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Wyszukujesz frazę "Muhammad, Noor" wg kryterium: Autor


Wyświetlanie 1-4 z 4
Tytuł:
Erosion Wear Characteristics of Novel AMMC Produced Using Powder Metallurgy
Autorzy:
Behera, Rajesh Kumar
Samal, Birajendu Prasad
Panigrahi, Sarat Chandra
Parida, Pramod Kumar
Muduli, Kamalakanta
Muhammad, Noor
Das, Nitaisundar
Abd Rahim, Shayfull Zamree
Powiązania:
https://bibliotekanauki.pl/articles/2125551.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
AMMC
powder metallurgy
microstructure
wear behavior
particle erosion
Taguchi technique
Opis:
Currently, the world of material requires intensive research to discover a new-class of materials those posses the properties like lower in weight, greater in strength and better in mechanical properties. This led to the study of light and strong alloys or composites. This study focuses to produce current novel aluminium composite with an appreciable density, good machinable characteristics, less corrosive, high strength, light weight and low manufacturing cost product. In this research, an aluminium metal matrix composites (AMMC) (Al-0.5Si-0.5Mg-2.5Cu-15SiC) was developed using the metallurgical powdered method and subjected to the investigation of erosion wear characteristics. Here the solid particle erosion test was conducted on AMMC samples. The article presents, the design of Taguchi experiments and statistical techniques of erosion wear characteristics and the behaviors of the composite. The rate of erosion wear found to decrease with increasing impact angle, regardless of the rate of impact. With higher impact velocity erosion rate increases but decreases with stand of distance.
Źródło:
Archives of Metallurgy and Materials; 2022, 67, 3; 1027--1032
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Variance estimation in stratified adaptive cluster sampling
Autorzy:
Yasmeen, Uzma
Noor-ul-Amin, Muhammad
Hanif, Muhammad
Powiązania:
https://bibliotekanauki.pl/articles/2034098.pdf
Data publikacji:
2022
Wydawca:
Główny Urząd Statystyczny
Tematy:
variance estimator
stratified sampling
stratified adaptive cluster sampling (SACS)
Opis:
In many sampling surveys, the use of auxiliary information at either the design or estimation stage, or at both these stages is usual practice. Auxiliary information is commonly used to obtain improved designs and to achieve a high level of precision in the estimation of population density. Adaptive cluster sampling (ACS) was proposed to observe rare units with the purpose of obtaining highly precise estimations of rare and specially clustered populations in terms of least variances of the estimators. This sampling design proved to be more precise than its more conventional counterparts, including simple random sampling (SRS), stratified sampling, etc. In this paper, a generalised estimator is anticipated for a finite population variance with the use of information of an auxiliary variable under stratified adaptive cluster sampling (SACS). The bias and mean square error expressions of the recommended estimators are derived up to the first degree of approximation. A simulation study showed that the proposed estimators have the least estimated mean square error under the SACS technique in comparison to variance estimators in stratified sampling.
Źródło:
Statistics in Transition new series; 2022, 23, 1; 173-184
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Synthesis and activity evaluation of Ce-Mn-Cu mixed oxide catalyst for selective oxidation of co in automobile engine exhaust: effect of Ce/Mn loading content on catalytic activity
Autorzy:
Bilal, Yasir
Nasir, Muhammad Ali
Nasreen, Sadia
Akhter, Niaz Ahmed
Pasha, Riffat Asim
Noor, Muhammad Farhan
Powiązania:
https://bibliotekanauki.pl/articles/101992.pdf
Data publikacji:
2018
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
base metal oxide catalyst
catalytic converter
CO sensor
CO-precipitation
catalytic activity
katalizator tlenku metalu zasadowego
katalizator
czujnik CO
strącanie CO
aktywność katalityczna
Opis:
A series of Mn-doped CeO2-CuO catalyst (CeO2-MnOx-CuO) (Ce/Mn molar ratio of 0.5, 1.0 2.0 and 3.0) were prepared using co-precipitation method for the selective oxidation of CO in automobile engine exhaust. The content of copper was 5.0 wt. % in each sample. Catalysts were installed on the automobile engine exhaust and CO amount was recorded with help of CO sensor, with and without the catalyst. The catalytic converter efficiency was estimated for each catalyst through efficiency formula. It was observed that Ce/Mn catalyst with a molar ratio of 2.0 shows the maximum efficiency (88.35%). Stability of conversion process was analyzed by plotting the CO amount with respect to time. The catalyst with Ce/Mn molar ratio of 2.0 performed the most streamline conversion process with least deviations.
Źródło:
Advances in Science and Technology. Research Journal; 2018, 12, 1; 260-266
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new family of robust regression estimators utilizing robust regression tools and supplementary attributes
Autorzy:
Sajjad, Irsa
Hanif, Muhammad
Koyuncu, Nursel
Shahzad, Usman
Al-Noor, Nadia H.
Powiązania:
https://bibliotekanauki.pl/articles/1363609.pdf
Data publikacji:
2021-03-03
Wydawca:
Główny Urząd Statystyczny
Tematy:
percentage relative efficiency
Opis:
Zaman and Bulut (2018a) developed a class of estimators for a population mean utilising LMS robust regression and supplementary attributes. In this paper, a family of estimators is proposed, based on the adaptation of the estimators presented by Zaman (2019), followed by the introduction of a new family of regression-type estimators utilising robust regression tools (LAD, H-M, LMS, H-MM, Hampel-M, Tukey-M, LTS) and supplementary attributes. The mean square error expressions of the adapted and proposed families are determined through a general formula. The study demonstrates that the adapted class of the Zaman (2019) estimators is in every case more proficient than that of Zaman and Bulut (2018a). In addition, the proposed robust regression estimators based on robust regression tools and supplementary attributes are more efficient than those of Zaman and Bulut (2018a) and Zaman (2019).The theoretical findings are supported by real-life examples.
Źródło:
Statistics in Transition new series; 2021, 22, 1; 207-216
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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