Abstract: Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.
Abstract: Sinc-collocation scheme is one of the new techniques
used in solving numerical problems involving integral equations. This
method has been shown to be a powerful numerical tool for finding
fast and accurate solutions. So, in this paper, some properties of the
Sinc-collocation method required for our subsequent development
are given and are utilized to reduce integral equation of the first
kind to some algebraic equations. Then convergence with exponential
rate is proved by a theorem to guarantee applicability of numerical
technique. Finally, numerical examples are included to demonstrate
the validity and applicability of the technique.
Abstract: this paper focuses on designing of PSS and SVC
controller based on chaos and PSO algorithms to improve the
stability of power system. Single machine infinite bus (SMIB) system
with SVC located at the terminal of generator has been considered to
evaluate the proposed controllers where both SVC and PSS have the
same controller. The coefficients of PSS and SVC controller have
been optimized by chaos and PSO algorithms. Finally the system
with proposed controllers has been simulated for the special
disturbance in input power of generator, and then the dynamic
responses of generator have been presented. The simulation results
showed that the system composed with recommended controller has
outstanding operation in fast damping of oscillations of power system.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: Today, money laundering (ML) poses a serious threat
not only to financial institutions but also to the nation. This criminal
activity is becoming more and more sophisticated and seems to have
moved from the cliché of drug trafficking to financing terrorism and
surely not forgetting personal gain. Most international financial
institutions have been implementing anti-money laundering solutions
(AML) to fight investment fraud. However, traditional investigative
techniques consume numerous man-hours. Recently, data mining
approaches have been developed and are considered as well-suited
techniques for detecting ML activities. Within the scope of a
collaboration project for the purpose of developing a new solution for
the AML Units in an international investment bank, we proposed a
data mining-based solution for AML. In this paper, we present a
heuristics approach to improve the performance for this solution. We
also show some preliminary results associated with this method on
analysing transaction datasets.
Abstract: This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.
Abstract: In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.
Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: This study was designed to investigate the role of serum nitric oxide and sialic acid in the development of diabetic nephropathy as disease marker. Total 210 diabetic patients (age and sex matched) were selected followed by informed consent and divided into four groups (70 each) as I: control; II: diabetic; III: diabetic hypertensive; IV: diabetic nephropathy. The blood samples of all subjects were collected and analyzed for serum nitric oxide, sialic acid, fasting blood glucose, serum urea, creatinine, HbA1c and GFR. The BMI, systolic and diastolic blood pressures, blood glucose, HbA1c and serum sialic acid levels were high (p
Abstract: This paper presents a controller design technique for
Synchronous Reluctance Motor to improve its dynamic performance
with fast response and high accuracy. The sliding mode control is the
most attractive and suitable method to use for this purpose, since it is
simple in design and for its insensitivity to parameter variations or
external disturbances. When this method implemented it yields fast
dynamic response without overshoot and a zero steady-state error.
The current loop control with decentralized sliding mode is presented
in this paper. The mathematical model for the synchronous machine,
the inverter and the controller is developed. The stability of the
sliding mode controller is analyzed. Simulation of synchronous
reluctance motor and the controller with PWM-inverter has been
curried out, using the SIMULINK software package of MATLAB.
Simulation results are presented to show the effectiveness of the
approach.
Abstract: Ten percent of the population will develop plantar
fasciitis (PF) during their lifetime. Two million people are treated
yearly accounting for 11-15% of visits to medical professionals.
Treatment ranges from conservative to surgical intervention. The
purpose of this study was to assess the effects of extracorporeal
shockwave therapy (ECSWT) on heel pain, function, range of motion
(ROM), and strength in patients with PF. One hundred subjects were
treated with ECSWT and measures were taken before and three
months after treatment. There was significant differences in visual
analog scale scores for pain at rest (p=0.0001); after activity (p=
0.0001) and; overall improvement (p=0.0001). There was also
significant improvement in Lower Extremity Functional Scale scores
(p=0.0001); ankle plantarflexion (p=0.0001), dorsiflexion (p=0.001),
and eversion (p=0.017),and first metatarsophalangeal joint flexion
(p=0.002) and extension (p=0.003) ROM. ECSWT is an effective
treatment improving heel pain, function and ROM in patients with
PF.
Abstract: Nowadays, a passenger car suspension must has high
performance criteria with light weight, low cost, and low energy
consumption. Pilot controlled proportional valve is designed and
analyzed to get small pressure change rate after blow-off, and to get a
fast response of the damper, a reverse damping mechanism is adapted.
The reverse continuous variable damper is designed as a HS-SH
damper which offers good body control with reduced transferred input
force from the tire, compared with any other type of suspension
system. The damper structure is designed, so that rebound and
compression damping forces can be tuned independently, of which the
variable valve is placed externally. The rate of pressure change with
respect to the flow rate after blow-off becomes smooth when the fixed
orifice size increases, which means that the blow-off slope is
controllable using the fixed orifice size. Damping forces are measured
with the change of the solenoid current at the different piston
velocities to confirm the maximum hysteresis of 20 N, linearity, and
variance of damping force. The damping force variance is wide and
continuous, and is controlled by the spool opening, of which scheme is
usually adapted in proportional valves. The reverse continuous
variable damper developed in this study is expected to be utilized in
the semi-active suspension systems in passenger cars after its
performance and simplicity of the design is confirmed through a real
car test.
Abstract: In this work we introduce an efficient method to limit
the impact of the hiding process on the quality of the cover speech.
Vector quantization of the speech spectral information reduces drastically
the number of the secret speech parameters to be embedded
in the cover signal. Compared to scalar hiding, vector quantization
hiding technique provides a stego signal that is indistinguishable from
the cover speech. The objective and subjective performance measures
reveal that the current hiding technique attracts no suspicion about the
presence of the secret message in the stego speech, while being able
to recover an intelligible copy of the secret message at the receiver
side.
Abstract: The cellular network is one of the emerging areas of
communication, in which the mobile nodes act as member for one
base station. The cluster based communication is now an emerging
area of wireless cellular multimedia networks. The cluster renders
fast communication and also a convenient way to work with
connectivity. In our scheme we have proposed an optimization
technique for the fuzzy cluster nodes, by categorizing the group
members into three categories like long refreshable member, medium
refreshable member and short refreshable member. By considering
long refreshable nodes as static nodes, we compute the new
membership values for the other nodes in the cluster. We compare
their previous and present membership value with the threshold value
to categorize them into three different members. By which, we
optimize the nodes in the fuzzy clusters. The simulation results show
that there is reduction in the cluster computational time and
iterational time after optimization.
Abstract: In multi hop wireless systems, such as ad hoc and
sensor networks, mobile ad hoc network applications are deployed,
security emerges as a central requirement. A particularly devastating
attack is known as the wormhole attack, where two or more malicious
colluding nodes create a higher level virtual tunnel in the network,
which is employed to transport packets between the tunnel end points.
These tunnels emulate shorter links in the network. In which
adversary records transmitted packets at one location in the network,
tunnels them to another location, and retransmits them into the
network. The wormhole attack is possible even if the attacker has not
compromised any hosts and even if all communication provides
authenticity and confidentiality. In this paper, we analyze wormhole
attack nature in ad hoc and sensor networks and existing methods of
the defending mechanism to detect wormhole attacks without require
any specialized hardware. This analysis able to provide in
establishing a method to reduce the rate of refresh time and the
response time to become more faster.
Abstract: In this paper, we present the preconditioned mixed-type
splitting iterative method for solving the linear systems, Ax = b,
where A is a Z-matrix. And we give some comparison theorems
to show that the convergence rate of the preconditioned mixed-type
splitting iterative method is faster than that of the mixed-type splitting
iterative method. Finally, we give a numerical example to illustrate
our results.
Abstract: This research studied the hypoglycemic effect of
water soluble polysaccharide (WSP) extracted from yam (Dioscorea
hispida) tuber by three different methods: aqueous extraction, papain
assisted extraction, and tempeh inoculums assisted extraction. The
two later extraction methods were aimed to remove WSP binding
protein to have more pure WSP. The hypoglycemic activities were
evaluated by means in vivo test on alloxan induced hyperglycemic
rats, glucose response test (GRT), in situ glucose absorption test
using everted sac, and short chain fatty acids (SCFAs) analysis. All
yam WSP extracts exhibited ability to decrease blood glucose level in
hyperglycemia condition as well as inhibited glucose absorption and
SCFA formation. The order of hypoglycemic activity was tempeh
inoculums assisted- >papain assisted- >aqueous WSP extracts. GRT
and in situ glucose absorption test showed that order of inhibition
was papain assisted- >tempeh inoculums assisted- >aqueous WSP
extracts. Digesta of caecum of yam WSP extracts oral fed rats had
more SCFA than control. Tempeh inoculums assisted WSP extract
exhibited the most significant hypoglycemic activity.
Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.
Abstract: Fuller’s earth is a fine-grained, naturally occurring substance that has a substantial ability to adsorb impurities. In the present study Fuller’s earth has been characterized and used for the removal of Pb(II) from aqueous solution. The effect of various physicochemical parameters such as pH, adsorbent dosage and shaking time on adsorption were studied. The result of the equilibrium studies showed that the solution pH was the key factor affecting the adsorption. The optimum pH for adsorption was 5. Kinetics data for the adsorption of Pb(II) was best described by pseudo-second order model. The effective diffusion co-efficient for Pb(II) adsorption was of the order of 10-8 m2/s. The adsorption data for metal adsorption can be well described by Langmuir adsorption isotherm. The maximum uptake of metal was 103.3 mg/g of adsorbent. Mass transfer analysis was also carried out for the adsorption process. The values of mass transfer coefficients obtained from the study indicate that the velocity of the adsorbate transport from bulk to the solid phase was quite fast. The mean sorption energy calculated from Dubinin-Radushkevich isotherm indicated that the metal adsorption process was chemical in nature.
Abstract: In this paper, a simple heuristic genetic algorithm is
used for Multistage Multiuser detection in fast fading environments.
Multipath channels, multiple access interference (MAI) and near far
effect cause the performance of the conventional detector to degrade.
Heuristic Genetic algorithms, a rapidly growing area of artificial
intelligence, uses evolutionary programming for initial search, which
not only helps to converge the solution towards near optimal
performance efficiently but also at a very low complexity as
compared with optimal detector. This holds true for Additive White
Gaussian Noise (AWGN) and multipath fading channels.
Experimental results are presented to show the superior performance
of the proposed techque over the existing methods.