Abstract: The model of neural networks on the small-world
topology, with metric (local and random connectivity) is investigated.
The synaptic weights are random, driving the network towards a
chaotic state for the neural activity. An ordered macroscopic neuron
state is induced by a bias in the network connections. When the
connections are mainly local, the network emulates a block-like
structure. It is found that the topology and the bias compete to
influence the network to evolve into a global or a block activity
ordering, according to the initial conditions.
Abstract: In recent years, the number of the cases of information
leaks is increasing. Companies and Research Institutions make various
actions against information thefts and security accidents. One of the
actions is adoption of the crime prevention system, including the
monitoring system by surveillance cameras. In order to solve
difficulties of multiple cameras monitoring, we develop the automatic
human tracking system using mobile agents through multiple
surveillance cameras to track target persons. In this paper, we develop
the monitor which confirms mobile agents tracing target persons, and
the simulator of video picture analysis to construct the tracking
algorithm.
Abstract: In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Abstract: This study aims to identify cellular phone users- shopping motivating factors towards online shopping. 100 university students located in Klang Valley, Malaysia were involved as the respondents. They were required to complete a set of questionnaire and had to own a cellular phone in order to be selected as sample in this study. Three from five proposed hypotheses were supported: purchasing information, shopping utilities and service quality. As a result, marketers and retailers should concentrate more on the less important factors in order to encourage and create willingness of the consumers to purchase online. Recommendation for future research is also presented.
Abstract: The genus Fumaria L. (Papaveraceae) in Iran
comprises 8 species with a vast medicinal use in Asian folk
medicine. These herbs are considered to be useful in the
treatment of gastrointestinal disease and skin disorders.
Antioxidant activities of alkaloids and phenolic extracts of
these species had been studied previously. These species are:
F. officinalis, F. parviflora, F. asepala, F. densiflora, F.
schleicheri, F. vaillantii and F. indica. More than 50
populations of Fumaria species were sampled from nature. In
this study different fatty acids are extracted. Their picks were
recorded by GC technique. This species contain some kind of
fatty acids with antioxidant effects. A part of these lipids are
phospholipids. As these are unsaturated fatty acids they may
have industrial use as natural additive to cosmetics, dermal
and oral medicines. The presences of different materials are
discussed. Our studies for antioxidant effects of these
substances are continued.
Abstract: Most papers model Joint Replenishment Problem
(JRP) as a (kT,S) where kT is a multiple value for a common review
period T,and S is a predefined order up to level. In general the (T,S)
policy is characterized by a long out of control period which requires
a large amount of safety stock compared to the (R,Q) policy. In this
paper a probabilistic model is built where an item, call it item(i),
with the shortest order time between interval (T)is modeled under
(R,Q) policy and its inventory is continuously reviewed, while the
rest of items (j) are periodically reviewed at a definite time
corresponding to item
Abstract: This paper presents an adaptive motion estimator
that can be dynamically reconfigured by the best algorithm
depending on the variation of the video nature during the lifetime
of an application under running. The 4 Step Search (4SS) and the
Gradient Search (GS) algorithms are integrated in the estimator in
order to be used in the case of rapid and slow video sequences
respectively. The Full Search Block Matching (FSBM) algorithm
has been also integrated in order to be used in the case of the
video sequences which are not real time oriented.
In order to efficiently reduce the computational cost while
achieving better visual quality with low cost power, the proposed
motion estimator is based on a Variable Block Size (VBS) scheme
that uses only the 16x16, 16x8, 8x16 and 8x8 modes.
Experimental results show that the adaptive motion estimator
allows better results in term of Peak Signal to Noise Ratio
(PSNR), computational cost, FPGA occupied area, and dissipated
power relatively to the most popular variable block size schemes
presented in the literature.
Abstract: Freeze concentration freezes or crystallises the water
molecules out as ice crystals and leaves behind a highly concentrated
solution. In conventional suspension freeze concentration where ice
crystals formed as a suspension in the mother liquor, separation of
ice is difficult. The size of the ice crystals is still very limited which
will require usage of scraped surface heat exchangers, which is very
expensive and accounted for approximately 30% of the capital cost.
This research is conducted using a newer method of freeze
concentration, which is progressive freeze concentration. Ice crystals
were formed as a layer on the designed heat exchanger surface. In
this particular research, a helical structured copper crystallisation
chamber was designed and fabricated. The effect of two operating
conditions on the performance of the newly designed crystallisation
chamber was investigated, which are circulation flowrate and coolant
temperature. The performance of the design was evaluated by the
effective partition constant, K, calculated from the volume and
concentration of the solid and liquid phase. The system was also
monitored by a data acquisition tool in order to see the temperature
profile throughout the process. On completing the experimental
work, it was found that higher flowrate resulted in a lower K, which
translated into high efficiency. The efficiency is the highest at 1000
ml/min. It was also found that the process gives the highest
efficiency at a coolant temperature of -6 °C.
Abstract: In this paper, we use Radial Basis Function Networks
(RBFN) for solving the problem of environmental interference
cancellation of speech signal. We show that the Second Order Thin-
Plate Spline (SOTPS) kernel cancels the interferences effectively.
For make comparison, we test our experiments on two conventional
most used RBFN kernels: the Gaussian and First order TPS (FOTPS)
basis functions. The speech signals used here were taken from the
OGI Multi-Language Telephone Speech Corpus database and were
corrupted with six type of environmental noise from NOISEX-92
database. Experimental results show that the SOTPS kernel can
considerably outperform the Gaussian and FOTPS functions on
speech interference cancellation problem.
Abstract: This paper deals with a high-order accurate Runge
Kutta Discontinuous Galerkin (RKDG) method for the numerical
solution of the wave equation, which is one of the simple case of a
linear hyperbolic partial differential equation. Nodal DG method is
used for a finite element space discretization in 'x' by discontinuous
approximations. This method combines mainly two key ideas which
are based on the finite volume and finite element methods. The
physics of wave propagation being accounted for by means of
Riemann problems and accuracy is obtained by means of high-order
polynomial approximations within the elements. High order accurate
Low Storage Explicit Runge Kutta (LSERK) method is used for
temporal discretization in 't' that allows the method to be nonlinearly
stable regardless of its accuracy. The resulting RKDG
methods are stable and high-order accurate. The L1 ,L2 and L∞ error
norm analysis shows that the scheme is highly accurate and effective.
Hence, the method is well suited to achieve high order accurate
solution for the scalar wave equation and other hyperbolic equations.
Abstract: The angular distribution of Compton scattering of two
quanta originating in the annihilation of a positron with an electron
is investigated as a quantum key distribution (QKD) mechanism in
the gamma spectral range. The geometry of coincident Compton
scattering is observed on the two sides as a way to obtain partially
correlated readings on the quantum channel. We derive the noise
probability density function of a conceptually equivalent prepare
and measure quantum channel in order to evaluate the limits of the
concept in terms of the device secrecy capacity and estimate it at
roughly 1.9 bits per 1 000 annihilation events. The high error rate
is well above the tolerable error rates of the common reconciliation
protocols; therefore, the proposed key agreement protocol by public
discussion requires key reconciliation using classical error-correcting
codes. We constructed a prototype device based on the readily
available monolithic detectors in the least complex setup.
Abstract: In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.
Abstract: Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.
Abstract: Discretization of spatial derivatives is an important
issue in meshfree methods especially when the derivative terms
contain non-linear coefficients. In this paper, various methods used
for discretization of second-order spatial derivatives are investigated
in the context of Smoothed Particle Hydrodynamics. Three popular
forms (i.e. "double summation", "second-order kernel derivation",
and "difference scheme") are studied using one-dimensional unsteady
heat conduction equation. To assess these schemes, transient response
to a step function initial condition is considered. Due to parabolic
nature of the heat equation, one can expect smooth and monotone
solutions. It is shown, however in this paper, that regardless of
the type of kernel function used and the size of smoothing radius,
the double summation discretization form leads to non-physical
oscillations which persist in the solution. Also, results show that when
a second-order kernel derivative is used, a high-order kernel function
shall be employed in such a way that the distance of inflection
point from origin in the kernel function be less than the nearest
particle distance. Otherwise, solutions may exhibit oscillations near
discontinuities unlike the "difference scheme" which unconditionally
produces monotone results.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: In this paper, we propose an improvement of pattern
growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree
framework and separator database to reduce the execution time and
memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result
shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.
Abstract: In non destructive testing by radiography, a perfect
knowledge of the weld defect shape is an essential step to
appreciate the quality of the weld and make decision on its
acceptability or rejection. Because of the complex nature of the
considered images, and in order that the detected defect region
represents the most accurately possible the real defect, the choice
of thresholding methods must be done judiciously. In this paper,
performance criteria are used to conduct a comparative study of
four non parametric histogram thresholding methods for automatic
extraction of weld defect in radiographic images.
Abstract: When the failure function is monotone, some monotonic reliability methods are used to gratefully simplify and facilitate the reliability computations. However, these methods often work in a transformed iso-probabilistic space. To this end, a monotonic simulator or transformation is needed in order that the transformed failure function is still monotone. This note proves at first that the output distribution of failure function is invariant under the transformation. And then it presents some conditions under which the transformed function is still monotone in the newly obtained space. These concern the copulas and the dependence concepts. In many engineering applications, the Gaussian copulas are often used to approximate the real word copulas while the available information on the random variables is limited to the set of marginal distributions and the covariances. So this note catches an importance on the conditional monotonicity of the often used transformation from an independent random vector into a dependent random vector with Gaussian copulas.
Abstract: Mobile ad hoc network is a collection of mobile
nodes communicating through wireless channels without any existing
network infrastructure or centralized administration. Because of the
limited transmission range of wireless network interfaces, multiple
"hops" may be needed to exchange data across the network. In order
to facilitate communication within the network, a routing protocol is
used to discover routes between nodes. The primary goal of such an
ad hoc network routing protocol is correct and efficient route
establishment between a pair of nodes so that messages may be
delivered in a timely manner. Route construction should be done
with a minimum of overhead and bandwidth consumption. This paper
examines two routing protocols for mobile ad hoc networks– the
Destination Sequenced Distance Vector (DSDV), the table- driven
protocol and the Ad hoc On- Demand Distance Vector routing
(AODV), an On –Demand protocol and evaluates both protocols
based on packet delivery fraction, normalized routing load, average
delay and throughput while varying number of nodes, speed and
pause time.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.