Abstract: In this paper performance of Puma 560
manipulator is being compared for hybrid gradient descent
and least square method learning based ANFIS controller with
hybrid Genetic Algorithm and Generalized Pattern Search
tuned radial basis function based Neuro-Fuzzy controller.
ANFIS which is based on Takagi Sugeno type Fuzzy
controller needs prior knowledge of rule base while in radial
basis function based Neuro-Fuzzy rule base knowledge is not
required. Hybrid Genetic Algorithm with generalized Pattern
Search is used for tuning weights of radial basis function
based Neuro- fuzzy controller. All the controllers are checked
for butterfly trajectory tracking and results in the form of
Cartesian and joint space errors are being compared. ANFIS
based controller is showing better performance compared to
Radial Basis Function based Neuro-Fuzzy Controller but rule
base independency of RBF based Neuro-Fuzzy gives it an
edge over ANFIS
Abstract: This research aimed at investigating the Cr (III), Cd
(II) and Pb (II) removal efficiencies by using the newly synthesized
metal oxides/ polyethersulfone (PES), Al2O3/PES and ZrO2/PES,
membranes from synthetic wastewater and exploring fouling
mechanisms. A Comparative study between the removal efficiencies
of Cr (III), Cd (II) and Pb (II) from synthetic and natural wastewater
by using adsorption onto agricultural by products and the newly
synthesized Al2O3/PES and ZrO2/PES membranes was conducted to
assess the advantages and limitations of using the metal oxides/PES
membranes for heavy metals removal. The results showed that about
99 % and 88 % removal efficiencies were achieved by the tested
membranes for Pb (II) and Cr (III), respectively.
Abstract: Service trade is an important force of influencing economic development. A review on the related literatures is done firstly. Then through the construction of a Diamond Model, the main factors which influence the competitiveness of Chinese service trade are determined. With three competitiveness indexes served as the reference series respectively, the influencing factors served as the comparable series, three grey incidence models are then built up to conduct an empirical analysis on the main factors influencing the competitiveness of service trade after China entering WTO. The result indicates that urbanization level, open degree of service industry and foreign direct investment have larger impacts on Chinese service trade competitiveness, followed in turn by GDP in service industry and human capital, while commodity trade has the minimum impact. Further discussion provides train of thought for the upgrade of Chinese service trade competitiveness.
Abstract: The development of biomimetic micro-aerial-vehicles
(MAVs) with flapping wings is the future trend in military/domestic
field. The successful flight of MAVs is strongly related to the
understanding of unsteady aerodynamic performance of low Reynolds
number airfoils under dynamic flapping motion. This study explored
the effects of flapping frequency, stroke amplitude, and the inclined
angle of stroke plane on lift force and thrust force of a bio-inspiration
corrugated airfoil with 33 full factorial design of experiment and
ANOVA analysis. Unsteady vorticity flows over a corrugated thin
airfoil executing flapping motion are computed with time-dependent
two-dimensional laminar incompressible Reynolds-averaged
Navier-Stokes equations with the conformal hybrid mesh. The tested
freestream Reynolds number based on the chord length of airfoil as
characteristic length is fixed of 103. The dynamic mesh technique is
applied to model the flapping motion of a corrugated airfoil. Instant
vorticity contours over a complete flapping cycle clearly reveals the
flow mechanisms for lift force generation are dynamic stall, rotational
circulation, and wake capture. The thrust force is produced as the
leading edge vortex shedding from the trailing edge of airfoil to form a
reverse von Karman vortex. Results also indicated that the inclined
angle is the most significant factor on both the lift force and thrust
force. There are strong interactions between tested factors which mean
an optimization study on parameters should be conducted in further
runs.
Abstract: Home Automation is a field that, among other
subjects, is concerned with the comfort, security and energy
requirements of private homes. The configuration of automatic
functions in this type of houses is not always simple to its inhabitants
requiring the initial setup and regular adjustments. In this work, the
ubiquitous computing system vision is used, where the users- action
patterns are captured, recorded and used to create the contextawareness
that allows the self-configuration of the home automation
system. The system will try to free the users from setup adjustments
as the home tries to adapt to its inhabitants- real habits. In this paper
it is described a completely automated process to determine the light
state and act on them, taking in account the users- daily habits.
Artificial Neural Network (ANN) is used as a pattern recognition
method, classifying for each moment the light state. The work
presented uses data from a real house where a family is actually
living.
Abstract: XML data consists of a very flexible tree-structure
which makes it difficult to support the storing and retrieving of XML
data. The node numbering scheme is one of the most popular
approaches to store XML in relational databases. Together with the
node numbering storage scheme, structural joins can be used to
efficiently process the hierarchical relationships in XML. However, in
order to process a tree-structured XPath query containing several
hierarchical relationships and conditional sentences on XML data,
many structural joins need to be carried out, which results in a high
query execution cost. This paper introduces mechanisms to reduce the
XPath queries including branch nodes into a much more efficient form
with less numbers of structural joins. A two step approach is proposed.
The first step merges duplicate nodes in the tree-structured query and
the second step divides the query into sub-queries, shortens the paths
and then merges the sub-queries back together. The proposed
approach can highly contribute to the efficient execution of XML
queries. Experimental results show that the proposed scheme can
reduce the query execution cost by up to an order of magnitude of the
original execution cost.
Abstract: Beta-spline is built on G2 continuity which guarantees
smoothness of generated curves and surfaces using it. This curve is
preferred to be used in object design rather than reconstruction. This
study however, employs the Beta-spline in reconstructing a 3-
dimensional G2 image of the Stanford Rabbit. The original data
consists of multi-slice binary images of the rabbit. The result is then
compared with related works using other techniques.
Abstract: This paper presents a single correlator RAKE receiver for direct sequence code division multiple access (DS-CDMA) systems. In conventional RAKE receivers, multiple correlators are used to despread the multipath signals and then to align and combine those signals in a later stage before making a bit decision. The simplified receiver structure presented here uses a single correlator and single code sequence generator to recover the multipaths. Modified Walsh- Hadamard codes are used here for data spreading that provides better uncorrelation properties for the multipath signals. The main advantage of this receiver structure is that it requires only a single correlator and a code generator in contrary to the conventional RAKE receiver concept with multiple correlators. It is shown in results that the proposed receiver achieves better bit error rates in comparison with the conventional one for more than one multipaths.
Abstract: The increasing development of wireless networks and
the widespread popularity of handheld devices such as Personal
Digital Assistants (PDAs), mobile phones and wireless tablets
represents an incredible opportunity to enable mobile devices as a
universal payment method, involving daily financial transactions.
Unfortunately, some issues hampering the widespread acceptance of
mobile payment such as accountability properties, privacy protection,
limitation of wireless network and mobile device. Recently, many
public-key cryptography based mobile payment protocol have been
proposed. However, limited capabilities of mobile devices and
wireless networks make these protocols are unsuitable for mobile
network. Moreover, these protocols were designed to preserve
traditional flow of payment data, which is vulnerable to attack and
increase the user-s risk. In this paper, we propose a private mobile
payment protocol which based on client centric model and by
employing symmetric key operations. The proposed mobile payment
protocol not only minimizes the computational operations and
communication passes between the engaging parties, but also
achieves a completely privacy protection for the payer. The future
work will concentrate on improving the verification solution to
support mobile user authentication and authorization for mobile
payment transactions.
Abstract: Knowledge is a key asset for any organisation to
sustain competitive advantages, but it is difficult to identify and
represent knowledge which is needed to perform activities in
business processes. The effective knowledge management and
support for relevant business activities definitely gives a huge impact
to the performance of the organisation as a whole. This is because
that knowledge have the functions of directing, coordinating and
controlling actions within business processes. The study has
introduced organisational morphology, a norm-based approach by
applying semiotic theories which emphasise on the representation of
knowledge in norms. This approach is concerned with the
identification of activities into three categories: substantive,
communication and control activities. All activities are directed by
norms; hence three types of norms exist; each is associated to a
category of activities. The paper describes the approach briefly and
illustrates the application of this approach through a case study of
academic activities in higher education institutions. The result of the
study shows that the approach provides an effective way to profile
business knowledge and the profile enables the understanding and
specification of business requirements of an organisation.
Abstract: Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.
Abstract: In the oil and gas industry, energy prediction can help
the distributor and customer to forecast the outgoing and incoming
gas through the pipeline. It will also help to eliminate any
uncertainties in gas metering for billing purposes. The objective of
this paper is to develop Neural Network Model for energy
consumption and analyze the performance model. This paper
provides a comprehensive review on published research on the
energy consumption prediction which focuses on structures and the
parameters used in developing Neural Network models. This paper is
then focused on the parameter selection of the neural network
prediction model development for energy consumption and analysis
on the result. The most reliable model that gives the most accurate
result is proposed for the prediction. The result shows that the
proposed neural network energy prediction model is able to
demonstrate an adequate performance with least Root Mean Square
Error.
Abstract: Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: Geometric design is an important part of planning
process design for physical highway to fill up basic function of roads,
to give good traffic service. It is found that most of the road safety
problems occur at the horizontal curves and complex-compound
curves. In this paper, review on Sagarinn-Myinsain Portion of Nay
Pyi Taw - Mandalay highway has been conducted in aspect of
geometric design induced road safety condition. Horizontal
alignment of geometric features and curve details are reviewed based
on (AASHTO) standard and revised by Autodesk Land Desktop
Software. Moreover, 85th Percentile Operation Speeds (V85) with
driver confidence on horizontal curves is evaluated in order to obtain
the range of highway safety factor (FS). The length of the selected
highway portion is 13.65 miles and 8 lanes. The results of this study
can be used to investigate the possible hazardous locations in
advance and to revise how design radius and super elevation should
be for better road safety performance for the selected portion.
Moreover, the relationship between highway safety and highway
geometry characteristics can also be known.
Abstract: This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: Edge detection is usually the first step in medical
image processing. However, the difficulty increases when a
conventional kernel-based edge detector is applied to ultrasonic
images with a textural pattern and speckle noise. We designed an
adaptive diffusion filter to remove speckle noise while preserving the
initial edges detected by using a Sobel edge detector. We also propose
a genetic algorithm for edge selection to form complete boundaries of
the detected entities. We designed two fitness functions to evaluate
whether a criterion with a complex edge configuration can render a
better result than a simple criterion such as the strength of gradient.
The edges obtained by using a complex fitness function are thicker and
more fragmented than those obtained by using a simple fitness
function, suggesting that a complex edge selecting scheme is not
necessary for good edge detection in medical ultrasonic images;
instead, a proper noise-smoothing filter is the key.
Abstract: Determining reasonable fees is the main objective of designing the cost estimation and payment systems for consultant contracts. However, project clients utilize different cost estimation and payment systems because of their varying views on the reasonableness of consultant fees. This study reviews the cost estimation and payment systems of consultant contracts for five countries, including the US (Washington State Department of Transportation), Japan (Ministry of Land, Infrastructure, Transport and Tourism), China (Engineering Design Charging Standard) and UK (Her Majesty's Treasure). Specifically, this work investigates the budgeting process, contractor selection method, contractual price negotiation process, cost review, and cost-control concept of the systems used in these countries. The main finding indicates that that project client-s view on whether the fee is high will affect the way he controls it. In the US, the fee is commonly considered to be high. As a result, stringent auditing system (low flexibility given to the consultant) is then applied. In the UK, the fee is viewed to be low by comparing it to the total life-cycle project cost. Thus, a system that has high flexibility in budgeting and cost reviewing is given to the consultant. In terms of the flexibility allowed for the consultant, the systems applied in Japan and China fall between those of the US and UK. Both the US and UK systems are helpful in determining a reasonable fee. However, in the US system, rigid auditing standards must be established and additional cost-audit manpower is required. In the UK system, sufficient historical cost data should be needed to evaluate the reasonableness of the consultant-s proposed fee