Abstract: The development of distributed systems has been affected by the need to accommodate an increasing degree of flexibility, adaptability, and autonomy. The Mobile Agent technology is emerging as an alternative to build a smart generation of highly distributed systems. In this work, we investigate the performance aspect of agent-based technologies for information retrieval. We present a comparative performance evaluation model of Mobile Agents versus Remote Method Invocation by means of an analytical approach. We demonstrate the effectiveness of mobile agents for dynamic code deployment and remote data processing by reducing total latency and at the same time producing minimum network traffic. We argue that exploiting agent-based technologies significantly enhances the performance of distributed systems in the domain of information retrieval.
Abstract: This paper discusses site selection process for
biological soil conservation planning. It was supported by a valuefocused
approach and spatial multi-criteria evaluation techniques. A
first set of spatial criteria was used to design a number of potential
sites. Next, a new set of spatial and non-spatial criteria was
employed, including the natural factors and the financial costs,
together with the degree of suitability for the Bonkuh watershed to
biological soil conservation planning and to recommend the most
acceptable program. The whole process was facilitated by a new
software tool that supports spatial multiple criteria evaluation, or
SMCE in GIS software (ILWIS). The application of this tool,
combined with a continual feedback by the public attentions, has
provided an effective methodology to solve complex decisional
problem in biological soil conservation planning.
Abstract: In this paper, we propose a new architecture for the implementation of the N-point Fast Fourier Transform (FFT), based on the Radix-2 Decimation in Frequency algorithm. This architecture is based on a pipeline circuit that can process a stream of samples and produce two FFT transform samples every clock cycle. Compared to existing implementations the architecture proposed achieves double processing speed using the same circuit complexity.
Abstract: The Yasuj city stream named the Beshar supply
water for different usages such as aquaculture farms , drinking,
agricultural and industrial usages. Fish processing plants
,Agricultural farms, waste water of industrial zones and hospitals
waste water which they are generate by human activity produce a
considerable volume of effluent and when they are released in to the
stream they can effect on the water quality and down stream aquatic
systems. This study was conducted to evaluate the effects of outflow
effluent from different human activity and point and non point
pollution sources on the water quality and health of the Beshar
river next to Yasuj. Yasuj is the biggest and most important city in
the Kohkiloye and Boyerahmad province . The Beshar River is one
of the most important aquatic ecosystems in the upstream of the
Karun watershed in south of Iran which is affected by point and non
point pollutant sources . This study was done in order to evaluate the
effects of human activities on the water quality and health of the
Beshar river. This river is approximately 190 km in length and
situated at the geographical positions of 51° 20' to 51° 48' E and 30°
18' to 30° 52' N it is one of the most important aquatic ecosystems of
Kohkiloye and Boyerahmad province in south-west Iran. In this
research project, five study stations were selected to examine water
pollution in the Beshar River systems. Human activity is now one of
the most important factors affecting on hydrology and water quality
of the Beshar river. Humans use large amounts of resources to sustain
various standards of living, although measures of sustainability are
highly variable depending on how sustainability is defined. The
Beshar river ecosystems are particularly sensitive and vulnerable to
human activities. The water samples were analyzed, then some
important water quality parameters such as pH, dissolve oxygen
(DO), Biochemical Oxygen Demand (BOD5), Chemical Oxygen
Demand (COD), Total Suspended Solids (TDS),Turbidity,
Temperature, Nitrates (NO3) and Phosphates (PO4) were estimated
at the two stations. The results show a downward trend in the water
quality at the down stream of the city. The amounts of
BOD5,COD,TSS,T,Turbidity, NO3 and PO4 in the down stream
stations were considerably more than the station 1. By contrast the
amounts of DO in the down stream stations were less than to the
station 1. However when effluent discharge consequence of human
activities are released into the Beshar river near the city, the quality
of river are decreases and the environmental problems of the river
during the next years are predicted to rise.
Abstract: This paper proposes and analyses the wireless
telecommunication system with multiple antennas to the emission
and reception MIMO (multiple input multiple output) with space
diversity in a OFDM context. In particular it analyses the
performance of a DTT (Digital Terrestrial Television) broadcasting
system that includes MIMO-OFDM techniques. Different
propagation channel models and configurations are considered for
each diversity scheme. This study has been carried out in the context
of development of the next generation DVB-T/H and WRAN.
Abstract: Automated discovery of hierarchical structures in
large data sets has been an active research area in the recent past.
This paper focuses on the issue of mining generalized rules with crisp
hierarchical structure using Genetic Programming (GP) approach to
knowledge discovery. The post-processing scheme presented in this
work uses flat rules as initial individuals of GP and discovers
hierarchical structure. Suitable genetic operators are proposed for the
suggested encoding. Based on the Subsumption Matrix(SM), an
appropriate fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the discovered
hierarchy. Experimental results are presented to demonstrate the
performance of the proposed algorithm.
Abstract: This paper presents a new hardware interface using a
microcontroller which processes audio music signals to standard
MIDI data. A technique for processing music signals by extracting
note parameters from music signals is described. An algorithm to
convert the voice samples for real-time processing without complex
calculations is proposed. A high frequency microcontroller as the
main processor is deployed to execute the outlined algorithm. The
MIDI data generated is transmitted using the EIA-232 protocol. The
analyses of data generated show the feasibility of using
microcontrollers for real-time MIDI generation hardware interface.
Abstract: In this paper, a novel approach is presented
for designing multiplier-free state-space digital filters. The
multiplier-free design is obtained by finding power-of-2 coefficients
and also quantizing the state variables to power-of-2
numbers. Expressions for the noise variance are derived for the
quantized state vector and the output of the filter. A “structuretransformation
matrix" is incorporated in these expressions. It
is shown that quantization effects can be minimized by properly
designing the structure-transformation matrix. Simulation
results are very promising and illustrate the design algorithm.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.
Abstract: The localized corrosion behavior of laser surface
melted 304L austenitic stainless steel was studied by
potentiodynamic polarization test. The extent of improvement in
corrosion resistance was governed by the preferred orientation and
the percentage of delta ferrite present on the surface of the laser
melted sample. It was established by orientation imaging microscopy
that the highest pitting potential value was obtained when grains were
oriented in the most close- packed [101] direction compared to the
random distribution of the base metal and other laser surface melted
samples oriented in [001] direction. The sample with lower
percentage of ferrite had good pitting resistance.
Abstract: As the Computed Tomography(CT) requires normally
hundreds of projections to reconstruct the image, patients are exposed
to more X-ray energy, which may cause side effects such as cancer.
Even when the variability of the particles in the object is very less,
Computed Tomography requires many projections for good quality
reconstruction. In this paper, less variability of the particles in an
object has been exploited to obtain good quality reconstruction.
Though the reconstructed image and the original image have same
projections, in general, they need not be the same. In addition
to projections, if a priori information about the image is known,
it is possible to obtain good quality reconstructed image. In this
paper, it has been shown by experimental results why conventional
algorithms fail to reconstruct from a few projections, and an efficient
polynomial time algorithm has been given to reconstruct a bi-level
image from its projections along row and column, and a known sub
image of unknown image with smoothness constraints by reducing the
reconstruction problem to integral max flow problem. This paper also
discusses the necessary and sufficient conditions for uniqueness and
extension of 2D-bi-level image reconstruction to 3D-bi-level image
reconstruction.
Abstract: In this paper, an artificial neural network simulator is
employed to carry out diagnosis and prognosis on electric motor as
rotating machinery based on predictive maintenance. Vibration data
of the primary failed motor including unbalance, misalignment and
bearing fault were collected for training the neural network. Neural
network training was performed for a variety of inputs and the motor
condition was used as the expert training information. The main
purpose of applying the neural network as an expert system was to
detect the type of failure and applying preventive maintenance. The
advantage of this study is for machinery Industries by providing
appropriate maintenance that has an essential activity to keep the
production process going at all processes in the machinery industry.
Proper maintenance is pivotal in order to prevent the possible failures
in operating system and increase the availability and effectiveness of
a system by analyzing vibration monitoring and developing expert
system.
Abstract: Equations on curved manifolds display interesting properties in a number of ways. In particular, the symmetries and, therefore, the conservation laws reduce depending on how curved the manifold is. Of particular interest are the wave and Gordon-type equations; we study the symmetry properties and conservation laws of these equations on the Milne and Bianchi type III metrics. Properties of reduction procedures via symmetries, variational structures and conservation laws are more involved than on the well known flat (Minkowski) manifold.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.
Abstract: This paper introduces a measure of similarity between
two clusterings of the same dataset produced by two different
algorithms, or even the same algorithm (K-means, for instance, with
different initializations usually produce different results in clustering
the same dataset). We then apply the measure to calculate the
similarity between pairs of clusterings, with special interest directed
at comparing the similarity between various machine clusterings and
human clustering of datasets. The similarity measure thus can be used
to identify the best (in terms of most similar to human) clustering
algorithm for a specific problem at hand. Experimental results
pertaining to the text categorization problem of a Portuguese corpus
(wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The
significance and other potential applications of the proposed measure
are discussed.
Abstract: We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.
Abstract: Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.
Abstract: Growth and mineral nutrient elemental content were
studied in Mokara chark kuan pink terrestrial orchid and wild
Lantana camara weed agroecosystem. The treated subplots were
encircled with L. camara plants and sprayed weekly with L. camara
10% leaf aqueous extract. Allelopathic interactions were possible
through extensive invading root of L. camara plants into the treated
orchid subplots and weekly L. camara leaf aqueous extract
sprayings. Orchid growth was not significantly different in between
the control and treated plots, but chlorosis and yellowish patches of
leaves were observed in control orchid leaves. Nitrogen content in L.
camara leaf was significantly higher than in orchid leaf, the order of
importance of mineral nutrient contents in L. camara leaf was
K>Mg>Na>N. In treated orchid leaf, the order of importance was
N>K>Mg>Na. Orchid leaf N content from the treated plot was
higher than control, but Mg and Na contents were almost similar.
Abstract: Scarcity of water resources and huge costs of
establishing new hydraulic installations necessitate optimal
exploitation from existing reservoirs. Sustainable management and
efficient exploitation from existing finite water resources are
important factors in water resource management, particularly in the
periods of water insufficiency and in dry regions, and on account of
competitive allocations in the view of exploitation management. This
study aims to minimize reservoir water release from a determined
rate of demand. A numerical model for water optimal exploitation
has been developed using GAMS introduced by the World Bank and
applied to the case of Meijaran dam, northern Iran. The results
indicate that this model can optimize the function of reservoir
exploitation while required water for lower parts of the region will be
supplied. Further, allocating optimal water from reservoir, the
optimal rate of water allocated to any group of the users were
specified to increase benefits in curve dam exploitation.
Abstract: Exact expressions for bit-error probability (BEP) for
coherent square detection of uncoded and coded M-ary quadrature
amplitude modulation (MQAM) using an array of antennas with
maximal ratio combining (MRC) in a flat fading channel interference
limited system in a Nakagami-m fading environment is derived. The
analysis assumes an arbitrary number of independent and identically
distributed Nakagami interferers. The results for coded MQAM are
computed numerically for the case of (24,12) extended Golay code
and compared with uncoded MQAM by plotting error probabilities
versus average signal-to-interference ratio (SIR) for various values of
order of diversity N, number of distinct symbols M, in order to
examine the effect of cochannel interferers on the performance of the
digital communication system. The diversity gains and net gains are
also presented in tabular form in order to examine the performance of
digital communication system in the presence of interferers, as the
order of diversity increases. The analytical results presented in this
paper are expected to provide useful information needed for design
and analysis of digital communication systems with space diversity
in wireless fading channels.