Abstract: Currently, the Malaysian construction industry is
focusing on transforming construction processes from conventional
building methods to the Industrialized Building System (IBS). Still,
research on the decision making of IBS technology adoption with the
influence of contextual factors is scarce. The purpose of this paper is
to explore how contextual factors influence the IBS decision making
in building projects which is perceived by those involved in
construction industry namely construction stakeholders and IBS
supply chain members. Theoretical background, theoretical
frameworks and literatures which identify possible contextual factors
that influence decision making towards IBS technology adoption are
presented. This paper also discusses the importance of contextual
factors in IBS decision making, highlighting some possible crossover
benefits and making some suggestions as to how these can be
utilized. Conclusions are drawn and recommendations are made with
respect to the perception of socio-economic, IBS policy and IBS
technology associated with building projects.
Abstract: Computer languages are usually lumped together
into broad -paradigms-, leaving us in want of a finer classification
of kinds of language. Theories distinguishing between -genuine
differences- in language has been called for, and we propose that
such differences can be observed through a notion of expressive mode.
We outline this concept, propose how it could be operationalized and
indicate a possible context for the development of a corresponding
theory. Finally we consider a possible application in connection
with evaluation of language revision. We illustrate this with a case,
investigating possible revisions of the relational algebra in order to
overcome weaknesses of the division operator in connection with
universal queries.
Abstract: In this paper we have proposed a methodology to
develop an amperometric biosensor for the analysis of glucose
concentration using a simple microcontroller based data acquisition
system. The work involves the development of Detachable
Membrane Unit (enzyme based biomembrane) with immobilized
glucose oxidase on the membrane and interfacing the same to the
signal conditioning system. The current generated by the biosensor
for different glucose concentrations was signal conditioned, then
acquired and computed by a simple AT89C51-microcontroller. The
optimum operating parameters for the better performance were found
and reported. The detailed performance evaluation of the biosensor
has been carried out. The proposed microcontroller based biosensor
system has the sensitivity of 0.04V/g/dl, with a resolution of
50mg/dl. It has exhibited very good inter day stability observed up to
30 days. Comparing to the reference method such as HPLC, the
accuracy of the proposed biosensor system is well within ± 1.5%.
The system can be used for real time analysis of glucose
concentration in the field such as, food and fermentation and clinical
(In-Vitro) applications.
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: In this paper we discuss the effect of unbounded particle interaction operator on particle growth and we study how this can address the choice of appropriate time steps of the numerical simulation. We provide also rigorous mathematical proofs showing that large particles become dominating with increasing time while small particles contribute negligibly. Second, we discuss the efficiency of the algorithm by performing numerical simulations tests and by comparing the simulated solutions with some known analytic solutions to the Smoluchowski equation.
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: A new digital watermarking technique for images that
are sensitive to blocking artifacts is presented. Experimental results
show that the proposed MDCT based approach produces highly
imperceptible watermarked images and is robust to attacks such as
compression, noise, filtering and geometric transformations. The
proposed MDCT watermarking technique is applied to fingerprints
for ensuring security. The face image and demographic text data of
an individual are used as multiple watermarks. An AFIS system was
used to quantitatively evaluate the matching performance of the
MDCT-based watermarked fingerprint. The high fingerprint
matching scores show that the MDCT approach is resilient to
blocking artifacts. The quality of the extracted face and extracted text
images was computed using two human visual system metrics and
the results show that the image quality was high.
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: As the enormous amount of on-line text grows on the
World-Wide Web, the development of methods for automatically
summarizing this text becomes more important. The primary goal of
this research is to create an efficient tool that is able to summarize
large documents automatically. We propose an Evolving
connectionist System that is adaptive, incremental learning and
knowledge representation system that evolves its structure and
functionality. In this paper, we propose a novel approach for Part of
Speech disambiguation using a recurrent neural network, a paradigm
capable of dealing with sequential data. We observed that
connectionist approach to text summarization has a natural way of
learning grammatical structures through experience. Experimental
results show that our approach achieves acceptable performance.
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 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: 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: The weight constrained shortest path problem
(WCSPP) is one of most several known basic problems in
combinatorial optimization. Because of its importance in many areas
of applications such as computer science, engineering and operations
research, many researchers have extensively studied the WCSPP.
This paper mainly concentrates on the reduction of total search space
for finding WCSP using some existing Genetic Algorithm (GA). For
this purpose, some controlled schemes of genetic operators are
adopted on list chromosome representation. This approach gives a
near optimum solution with smaller elapsed generation than classical
GA technique. From further analysis on the matter, a new
generalized schema theorem is also developed from the philosophy
of Holland-s theorem.
Abstract: In this paper, we propose a reversible watermarking
scheme based on histogram shifting (HS) to embed watermark bits
into the H.264/AVC standard videos by modifying the last nonzero
level in the context adaptive variable length coding (CAVLC) domain.
The proposed method collects all of the last nonzero coefficients (or
called last level coefficient) of 4×4 sub-macro blocks in a macro
block and utilizes predictions for the current last level from the
neighbor block-s last levels to embed watermark bits. The feature of
the proposed method is low computational and has the ability of
reversible recovery. The experimental results have demonstrated that
our proposed scheme has acceptable degradation on video quality and
output bit-rate for most test videos.
Abstract: Tofurther advance research on immune-related genes
from T. molitor, we constructed acDNA library and analyzed
expressed sequence taq (EST) sequences from 1,056 clones. After
removing vector sequence and quality checkingthrough thePhred
program (trim_alt 0.05 (P-score>20), 1039 sequences were generated.
The average length of insert was 792 bp. In addition, we identified 162
clusters, 167 contigs and 391 contigs after clustering and assembling
process using a TGICL package. EST sequences were searchedagainst
NCBI nr database by local BLAST (blastx, E
Abstract: The use of machine vision to inspect the outcome of
surgical tasks is investigated, with the aim of incorporating this
approach in robotic surgery systems. Machine vision is a non-contact
form of inspection i.e. no part of the vision system is in direct contact
with the patient, and is therefore well suited for surgery where
sterility is an important consideration,. As a proof-of-concept, three
primary surgical tasks for a common neurosurgical procedure were
inspected using machine vision. Experiments were performed on
cadaveric pig heads to simulate the two possible outcomes i.e.
satisfactory or unsatisfactory, for tasks involved in making a burr
hole, namely incision, retraction, and drilling. We identify low level
image features to distinguish the two outcomes, as well as report on
results that validate our proposed approach. The potential of using
machine vision in a surgical environment, and the challenges that
must be addressed, are identified and discussed.