Abstract: Water hyacinth has been used in aquatic systems for
wastewater purification in many years worldwide. The role of water
hyacinth (Eichhornia crassipes) species in polishing nitrate and
phosphorus concentration from municipal wastewater treatment plant
effluent by phytoremediation method was evaluated. The objective
of this project is to determine the removal efficiency of water
hyacinth in polishing nitrate and phosphorus, as well as chemical
oxygen demand (COD) and ammonia. Water hyacinth is considered
as the most efficient aquatic plant used in removing vast range of
pollutants such as organic matters, nutrients and heavy metals. Water
hyacinth, also referred as macrophytes, were cultivated in the
treatment house in a reactor tank of approximately 90(L) x 40(W) x
25(H) in dimension and built with three compartments. Three water
hyacinths were placed in each compartments and water sample in
each compartment were collected in every two days. The plant
observation was conducted by weight measurement, plant uptake and
new young shoot development. Water hyacinth effectively removed
approximately 49% of COD, 81% of ammonia, 67% of phosphorus
and 92% of nitrate. It also showed significant growth rate at starting
from day 6 with 0.33 shoot/day and they kept developing up to 0.38
shoot/day at the end of day 24. From the studies conducted, it was
proved that water hyacinth is capable of polishing the effluent of
municipal wastewater which contains undesirable amount of nitrate
and phosphorus concentration.
Abstract: Based on the homotopy perturbation method (HPM)
and Padé approximants (PA), approximate and exact solutions are
obtained for cubic Boussinesq and modified Boussinesq equations.
The obtained solutions contain solitary waves, rational solutions.
HPM is used for analytic treatment to those equations and PA for
increasing the convergence region of the HPM analytical solution.
The results reveal that the HPM with the enhancement of PA is a
very effective, convenient and quite accurate to such types of partial
differential equations.
Abstract: Collaborative working environments for distance
education can be considered as a more generic form of contemporary
remote labs. At present, the majority of existing real laboratories are
not constructed to allow the involved participants to collaborate in
real time. To make this revolutionary learning environment possible
we must allow the different users to carry out an experiment
simultaneously. In recent times, multi-user environments are
successfully applied in many applications such as air traffic control
systems, team-oriented military systems, chat-text tools, multi-player
games etc. Thus, understanding the ideas and techniques behind these
systems could be of great importance in the contribution of ideas to
our e-learning environment for collaborative working. In this
investigation, collaborative working environments from theoretical
and practical perspectives are considered in order to build an
effective collaborative real laboratory, which allows two students or
more to conduct remote experiments at the same time as a team. In
order to achieve this goal, we have implemented distributed system
architecture, enabling students to obtain an automated help by either
a human tutor or a rule-based e-tutor.
Abstract: In this paper we present a hybrid search algorithm for
solving constraint satisfaction and optimization problems. This
algorithm combines ideas of two basic approaches: complete and
incomplete algorithms which also known as systematic search and
local search algorithms. Different characteristics of systematic search
and local search methods are complementary. Therefore we have
tried to get the advantages of both approaches in the presented
algorithm. The major advantage of presented algorithm is finding
partial sound solution for complicated problems which their complete
solution could not be found in a reasonable time. This algorithm
results are compared with other algorithms using the well known
n-queens problem.
Abstract: Partial discharge (PD) detection is an important
method to evaluate the insulation condition of metal-clad apparatus.
Non-intrusive sensors which are easy to install and have no
interruptions on operation are preferred in onsite PD detection.
However, it often lacks of accuracy due to the interferences in PD
signals. In this paper a novel PD extraction method that uses frequency
analysis and entropy based time-frequency (TF) analysis is introduced.
The repetitive pulses from convertor are first removed via frequency
analysis. Then, the relative entropy and relative peak-frequency of
each pulse (i.e. time-indexed vector TF spectrum) are calculated and
all pulses with similar parameters are grouped. According to the
characteristics of non-intrusive sensor and the frequency distribution
of PDs, the pulses of PD and interferences are separated. Finally the
PD signal and interferences are recovered via inverse TF transform.
The de-noised result of noisy PD data demonstrates that the
combination of frequency and time-frequency techniques can
discriminate PDs from interferences with various frequency
distributions.
Abstract: The emergence of blended learning has been
influenced by the rapid changes in Higher Education within the last
few years. However, there is a lack of studies that look into the future
of blended learning in the Saudi context. The most likely explanation
is that blended learning is relatively new and, with respect to learning
in general, under-researched. This study addresses this gap and
explores the views of lecturers and students towards the future of
blended learning in Saudi Arabia. This study was informed by the
interpretive paradigm that appears to be most appropriate to
understand and interpret the perceptions of students and instructors
towards a new learning environment. While globally there has been
considerable research on the perceptions of e-learning and blended
learning with its different models, there is plenty of space for further
research specifically in the Arab region, and in Saudi Arabia where
blended learning is now being introduced.
Abstract: When cars are released from the factory, strut noises are very small and therefore it is difficult to perceive them. As the use time and travel distance increase, however, strut noises get larger so as to cause users much uneasiness. The noises generated at the field include engine noises and flow noises and therefore it is difficult to clearly discern the noises generated from struts. This study developed a test method which can reproduce field strut noises in the lab. Using the newly developed noise evaluation test, this study analyzed the effects that insulator performance degradation and failure can have on car noises. The study also confirmed that the insulator durability test by the simple back-and-forth motion cannot completely reflect the state of the parts failure in the field. Based on this, the study also confirmed that field noises can be reproduced through a durability test that considers heat aging.
Abstract: As the Internet continues to grow at a rapid pace as
the primary medium for communications and commerce and as
telecommunication networks and systems continue to expand their
global reach, digital information has become the most popular and
important information resource and our dependence upon the
underlying cyber infrastructure has been increasing significantly.
Unfortunately, as our dependency has grown, so has the threat to the
cyber infrastructure from spammers, attackers and criminal
enterprises. In this paper, we propose a new machine learning based
network intrusion detection framework for cyber security. The
detection process of the framework consists of two stages: model
construction and intrusion detection. In the model construction stage,
a semi-supervised machine learning algorithm is applied to a
collected set of network audit data to generate a profile of normal
network behavior and in the intrusion detection stage, input network
events are analyzed and compared with the patterns gathered in the
profile, and some of them are then flagged as anomalies should these
events are sufficiently far from the expected normal behavior. The
proposed framework is particularly applicable to the situations where
there is only a small amount of labeled network training data
available, which is very typical in real world network environments.
Abstract: Quality of Service (QoS) Routing aims to find path between source and destination satisfying the QoS requirements which efficiently using the network resources and underlying routing algorithm and to fmd low-cost paths that satisfy given QoS constraints. One of the key issues in providing end-to-end QoS guarantees in packet networks is determining feasible path that satisfies a number of QoS constraints. We present a Optimized Multi- Constrained Routing (OMCR) algorithm for the computation of constrained paths for QoS routing in computer networks. OMCR applies distance vector to construct a shortest path for each destination with reference to a given optimization metric, from which a set of feasible paths are derived at each node. OMCR is able to fmd feasible paths as well as optimize the utilization of network resources. OMCR operates with the hop-by-hop, connectionless routing model in IP Internet and does not create any loops while fmding the feasible paths. Nodes running OMCR not necessarily maintaining global view of network state such as topology, resource information and routing updates are sent only to neighboring nodes whereas its counterpart link-state routing method depend on complete network state for constrained path computation and that incurs excessive communication overhead.
Abstract: In digital signal processing it is important to
approximate multi-dimensional data by the method called rank
reduction, in which we reduce the rank of multi-dimensional data from
higher to lower. For 2-dimennsional data, singular value
decomposition (SVD) is one of the most known rank reduction
techniques. Additional, outer product expansion expanded from SVD
was proposed and implemented for multi-dimensional data, which has
been widely applied to image processing and pattern recognition.
However, the multi-dimensional outer product expansion has behavior
of great computation complex and has not orthogonally between the
expansion terms. Therefore we have proposed an alterative method,
Third-order Orthogonal Tensor Product Expansion short for 3-OTPE.
3-OTPE uses the power method instead of nonlinear optimization
method for decreasing at computing time. At the same time the group
of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is
also developed with SVD extensions for multi-dimensional data.
3-OTPE and HOSVD are similarly on the rank reduction of
multi-dimensional data. Using these two methods we can obtain
computation results respectively, some ones are the same while some
ones are slight different. In this paper, we compare 3-OTPE to
HOSVD in accuracy of calculation and computing time of resolution,
and clarify the difference between these two methods.
Abstract: Ontology is widely being used as a tool for organizing
information, creating the relation between the subjects within the
defined knowledge domain area. Various fields such as Civil,
Biology, and Management have successful integrated ontology in
decision support systems for managing domain knowledge and to
assist their decision makers. Gross pollutant traps (GPT) are devices
used in trapping and preventing large items or hazardous particles in
polluting and entering our waterways. However choosing and
determining GPT is a challenge in Malaysia as there are inadequate
GPT data repositories being captured and shared. Hence ontology is
needed to capture, organize and represent this knowledge into
meaningful information which can be contributed to the efficiency of
GPT selection in Malaysia urbanization. A GPT Ontology framework
is therefore built as the first step to capture GPT knowledge which
will then be integrated into the decision support system. This paper
will provide several examples of the GPT ontology, and explain how
it is constructed by using the Protégé tool.
Abstract: The development of shape and size of a crack in a
pressure vessel under uniaxial and biaxial loadings is important in
fitness-for-service evaluations such as leak-before-break. In this
work finite element modelling was used to evaluate the mean stress
and the J-integral around a front of a surface-breaking crack. A
procedure on the basis of ductile tearing resistance curves of high and
low constrained fracture mechanics geometries was developed to
estimate the amount of ductile crack extension for surface-breaking
cracks and to show the evolution of the initial crack shape. The
results showed non-uniform constraint levels and crack driving forces
around the crack front at large deformation levels. It was also shown
that initially semi-elliptical surface cracks under biaxial load
developed higher constraint levels around the crack front than in
uniaxial tension. However similar crack shapes were observed with
more extensions associated with cracks under biaxial loading.
Abstract: We demonstrate single-photon interference over 10 km using a plug and play system for quantum key distribution. The quality of the interferometer is measured by using the interferometer
visibility. The coding of the signal is based on the phase coding and the value of visibility is based on the interference effect, which result a number of count. The setup gives full control of polarization inside
the interferometer. The quality measurement of the interferometer is based on number of count per second and the system produces 94 % visibility in one of the detectors.
Abstract: The third phase of web means semantic web requires many web pages which are annotated with metadata. Thus, a crucial question is where to acquire these metadata. In this paper we propose our approach, a semi-automatic method to annotate the texts of documents and web pages and employs with a quite comprehensive knowledge base to categorize instances with regard to ontology. The approach is evaluated against the manual annotations and one of the most popular annotation tools which works the same as our tool. The approach is implemented in .net framework and uses the WordNet for knowledge base, an annotation tool for the Semantic Web.
Abstract: Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.
Abstract: The creation of a sustainable future depends on the knowledge and involvement of the people, as well as an understanding of the consequences of individual actions. Construction industry has long been associated with the detrimental effects to our mother earth. In Malaysia, the government, professional bodies and private companies are beginning to take heed in the necessity to reduce this environmental problem without restraining the need for development. This paper focuses on the actions undertaken by the Malaysian government, non-government organizations and construction players in promoting sustainability in construction. To ensure that those concerted efforts are not only skin deep in its impact, a survey was conducted to investigate the awareness of the developers regarding this issue and whether those developers has absorb the concept of sustainable construction in their current practices. The survey revealed that although the developers are aware of the rising issues on sustainability, little efforts are generated from them in implementing it. More effort is necessary to boost this application and further stimulate actions and strategies towards a sustainable built environment.
Abstract: The complexity of today-s software systems makes
collaborative development necessary to accomplish tasks.
Frameworks are necessary to allow developers perform their tasks
independently yet collaboratively. Similarity detection is one of the
major issues to consider when developing such frameworks. It allows
developers to mine existing repositories when developing their own
views of a software artifact, and it is necessary for identifying the
correspondences between the views to allow merging them and
checking their consistency. Due to the importance of the
requirements specification stage in software development, this paper
proposes a framework for collaborative development of Object-
Oriented formal specifications along with a similarity detection
approach to support the creation, merging and consistency checking
of specifications. The paper also explores the impact of using
additional concepts on improving the matching results. Finally, the
proposed approach is empirically evaluated.
Abstract: Personal computers draw non-sinusoidal current
with odd harmonics more significantly. Power Quality of
distribution networks is severely affected due to the flow of these
generated harmonics during the operation of electronic loads. In
this paper, mathematical modeling of odd harmonics in current like
3rd, 5th, 7th and 9th influencing the power quality has been presented.
Live signals have been captured with the help of power quality
analyzer for analysis purpose. The interesting feature is that Total
Harmonic Distortion (THD) in current decreases with the increase
of nonlinear loads has been verified theoretically. The results
obtained using mathematical expressions have been compared with
the practical results and exciting results have been found.
Abstract: We present a simplified equalization technique for a
π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated
signal in a multipath fading environment. The proposed equalizer is
realized as a fractionally spaced adaptive decision feedback equalizer
(FS-ADFE), employing exponential step-size least mean square
(LMS) algorithm as the adaptation technique. The main advantage of
the scheme stems from the usage of exponential step-size LMS algorithm
in the equalizer, which achieves similar convergence behavior
as that of a recursive least squares (RLS) algorithm with significantly
reduced computational complexity. To investigate the finite-precision
performance of the proposed equalizer along with the π/4 -DQPSK
modem, the entire system is evaluated on a 16-bit fixed point digital
signal processor (DSP) environment. The proposed scheme is found
to be attractive even for those cases where equalization is to be
performed within a restricted number of training samples.
Abstract: With the enormous growth on the web, users get easily
lost in the rich hyper structure. Thus developing user friendly and
automated tools for providing relevant information without any
redundant links to the users to cater to their needs is the primary task
for the website owners. Most of the existing web mining algorithms
have concentrated on finding frequent patterns while neglecting the
less frequent one that are likely to contain the outlying data such as
noise, irrelevant and redundant data. This paper proposes new
algorithm for mining the web content by detecting the redundant
links from the web documents using set theoretical(classical
mathematics) such as subset, union, intersection etc,. Then the
redundant links is removed from the original web content to get the
required information by the user..