Brno University of Technology

About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Computer science & Fracture mechanics. The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.

Mapping of the metal intake in plants by large-field X-ray microradiography and preliminary feasibility studies in microtomography

Abstract: This paper reports on dual energy micro-radiography and tomography techniques applied both to thin plant leaves treated with copper or lead solutions and on Cu-treated small roots and stem sections, performed at the SYRMEP X-ray beamline of ELETTRA synchrotron facility in Trieste (Italy). The features of the source allowed us to apply different imaging techniques with an extremely vast field of view, up to 160 ×6 mm2 and 28×6 mm2 for micro-radiography and tomography experiments, respectively. The feasibility of getting positive indications on metal accumulation in leaves, sections of roots and stems, stem and root whole cylindrical pieces has been checked.

Master Sintering Curve - A Practical Approach to its Construction

Abstract: The concept of a Master Sintering Curve (MSC) is a strong tool for optimizing the sintering process. However, constructing the MSC from sintering data involves complicated and time- consuming calculations. A practical method for the construction of a MSC is presented in the paper. With the help of a few dilatometric sintering experiments the newly developed software calculates the MSC and finds the optimal activation energy of a given material. The software, which also enables sintering prediction, was verified by sintering tetragonal and cubic zirconia, and alumina of two different particle sizes.

Characterization of acoustic and electromagnetic emission sources

Abstract: The creation of cracks is accompanied by electric charge redistribution due to loosened chemical bonds. Electric charges on crack walls create dipole moments. Vibrations of crack walls produce time-dependent dipole moments and, consequently, electric and magnetic fields are generated. An electric signal is induced on metal electrodes. Information about the vibration of crack walls was obtained from this signal analysis. For crack lengths below 1 mm the electrical signal has a frequency of over 2 MHz. In this paper the frequency analysis was performed in a frequency band of up to 5 MHz.

Data analytics of social media publicity to enhance household waste management

Abstract: Household waste segregation and recycling is ranked at a high priority of the waste management hierarchy. Its management remains a great challenge due to the high dependency on social behaviours. The integration of Internet of Things (IoT) and subscription accounts on social media platforms related to household waste management could be an effective and environmentally friendly publicity approach than traditional publicity via posters and newspapers. However, there is a paucity of literature on measuring social media publicity in household waste management, which brings challenges for practitioners to characterise and improve this publicity pathway. In this study, under an integrated framework, data mining approaches are employed or extended for multidimensional publicity analytics using the data of online footprints of propagandist and users. A real-world case study based on a subscription account on the WeChat platform, Shanghai Green Account, is analysed to reveal useful insights for personalised improvements of household waste management. This study suggests that the current publicity related to household waste management leans towards propagandist-centred in both timing and topic dimensions. The identified timing, which has high user engagement, is 12:00-13:00 and 21:00-22:00 on Thursday. The overall relative publicity quality of historical posts is calculated as 0.95. Average user engagement under the macro policy in Shanghai was elevated by 138.5% from 2018 to 2019, during which the collections of biodegradable food waste and recyclable waste were elevated by 88.8% and 431.8%. Intelligent decision support by publicity analytics could enhance household waste management through effective communication.