Technical University of Ostrava

About: Technical University of Ostrava is a education organization based out in Ostrava, Czechia. It is known for research contribution in the topics: Artificial neural network & Evolutionary algorithm. The organization has 4186 authors who have published 8936 publications receiving 65393 citations. The organization is also known as: Vysoká škola báňská – Technická univerzita Ostrava & VŠB – Technical University of Ostrava.

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

Abstract: This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem. It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors have implemented the basic version of NSGA-II, without making any changes in the operators; the second one is Modified NSGA-II, where the researchers have implemented NSGA-II after making some changes into it and finally, Hybrid NSGA-II variants, where the researchers have hybridized the conventional and modified NSGA-II with some other technique. The article analyses the modifications in NSGA-II and also discusses the various performance assessment techniques used by the researchers, i.e., test instances, performance metrics, statistical tests, case studies, benchmarking with other state-of-the-art algorithms. Additionally, the paper also provides a brief bibliometric analysis based on the work done in this study.

Waveform Effect on Fatigue Properties of Intact Sandstone in Uniaxial Cyclical Loading

Abstract: The effect of loading waveform and amplitude on the fatigue behaviour of intact sandstone was investigated using uniaxial cyclic loading conditions in the laboratory. In the first set of experiments sinusoidal, ramp and square waveforms were used at loading frequency of 5 Hz and peak amplitude of 0.05 mm. In another set of experiments, tests were conducted at a range of amplitudes varying from 0.05 to 0.3 mm at 5 Hz frequency using sinusoidal and ramp waveforms. It was found that loading waveform as well as amplitude is of great significance and affects the rock behaviour. It was found that fatigue behaviour is a function of the cyclic energy of the load and the shape of the waveform. Damage accumulated most rapidly under square waveforms with a high energy requirement. A ramp waveform was the least damaging of those considered. The loading waveforms strongly influenced the damage accumulation under cyclic loading conditions. Finally, it is concluded that machine behaviour in terms of amplitude affected the rock behaviour. This study has practical significance to the behaviour of rock and rock masses within the excavation systems subjected to cyclic loading.

Covalent Graphene‐MOF Hybrids for High‐Performance Asymmetric Supercapacitors

Abstract: In this work, the covalent attachment of an amine functionalized metal-organic framework (UiO-66-NH2 = Zr6 O4 (OH)4 (bdc-NH2 )6 ; bdc-NH2 = 2-amino-1,4-benzenedicarboxylate) (UiO-Universitetet i Oslo) to the basal-plane of carboxylate functionalized graphene (graphene acid = GA) via amide bonds is reported. The resultant GA@UiO-66-NH2 hybrid displayed a large specific surface area, hierarchical pores and an interconnected conductive network. The electrochemical characterizations demonstrated that the hybrid GA@UiO-66-NH2 acts as an effective charge storing material with a capacitance of up to 651 F g-1 , significantly higher than traditional graphene-based materials. The results suggest that the amide linkage plays a key role in the formation of a π-conjugated structure, which facilitates charge transfer and consequently offers good capacitance and cycling stability. Furthermore, to realize the practical feasibility, an asymmetric supercapacitor using a GA@UiO-66-NH2 positive electrode with Ti3 C2 TX MXene as the opposing electrode has been constructed. The cell is able to deliver a power density of up to 16 kW kg-1 and an energy density of up to 73 Wh kg-1 , which are comparable to several commercial devices such as Pb-acid and Ni/MH batteries. Under an intermediate level of loading, the device retained 88% of its initial capacitance after 10 000 cycles.

Brain-Computer Interface Based on Generation of Visual Images

Abstract: This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive Bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier.

Comparison of Heuristics for Scheduling Independent Tasks on Heterogeneous Distributed Environments

Abstract: Scheduling is one of the core steps to efficientlyexploit the capabilities of heterogeneous distributedcomputing systems and is an NP-complete problem.Therefore using meta-heuristic algorithms is asuitable approach in order to cope with its difficulty.In meta-heuristic algorithms, generating individualsin the initial step has an important effect on theconvergence behavior of the algorithm and finalsolutions. Using some heuristics for generating one ormore near-optimal individuals in the initial step canimprove the final solutions obtained by meta-heuristicalgorithms. Different criteria can be used forevaluating the efficiency of scheduling algorithms, themost important of which are makespan and flowtime.In this paper we propose an efficient heuristic methodand then we will compare with five popular heuristicsfor minimizing makespan and flowtime inheterogeneous distributed computing systems.