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Institution

National University of Malaysia

EducationKuala Lumpur, Malaysia
About: National University of Malaysia is a education organization based out in Kuala Lumpur, Malaysia. It is known for research contribution in the topics: Population & Heat transfer. The organization has 26593 authors who have published 41270 publications receiving 552683 citations. The organization is also known as: NUM & Universiti Kebangsaan Malaysia.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the effect of high temperature on cement-based materials containing fly ash and nanosilica has not been well characterized, and the porosity was determined using the BET (Brunauer, Emmett, and Teller) technique to study the specimens' behavior after exposure to high temperatures.

162 citations

Journal ArticleDOI
TL;DR: In this paper, Nitrogen-doped carbon and its composites possess great potential for fuel cell catalyst applications especially at the oxygen reduction cathode, and the progress in the area of this new class of catalysts and their composites for greater enhancement of oxygen reduction activity and stability in various fuel cell applications is reviewed.

161 citations

Journal ArticleDOI
TL;DR: CHIO is a very powerful optimization algorithm that can be used to tackle many optimization problems across a wide variety of optimization domains.
Abstract: In this paper, a new nature-inspired human-based optimization algorithm is proposed which is called coronavirus herd immunity optimizer (CHIO). The inspiration of CHIO is originated from the herd immunity concept as a way to tackle coronavirus pandemic (COVID-19). The speed of spreading coronavirus infection depends on how the infected individuals directly contact with other society members. In order to protect other members of society from the disease, social distancing is suggested by health experts. Herd immunity is a state the population reaches when most of the population is immune which results in the prevention of disease transmission. These concepts are modeled in terms of optimization concepts. CHIO mimics the herd immunity strategy as well as the social distancing concepts. Three types of individual cases are utilized for herd immunity: susceptible, infected, and immuned. This is to determine how the newly generated solution updates its genes with social distancing strategies. CHIO is evaluated using 23 well-known benchmark functions. Initially, the sensitivity of CHIO to its parameters is studied. Thereafter, the comparative evaluation against seven state-of-the-art methods is conducted. The comparative analysis verifies that CHIO is able to yield very competitive results compared to those obtained by other well-established methods. For more validations, three real-world engineering optimization problems extracted from IEEE-CEC 2011 are used. Again, CHIO is proved to be efficient. In conclusion, CHIO is a very powerful optimization algorithm that can be used to tackle many optimization problems across a wide variety of optimization domains.

161 citations

Journal ArticleDOI
TL;DR: In this article, the causal relationship between economic growth and CO2 emissions in a panel of 24 European countries from 1980 to 2010 was examined using an analytical framework that considers pooled mean group estimations in a dynamic heterogeneous panel setting.
Abstract: We examine the causal relationship between economic growth and CO2 emissions in a panel of 24 European countries from 1980 to 2010. Using an analytical framework that considers pooled mean group estimations in a dynamic heterogeneous panel setting, we show that there is an inverted U-shaped relationship between CO2 emissions and economic growth in the long run and that there is no such relationship in the short run. In particular, we find that biomass energy is insignificantly linked to CO2 emission. However, technological innovation significantly facilitates reduction of CO2 emissions in the investigated countries. Altogether, our study implies that economic growth and environmental quality can be achieved simultaneously, which opens up new insights for policy-makers for sustainable economic development via implementation of renewable energy consumption through technological innovation.

161 citations

Journal ArticleDOI
TL;DR: Although this technology is still at an embryonic stage, further studies with standard theoretical and comprehensive format are suggested to develop photocatalysts with high production rates and selectivity.
Abstract: In recent years, the increasing level of CO2 in the atmosphere has not only contributed to global warming but has also triggered considerable interest in photocatalytic reduction of CO2. The reduction of CO2 with H2O using sunlight is an innovative way to solve the current growing environmental challenges. This paper reviews the basic principles of photocatalysis and photocatalytic CO2 reduction, discusses the measures of the photocatalytic efficiency and summarizes current advances in the exploration of this technology using different types of semiconductor photocatalysts, such as TiO2 and modified TiO2, layered-perovskite Ag/ALa4Ti4O15 (A = Ca, Ba, Sr), ferroelectric LiNbO3, and plasmonic photocatalysts. Visible light harvesting, novel plasmonic photocatalysts offer potential solutions for some of the main drawbacks in this reduction process. Effective plasmonic photocatalysts that have shown reduction activities towards CO2 with H2O are highlighted here. Although this technology is still at an embryonic stage, further studies with standard theoretical and comprehensive format are suggested to develop photocatalysts with high production rates and selectivity. Based on the collected results, the immense prospects and opportunities that exist in this technique are also reviewed here.

161 citations


Authors

Showing all 26827 results

NameH-indexPapersCitations
Jonathan E. Shaw114629108114
Sabu Thomas102155451366
Biswajeet Pradhan9873532900
Haji Hassan Masjuki9750229653
Mika Sillanpää96101944260
Choon Nam Ong8644425157
Keith R. Abrams8635530980
Kamaruzzaman Sopian8498925293
Benedikt M. Kessler8238524243
Michel Marre8244439052
Peter Willett7647929037
Peter F. M. Choong7253218185
Nidal Hilal7239521524
Margareta Nordin7226719578
Teuku Meurah Indra Mahlia7033917444
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202382
2022363
20213,169
20202,808
20192,888
20183,299