Abstract: IEEE 802.15.4a impulse radio-time hopping ultra wide
band (IR-TH UWB) physical layer, due to small duty cycle and very
short pulse widths is robust against multipath propagation. However,
scattering and reflections with the large number of obstacles in indoor
channel environments, give rise to dense multipath fading. It imposes
serious problem to optimum Rake receiver architectures, for which
very large number of fingers are needed. Presence of strong noise
also affects the reception of fine pulses having extremely low power
spectral density. A robust SRake receiver for IEEE 802.15.4a IRTH
UWB in dense multipath and additive white Gaussian noise
(AWGN) is proposed to efficiently recover the weak signals with
much reduced complexity. It adaptively increases the signal to noise
(SNR) by decreasing noise through a recursive least square (RLS)
algorithm. For simulation, dense multipath environment of IEEE
802.15.4a industrial non line of sight (NLOS) is employed. The power
delay profile (PDF) and the cumulative distribution function (CDF)
for the respective channel environment are found. Moreover, the error
performance of the proposed architecture is evaluated in comparison
with conventional SRake and AWGN correlation receivers. The
simulation results indicate a substantial performance improvement
with very less number of Rake fingers.
Abstract: In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.
Abstract: Various solar energy technologies exist and they have
different application techniques in the generation of electrical power.
The widespread use of photovoltaic (PV) modules in such
technologies has been limited by relatively high costs and low
efficiencies. The efficiency of PV panels decreases as the operating
temperatures increase. This is due to the affect of solar intensity and
ambient temperature. In this work, Computational Fluid Dynamics
(CFD) was used to model the heat transfer from a standard PV panel
and thus determine the rate of dissipation of heat. To accurately
model the specific climatic conditions of the United Arab Emirates
(UAE), a case study of a new build green building in Dubai was
used. A finned heat pipe arrangement is proposed and analyzed to
determine the improved heat dissipation and thus improved
performance efficiency of the PV panel. A prototype of the
arrangement is built for experimental testing to validate the CFD
modeling and proof of concept.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution. Unfortunately, process data are composed by the mixture of several processes and it is hard to estimate as one certain distribution. To alternative conventional SPC, therefore, nonparametric control chart come into the picture because of the strength of nonparametric control chart, the absence of parameter estimation. SVDD based control chart is one of the nonparametric control charts having the advantage of flexible control boundary. However,basic concept of SVDD has been an oversight to the important of data characteristic, density distribution. Therefore, we proposed DW-SVDD (Density Weighted SVDD) to cover up the weakness of conventional SVDD. DW-SVDD makes a new attempt to consider dense of data as introducing the notion of density Weight. We extend as control chart using new proposed SVDD and a simulation study of various distributional data is conducted to demonstrate the improvement of performance.
Abstract: The focus of this paper is to construct daily time series
exchange rate forecast models of Samoan Tala/USD and Tala/AUD
during the year 2008 to 2012 with neural network The performance
of the models was measured by using varies error functions such as
Root Square mean error (RSME), Mean absolute error (MAE), and
Mean absolute percentage error (MAPE). Our empirical findings
suggest that AR (1) model is an effective tool to forecast the
Tala/USD and Tala/AUD.
Abstract: A DC servomotor position control system using a Fuzzy Logic Sliding mode Model Following Control or FLSMFC approach is presented. The FLSMFC structure consists of an integrator and variable structure system. The integral control is introduced into it in order to eliminated steady state error due to step and ramp command inputs and improve control precision, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a DC servomotor drives. Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, excellent control effects and avoids the chattering phenomenon.
Abstract: The performance of modified Fenton (MF) treatment
to promote PAH oxidation in artificially contaminated soil was
investigated in packed soil column with a hydrogen peroxide (H2O2)
delivery system simulating in situ injection. Soil samples were spiked
with phenanthrene (low molecular weight PAH) and fluoranthene
(high molecular weight PAH) to an initial concentration of 500
mg/kg dried soil each. The effectiveness of process parameters
H2O2/soil, iron/soil, chelating agent/soil weight ratios and reaction
time were studied using a 24 three level factorial design experiments.
Statistically significant quadratic models were developed using
Response Surface Methodology (RSM) for degrading PAHs from the
soil samples. Optimum operating condition was achieved at mild
range of H2O2/soil, iron/soil and chelating agent/soil weight ratios,
indicating cost efficient method for treating highly contaminated
lands.
Abstract: The quality-of-service (QoS) support for wireless
LANs has been a hot research topic during the past few years. In this paper, two QoS provisioning mechanisms are proposed for the employment in 802.11e EDCA MAC scheme. First, the proposed call
admission control mechanism can not only guarantee the QoS for the higher priority existing connections but also provide the minimum reserved bandwidth for traffic flows with lower priority. In addition, the adaptive contention window adjustment mechanism can adjust the
maximum and minimum contention window size dynamically according to the existing connection number of each AC. The collision
probability as well as the packet delay will thus be reduced effectively.
Performance results via simulations have revealed the enhanced QoS property achieved by employing these two mechanisms.
Abstract: Scheduling algorithm is a key technology in satellite
switching system with input-buffer. In this paper, a new scheduling
algorithm and its realization are proposed. Based on Crossbar
switching fabric, the algorithm adopts serial scheduling strategy and
adjusts the output port arbitrating strategy for the better equity of every
port. Consequently, it increases the matching probability. The
algorithm can greatly reduce the scheduling delay and cell loss rate.
The analysis and simulation results by OPNET show that the proposed
algorithm has the better performance than others in average delay and
cell loss rate, and has the equivalent complexity. On the basis of these
results, the hardware realization and simulation based on FPGA are
completed, which validate the feasibility of the new scheduling
algorithm.
Abstract: Image segmentation is an important step in image
processing. Major developments in medical imaging allow
physicians to use potent and non-invasive methods in order to
evaluate structures, performance and to diagnose human diseases. In
this study, an active contour was used to extract vessel networks
from color retina images. Automatic analysis of retina vessels
facilitates calculation of arterial index which is required to diagnose
some certain retinopathies.
Abstract: To improve the dynamics response of the vehicle
passive suspension, a two-terminal mass is suggested to connect in
parallel with the suspension strut. Three performance criteria, tire grip,
ride comfort and suspension deflection, are taken into consideration to
optimize the suspension parameters. However, the three criteria are
conflicting and non-commensurable. For this reason, the Chebyshev
goal programming method is applied to find the best tradeoff among
the three objectives. A simulation case is presented to describe the
multi-objective optimization procedure. For comparison, the
Chebyshev method is also employed to optimize the design of a
conventional passive suspension. The effectiveness of the proposed
design method has been clearly demonstrated by the result. It is also
shown that the suspension with a two-terminal mass in parallel has
better performance in terms of the three objectives.
Abstract: Mobile WiMAX is a broadband wireless solution that
enables convergence of mobile and fixed broadband networks
through a common wide area broadband radio access technology and
flexible network architecture. It adopts Orthogonal Frequency
Division Multiple Access (OFDMA) for improved multi-path
performance in Non-Line-Of-Sight (NLOS) environments. Scalable
OFDMA (SOFDMA) is introduced in the IEEE 802e[1]. WIMAX
system uses one of different types of channel coding but The
mandatory channel coding scheme is based on binary nonrecursive
Convolutional Coding (CC). There are other several optional channel
coding schemes such as block turbo codes, convolutional turbo
codes, and low density parity check (LDPC).
In this paper a comparison between the performance of WIMAX
using turbo code and using convolutional product code (CPC) [2] is
made. Also a combination between them had been done. The CPC
gives good results at different SNR values compared to both the
turbo system, and the combination between them. For example, at
BER equal to 10-2 for 128 subcarriers, the amount of improvement
in SNR equals approximately 3 dB higher than turbo code and equals
approximately 2dB higher than the combination respectively. Several
results are obtained at different modulating schemes (16QAM and
64QAM) and different numbers of sub-carriers (128 and 512).
Abstract: The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.
Abstract: Motion control of flexible arms is more difficult than
that of rigid arms, however utilizing its dynamics enables improved
performance such as a fast motion in short operation time. This paper
investigates a ball throwing robot with one rigid link and one flexible
link. This robot throws a ball at a set speed with a proper control torque.
A mathematical model of this ball throwing robot is derived through
Hamilton’s principle. Several patterns of torque input are designed and
tested through the proposed simulation models. The parameters of
each torque input pattern is optimized and determined by chaos
embedded vector evaluated particle swarm optimization (CEVEPSO).
Then, the residual vibration of the manipulator after throwing is
suppressed with input shaping technique. Finally, a real experiment is
set up for the model checking.
Abstract: This research aimed to develop plasma system used in air conditioners. This developed plasma system could be installed in the air conditioners - all split type. The quality of air could be improved to be equal to present plasma system. Development processes were as follows: 1) to study the plasma system used in the air conditioners, 2) to design a plasma generator, 3) to develop the plasma generator, and 4) to test its performance in many types of the air conditioners. This plasma system was developed by AC high voltage – 14 kv with a frequency of 50 kHz. Carbon was a conductor to generate arc in air purifier system. The research was tested by installing the plasma generator in the air conditioners - wall type. Whereas, there were 3 types of installations: air flow out, air flow in, and room center. The result of the plasma generator installed in the air conditioners, split type, revealed that the air flow out installation provided the highest average of o-zone at 223 mg/h. This type of installation provided the highest efficiency of air quality improvement. Moreover, the air flow in installation and the room center installation provided the average of the o-zone at 163 mg/h and 64 mg/h, respectively.
Abstract: A study concerning the photocatalytic decolourization
of Congo red (CR) dye, over artificial UV irradiation is presented.
Photocatalysts based on a commercial titanium dioxide (TiO2)
modified with transition metals (Ni, Cu and Zn) were used. The
dopage method used was wet impregnation. A TiO2 sample without
salt was subjected to the same hydrothermal treatment to be used as
reference. Congo red solutions to several pH conditions (natural and
basic) were used to evaluate photocatalytic performance of each
doped catalysts. Photodecolourization percentage was measured
spectrofotrometically after 3 h of treatment to 499 nm as response
variable. Kinetics investigations of photodegradation indicated that
reactions obey to Langmuir-Hinshelwood model and pseudo–first
order law. The rate constant studies of photocatalytic decolourization
reactions for Zn–TiO2 and Cu–TiO2 photocatalysts indicated that in
all cases the rate constant of the reaction was higher than that of TiO2
undoped. These results show that nature of the metal modifying the
TiO2 influence on the efficiency of the photocatalyst evaluated in
process. Ni does not present an additional effect compared with TiO2,
while Zn enhances the photoactivity due to its electronic properties.
Abstract: A new blind symbol by symbol equalizer is proposed.
The operation of the proposed equalizer is based on the geometric
properties of the two dimensional data constellation. An unsupervised
clustering technique is used to locate the clusters formed by the
received data. The symmetric properties of the clusters labels are
subsequently utilized in order to label the clusters. Following this
step, the received data are compared to clusters and decisions are
made on a symbol by symbol basis, by assigning to each data
the label of the nearest cluster. The operation of the equalizer is
investigated both in linear and nonlinear channels. The performance
of the proposed equalizer is compared to the performance of a CMAbased
blind equalizer.
Abstract: In this study, cometabolic biodegradation of
chloroform was experimented with mixed cultures in the presence of
various organic solvents like methanol, ethanol, isopropanol, acetone,
acetonitrile and toluene as these are predominant discharges in
pharmaceutical industries. Toluene and acetone showed higher
specific chloroform degradation rate when compared to other
compounds. Cometabolic degradation of chloroform was further
confirmed by observation of free chloride ions in the medium. An
extended Haldane model, incorporating the inhibition due to
chloroform and the competitive inhibition between primary
substrates, was developed to predict the biodegradation of primary
substrates, cometabolic degradation of chloroform and the biomass
growth. The proposed model is based on the use of biokinetic
parameters obtained from single substrate degradation studies. The
model was able to satisfactorily predict the experimental results of
ternary and quaternary mixtures. The proposed model can be used for
predicting the performance of bioreactors treating discharges from
pharmaceutical industries.
Abstract: The work presented in this study is related to an
energy system analysis based on passive cooling system for
dwellings. It consists to solar chimney energy performances
determination versus geometrical and environmental considerations
as the size and inlet width conditions of the chimney. Adrar site
located in the southern region of Algeria is chosen for this study
according to ambient temperature and solar irradiance technical data
availability. Obtained results are related to the glazing temperature
distributions, the chimney air flow and internal wall temperatures.
The air room change per hour (ACH) parameter, the outlet air
velocity and mass air flow rate are also determined. It is shown that
the chimney width has a significant effect on energy performances
compared to its entry size. A good agreement is observed between
these results and those obtained by others from the literature.