Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.
Abstract: The purpose of this paper is to analyze the case of the
U.S. Pivot and to suggest an appropriate model including entry
strategies and success factors for QPS of Cable TV. The
telecommunication companies have been operating QPS including
IPTV service, which enables them to cross over broadcasting areas.
Due to this circumstance, the Cable TV operators are now concerned
and are planning to add QPS with the mobile service. Based on the
Porter's five forces model, an analytical framework has been proposed
to MVNO in Cable TV industry in the United States. As a result of this
study, MVNO in Cable TV industry has to have a clear killer
application with their sufficient contents. Subsequently, the direction
of the future Cable TV industry is proposed.
Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: Renewable natural fibres such as oil palm, flax, and
pineapple leaf can be utilized to obtain new high performance
polymer materials. The reuse of waste natural fibres as reinforcement
for polymer is a sustainable option to the environment. However, due
to its high hydroxyl content of cellulose, natural fibres are
susceptible to absorb water that affects the composite mechanical
properties adversely. Research found that Nano materials such as
Nano Silica Carbide (n-SiC) and Nano Clay can be added into the
polymer composite to overcome this problem by enhancing its
mechanical properties in wet condition. The addition of Nano
material improves the tensile and wear properties, flexural stressstrain
behaviour, fracture toughness, and fracture strength of polymer
natural composites in wet and dry conditions.
Abstract: The crystalline quality of the AlGaN/GaN high electron mobility transistor (HEMT) structure grown on a 200 mm silicon substrate has been investigated using UV-visible micro- Raman scattering and photoluminescence (PL). The visible Raman scattering probes the whole nitride stack with the Si substrate and shows the presence of a small component of residual in-plane stress in the thick GaN buffer resulting from a wafer bowing, while the UV micro-Raman indicates a tensile interfacial stress induced at the top GaN/AlGaN/AlN layers. PL shows a good crystal quality GaN channel where the yellow band intensity is very low compared to that of the near-band-edge transition. The uniformity of this sample is shown by measurements from several points across the epiwafer.