Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Kumar, R. V. M. S. S. K." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Unsteady three-dimensional MHD nanofluid flow over a stretching sheet with variable wall thickness and slip effects
Autorzy:
Kumar, G. Vinod
Varma, S. V. K.
Kumar, R. V. M. S. S. K.
Powiązania:
https://bibliotekanauki.pl/articles/265665.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
pole magnetyczne
magnetohydrodynamika
poślizg
unsteady flow
magnetic field
Buongiorno’s model
variable wall thickness sheet
velocity
thermal and solutal slip
Opis:
The stretching sheets with variable thickness may occur in engineering applications more frequently than a flat sheet. Due to its various applications, in the present analysis we considered a three dimensional unsteady MHD nanofluid flow over a stretching sheet with a variable wall thickness in a porous medium. The effects of radiation, viscous dissipation and slip boundary conditions are considered. Buongiorno’s model is incorporated to study the combined effects of thermophoresis and Brownian motion. The dimensionless governing equations are solved by using MATLAB bvp4c package. The impact of various important flow parameters is presented and analysed through graphs and tables. It is interesting to note that all the three boundary layer thicknesses are diminished by slip parameters. Further, the unsteady parameter decreases the hydromagnetic boundary layer thickness.
Źródło:
International Journal of Applied Mechanics and Engineering; 2019, 24, 3; 709-724
1734-4492
2353-9003
Pojawia się w:
International Journal of Applied Mechanics and Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applicability of artificial intelligence in smart healthcare systems for automatic detection of Parkinson’s Disease
Autorzy:
Pallathadka, Harikumar
Padminivalli V., S.J.R.K.
Vasavi, M.
Nancy, P.
Naved, Mohd
Kumar, Harish
Ray, Samrat
Powiązania:
https://bibliotekanauki.pl/articles/38709253.pdf
Data publikacji:
2024
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
Parkinson’s disease
detection
machine learning
relief algorithm
LDA algorithm
SVM-RBF
accuracy
sensitivity
specificity
choroba Parkinsona
wykrywanie
nauczanie maszynowe
algorytm ulgi
Algorytm LDA
dokładność
wrażliwość
specyficzność
Opis:
Parkinson’s disease is associated with memory loss, anxiety, and depression in the brain. Problems such as poor balance and difficulty during walking can be observed in addition to symptoms of impaired posture and rigidity. The field dedicated to making computers capable of learning autonomously, without having to be explicitly programmed, is known as machine learning. An approach to the diagnosis of Parkinson’s disease, which is based on artificial intelligence, is discussed in this article. The input for this system is provided through photographic examples of Parkinson’s disease patient handwriting. Received photos are preprocessed using the relief feature option to begin the process. This is helpful in the process of selecting characteristics for the identification of Parkinson’s disease. After that, the linear discriminant analysis (LDA) algorithm is employed to reduce the dimensions, bringing down the total number of dimensions that are present in the input data. The photos are then classified via radial basis function-support vector machine (SVM-RBF), k-nearest neighbors (KNN), and naive Bayes algorithms, respectively.
Źródło:
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 175-185
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies