Abstract: Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative research on Learning Analytics. Three aspects of this will be discussed: 1) Establishing an international research project and team members, 2) cross-cultural understandings, and 3) ways of working in relation to the practicalities of the project. This article is intended to benefit other researchers by highlighting the challenges as well as the strategies used in this project to ensure such collaborative research succeeds.
Abstract: This paper is meant to analyze the ranking of
University of Malaysia Terengganu, UMT’s website in the World
Wide Web. There are only few researches have been done on
comparing the ranking of universities’ websites so this research will
be able to determine whether the existing UMT’s website is serving
its purpose which is to introduce UMT to the world. The ranking is
based on hub and authority values which are accordance to the
structure of the website. These values are computed using two websearching
algorithms, HITS and SALSA. Three other universities’
websites are used as the benchmarks which are UM, Harvard and
Stanford. The result is clearly showing that more work has to be done
on the existing UMT’s website where important pages according to
the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s
website will act as a guideline for the web-developer to develop a
more efficient website.
Abstract: This study presents experimental and optimization of
nanoparticle mass concentration and heat input based on the total
thermal resistance (Rth) of loop heat pipe (LHP), employed for PCCPU
cooling. In this study, silica nanoparticles (SiO2) in water with
particle mass concentration ranged from 0% (pure water) to 1% is
considered as the working fluid within the LHP. The experimental
design and optimization is accomplished by the design of
experimental tool, Response Surface Methodology (RSM). The
results show that the nanoparticle mass concentration and the heat
input have significant effect on the Rth of LHP. For a given heat
input, the Rth is found to decrease with the increase of the
nanoparticle mass concentration up to 0.5% and increased thereafter.
It is also found that the Rth is decreased when the heat input is
increased from 20W to 60W. The results are optimized with the
objective of minimizing the Rth, using Design-Expert software, and
the optimized nanoparticle mass concentration and heat input are
0.48% and 59.97W, respectively, the minimum thermal resistance
being 2.66 (ºC/W).
Abstract: Clustering is a process of grouping objects and data
into groups of clusters to ensure that data objects from the same
cluster are identical to each other. Clustering algorithms in one of the
area in data mining and it can be classified into partition, hierarchical,
density based and grid based. Therefore, in this paper we do survey
and review four major hierarchical clustering algorithms called
CURE, ROCK, CHAMELEON and BIRCH. The obtained state of
the art of these algorithms will help in eliminating the current
problems as well as deriving more robust and scalable algorithms for
clustering.