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: A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.
Abstract: Given a large sparse signal, great wishes are to
reconstruct the signal precisely and accurately from lease number of
measurements as possible as it could. Although this seems possible
by theory, the difficulty is in built an algorithm to perform the
accuracy and efficiency of reconstructing. This paper proposes a new
proved method to reconstruct sparse signal depend on using new
method called Least Support Matching Pursuit (LS-OMP) merge it
with the theory of Partial Knowing Support (PSK) given new method
called Partially Knowing of Least Support Orthogonal Matching
Pursuit (PKLS-OMP).
The new methods depend on the greedy algorithm to compute the
support which depends on the number of iterations. So to make it
faster, the PKLS-OMP adds the idea of partial knowing support of its
algorithm. It shows the efficiency, simplicity, and accuracy to get
back the original signal if the sampling matrix satisfies the Restricted
Isometry Property (RIP).
Simulation results also show that it outperforms many algorithms
especially for compressible signals.
Abstract: This work presents the first results from the long-term experiment, which is focused on the impact of intensive rainfall and long period of drought on microbial activities in soil. Fifteen lysimeters were prepared in the area of our interest. This area is a protection zone of underground source of drinking water. These lysimeters were filed with topsoil and subsoil collected in this area and divided into two groups. These groups differ in fertilization and amount of water received during the growing season. Amount of microbial biomass and leaching of mineral nitrogen and phosphates were chosen as main indicators of microbial activities in soil. Content of mineral nitrogen and phosphates was measured in soil solution, which was collected from each lysimeters. Amount of microbial biomass was determined in soil samples that were taken from the lysimeters before and after the long period of drought and intensive rainfall.
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: We study the possibility of using geometric operators
in the selection of human resources. We develop three new methods
that use the ordered weighted geometric (OWG) operator in different
indexes used for the selection of human resources. The objective of
these models is to manipulate the neutrality of the old methods so the
decision maker is able to select human resources according to his
particular attitude. In order to develop these models, first a short
revision of the OWG operator is developed. Second, we briefly
explain the general process for the selection of human resources.
Then, we develop the three new indexes. They will use the OWG
operator in the Hamming distance, in the adequacy coefficient and in
the index of maximum and minimum level. Finally, an illustrative
example about the new approach is given.
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: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: The aim for this research is to deliberately discuss
how and why the contexts of culture are the main significant factors
which need to be considered when conducting the international
business oversea. As a consequence of understanding these various
factors, the researcher would be able to infer some suggestions to the
international organizations. With this in mind, the results of the
understanding in a national culture environment can support the
organizations to settle its international strategies which may be useful
to develop the national export and import effectiveness. This data
collecting methods will be concentrated upon 5-10 interviews from
the senior members and business officers in the international
company in Thailand by e-mail interview and analyses the individual
manager’s viewpoint. As well as, focus on the questionnaires which
the respondents were selected randomly around 100 samples from
UK and Thailand, together with providing a functional sample size
and comparable to data. The results of the study question the role of
national culture, which contributed to in international business
effectiveness and emphasize the positive and negative aspects, as
well as suggestions to business investors are informed.
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 aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.
Abstract: This paper addresses the problem of source separation
in images. We propose a FastICA algorithm employing a modified
Gaussian contrast function for the Blind Source Separation.
Experimental result shows that the proposed Modified Gaussian
FastICA is effectively used for Blind Source Separation to obtain
better quality images. In this paper, a comparative study has been
made with other popular existing algorithms. The peak signal to
noise ratio (PSNR) and improved signal to noise ratio (ISNR) are
used as metrics for evaluating the quality of images. The ICA metric
Amari error is also used to measure the quality of separation.
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: A first intermediate roll of Sendzirmir mills was failure
by surface spalling during operation. After analyzing by visual, stereo
microscope, optical microscope, scanning electron microscope,
glow-discharged spectrometer and hardness test, respectively, the
results show that some voids and cracks existed on the contact surface
as well as subsurface. Further examination verified inadequate
hardness and inclusions were responsible for the failure of surface
spalling.
Abstract: Nonspecific protein adsorption generally occurs on
any solid surfaces and usually has adverse consequences. Adsorption
of proteins onto a solid surface is believed to be the initial and
controlling step in biofouling. Surfaces modified with end-tethered
poly(ethylene glycol) (PEG) have been shown to be protein-resistant
to some degree. In this study, the adsorption of β-casein and
lysozyme was performed on 6 different types of surfaces where PEG
was tethered onto stainless steel by polyethylene imine (PEI) through
either OH or NHS end groups. Protein adsorption was also performed
on the bare stainless steel surface as a control. The adsorption was
conducted at 23 °C and pH 7.2. In situ QCM-D was used to
determine PEG adsorption kinetics, plateau PEG chain densities,
protein adsorption kinetics and plateau protein adsorbed quantities.
PEG grafting density was the highest for a NHS coupled chain,
around 0.5 chains / nm2. Interestingly, lysozyme which has smaller
size than β-casein, appeared to adsorb much less mass than that of β-
casein. Overall, the surface with high PEG grafting density exhibited
a good protein rejection.
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: This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.