| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Nowicki, Michał
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (24/24 displayed)
- 2021LTspice Implementation of Gyrator-Capacitor Magnetic Circuit Model Considering Losses and Magnetic Saturation for Transient Simulations of Switching Mode Power Supplies Utilizing Inductive Elements with Cores Made of Amorphous Alloys
- 2020Magnetic Moment Measurement Standcitations
- 2020Seebeck Coefficient Measurement in Amorphous Alloys
- 2020Accuracy of frame-shaped samples based measurements of magnetoelastic characteristics of soft magnetic materialscitations
- 2020Soft magnetic cobalt based amorphous alloys with low saturation inductioncitations
- 2019Relative Seebeck coefficient differences used for metal sortingcitations
- 2019Strain Dependence of Hysteretic Giant Magnetoimpedance Effect in Co-Based Amorphous Ribboncitations
- 2019Experimental Verification of Isotropic and Anisotropic Anhysteretic Magnetization Modelscitations
- 2019Stress Dependence of Seebeck Coefficient in Iron-Based Amorphous Ribbonscitations
- 2018Modeling the Hysteresis Loop of Ultra-High Permeability Amorphous Alloy for Space Applicationscitations
- 2018Two phase magnetic material modelling using two dimensional extended Preisach modelcitations
- 2018Measurement System for Magnetic Field Sensors Testing with Earth’s Magnetic Field Compensationcitations
- 2018Anhysteretic Magnetization Measurement Methods for Soft Magnetic Materialscitations
- 2017Synthesis of Optimal Robust Regulator for Food Processing Facilitiescitations
- 2017Utilization of Eddy Current Tomography in Automotive Industrycitations
- 2016Heuristic Analysis Model of Nitrided Layers’ Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligencecitations
- 2016Heat accumulating blocks based on the pyrophyllite and thermally expanded graphitecitations
- 2016Assessment of graphene coatings influence on tribological properties of surfaces
- 2016Application of graphene and newly developed amorphous alloys in current transformers for railway applications
- 2015The Influence of Thermomagnetic Treatment on the Magnetoelastic Characteristics of Fe61Co19Si5B15 Amorphous Alloyscitations
- 2015Preparation, Processing and Selected Properties of Modern Melt-Quenched Alloyscitations
- 2015Magnetic Thermogravimetric Analysis of CuCo and CuFe Amorphous Alloyscitations
- 2014Digitally Controlled Current Transformer with Hall Sensorcitations
- 2014Influence of Tensile Force on Magnetic Properties of Amorphous Fe80B11Si9 Alloys in Different States of Thermal Relaxationcitations
Places of action
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article
Heuristic Analysis Model of Nitrided Layers’ Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligence
Abstract
The article presents a selected area of research and development concerning the methods of material analysis based on the automatic image recognition of the investigated metallographic sections. The objectives of the analyses of the materials for gas nitriding technology are described. The methods of the preparation of nitrided layers, the steps of the process and the construction and operation of devices for gas nitriding are given. We discuss the possibility of using the methods of digital images processing in the analysis of the materials, as well as their essential task groups: improving the quality of the images, segmentation, morphological transformations and image recognition. The developed analysis model of the nitrided layers formation, covering image processing and analysis techniques, as well as selected methods of artificial intelligence are presented. The model is divided into stages, which are formalized in order to better reproduce their actions. The validation of the presented method is performed. The advantages and limitations of the developed solution, as well as the possibilities of its practical use, are listed.