The heuristic rules based on the concept of fully stressed design are introduced through special genetic operators, which use the information concerning the stress distribution of structural members. Moreover, approximated solutions obtained by deterministic, sequential discrete optimization methods are inserted into the initial population. The obtained hybrid evolutionary algorithm is specialized for truss design. Benchmark problems are calculated in numerical examples. The knowledge about the problem integrated into the evolutionary algorithm can enhance considerably the effectiveness of the approach and improve significantly the convergence rate and the quality of the results. The advantages and drawbacks of the proposed method are discussed.     

Characterization of catalysts obtained from rapidly quenched alloy precursors by electrochemical/chemical processes of material degradation—selected examples

Rapidly quenched amorphous alloys—containing metallic or metalloid elements—are precursors for selective catalysts of many technically important reactions. To increase their activity, various methods of material degradation occurring at the surface and in the bulk of the rapidly quenched alloys have been used for promoting the catalytic performance of such materials. The modifications of the structure, composition, and morphology of the substrate proved to be efficient in transforming inactive metal alloy precursors into active and selective catalysts for hydrogenation, and dehydrogenation of organic compounds, as well as for other processes like steam reforming of methanol. This article presents several examples of characterization of such catalysts and discusses their selectivity and activity in a connection with physical and chemical properties of their surfaces. Moreover, it is shown that scanning electron microscopy, Auger electron spectroscopy, scanning Auger microscopy, and energy dispersive spectrometry allowed the local changes occurring during the activation process to be identified and their implications for catalytic function to be considered.     

MCFC versus other fuel cells—Characteristics, technologies and prospects

Characteristics of molten carbonate fuel cell (MCFC) were critically compared to these of polymer electrolyte membrane fuel cell (PEMFC), alkaline fuel cell (AFC), phosphoric acid fuel cell (PAFC) and solid oxide fuel cell (SOFC). In comparison to the other fuel cells, the MCFC operates with the lowest current densities due to limited zones of effective electrode reactions and low solubilities of oxygen and hydrogen in molten carbonates; also it has a thickest electrodes–electrolyte assembly. In consequence, the applications of MCFC are almost limited to stationary power generators. Although the MCFC stationary power generators have now approached high technological level of precommercialization, in the future they may face a serious contest from SOFC and PEMFC, for which improvement of operational parameters is believed to be achieved easier.     

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5′- and 3′-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.     

Extraction of diffuse objects from images by means of watershed and region merging: example of solar images.

This paper presents a new method for extraction of diffuse objects from images, which was developed for segmentation of solar images obtained from extreme-UV imaging telescope (EIT) experiments of the satellite SOHO mission. As a particular type of objects to be extracted coronal holes in EIT images have been chosen. The method described is based on the use of a watershed algorithm. The result of the watershed segmentation is a partition of the whole domain of the image into a large number of small regions. These regions are then combined in a region merging process. The proposed region merging algorithm iteratively adds the darkest regions and maximizes the average contrast between a current mask and a set of its neighboring regions. We show that the maximization of the average contrast gives segmentation results that are visually acceptable. Furthermore, this approach allows us to conduct the segmentation of EIT images independently of any explicit fine-tuning parameters. The proposed method was extensively tested on EIT images obtained at various times and various levels of solar activity, and we will show that it can be used independently of the local brightness level and the extent of coronal holes.