Autor: Hoser, K. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: From Heavy Fermion and Spin-Glass Behavior to Magnetic Order in $CeT_4M$ Compounds
Autorzy:: Toliński, T.
Kowalczyk, A.
Falkowski, M.
Synoradzki, K.
Chełkowska, G.
Hoser, A.
Rols, S.
Powiązania:: https://bibliotekanauki.pl/articles/1426703.pdf
Data publikacji:: 2012-05
Wydawca:: Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:: 71.20.Lp
71.27.+a
75.30.Mb
75.30.Cr
75.50.Lk
78.70.Nx
Opis:: We report on the transitions between the ferromagnetic order, spin-glass behavior, heavy fermion and fluctuating valence state in a series of isostructural compounds $CeT_4M$ (T = Ni, Cu; M = Al, Ga, Mn). The dilution of Ce or the T and M elements allowed us to follow the physical properties evolution employing the measurements of the heat capacity, dc magnetic susceptibility, frequency dependent ac magnetic susceptibility, magnetization relaxation, inelastic neutron scattering and also the X-ray photoemission spectroscopy. It is shown that the Mn rich compounds lean towards the spin glass behavior. For the compounds governed by the close to localization Ce 4f states the effect of the crystal electric field has been studied. It has been shown that the spin glass-like behavior can significantly influence the physics of the $CeT_4M$ compounds.
Źródło:: Acta Physica Polonica A; 2012, 121, 5-6; 1014-1018
0587-4246
1898-794X
Pojawia się w:: Acta Physica Polonica A
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Developing automatic recognition system of drill wear in standard laminated chipboard drilling process
Autorzy:: Kurek, J.
Kruk, M.
Osowski, S.
Hoser, P.
Wieczorek, G.
Jegorowa, A.
Górski, J.
Wilkowski, J.
Śmietańska, K.
Kossakowska, J.
Powiązania:: https://bibliotekanauki.pl/articles/200766.pdf
Data publikacji:: 2016
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: diagnostic expert systems
neural networks
wavelet packets
wear monitoring
diagnostyczny system ekspercki
sieci neuronowe
pakiety falkowe
monitorowanie zużycia
Opis:: The paper presents an automatic approach to recognition of the drill condition in a standard laminated chipboard drilling process. The state of the drill is classified into two classes: “useful” (sharp enough) and “useless” (worn out). The case “useless” indicates symptoms of excessive drill wear, unsatisfactory from the point of view of furniture processing quality. On the other hand the “useful” state identifies tools which are still able to drill holes acceptable due to the required processing quality. The main problem in this task is to choose an appropriate set of diagnostic features (variables), based on which the recognition of drill state (“useful” versus “useless”) can be made. The features have been generated based on 5 registered signals: feed force, cutting torque, noise, vibration and acoustic emission. Different statistical parameters describing these signals and also their Fourier and wavelet representations have been used for defining the features. Sequential feature selection is applied to detect the most class discriminative set of features. The final step of recognition is done by using three types of classifiers, including support vector machine, ensemble of decision trees and random forest. Six standard drills of 12 mm diameter with tungsten carbide tips were used in experiments. The results have confirmed good quality of the proposed diagnostic system.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 3; 633-640
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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