Abstract: The number of features required to represent an image
can be very huge. Using all available features to recognize objects
can suffer from curse dimensionality. Feature selection and
extraction is the pre-processing step of image mining. Main issues in
analyzing images is the effective identification of features and
another one is extracting them. The mining problem that has been
focused is the grouping of features for different shapes. Experiments
have been conducted by using shape outline as the features. Shape
outline readings are put through normalization and dimensionality
reduction process using an eigenvector based method to produce a
new set of readings. After this pre-processing step data will be
grouped through their shapes. Through statistical analysis, these
readings together with peak measures a robust classification and
recognition process is achieved. Tests showed that the suggested
methods are able to automatically recognize objects through their
shapes. Finally, experiments also demonstrate the system invariance
to rotation, translation, scale, reflection and to a small degree of
distortion.
Abstract: This study deals with evaluation of influence of salinity (NaCl) onto equilibrium of Cu and Ni removal from aqueous solutions by natural sorbent – zeolite. Equilibrium data were obtained by batch experiments. The salinity of the aqueous solution was influenced by dissolving NaCl in distilled water. It was studied in the range of NaCl concentrations from 1 g.l-1 to 100g.l-1. For Cu sorption there is a significant influence of salinity. The maximum capacity of zeolite for Cu was decreasing with growing concentration of NaCl. For Ni sorption there is not so significant influence of salinity as for Cu. The maximum capacity of zeolite for Ni was slightly decreasing with growing concentration of NaCl.
Abstract: Biological Ammonia removal (nitrification), the
oxidation of ammonia to nitrate catalyzed by bacteria, is a key part of
global nitrogen cycling. In the first step of nitrification,
chemolithoautotrophic ammonia oxidizer transform ammonia to
nitrite, this subsequently oxidized to nitrate by nitrite oxidizing
bacteria. This process can be affected by several factors. In this study
the effect of influent COD on biological ammonia removal in a
bench-scale biological reactor was investigated. Experiments were
carried out using synthetic wastewater. The initial ammonium
concentration was 25mgNH4
+-N L-1. The effect of COD between
247.55±1.8 and 601.08±3.24mgL-1 on biological ammonia removal
was investigated by varying the COD loading supplied to reactor.
From the results obtained in this study it could be concluded in the
range of 247.55±1.8 to 351.35±2.05mgL-1, there is a direct
relationship between amount of COD and ammonia removal.
However more than 351.35±2.05 up to 601.08±3.24mgL-1 were
found an indirect relationship between them.
Abstract: This paper presents a dynamic adaptation scheme for
the frequency of inter-deme migration in distributed genetic algorithms
(GA), and its VLSI hardware design. Distributed GA,
or multi-deme-based GA, uses multiple populations which evolve
concurrently. The purpose of dynamic adaptation is to improve
convergence performance so as to obtain better solutions. Through
simulation experiments, we proved that our scheme achieves better
performance than fixed frequency migration schemes.
Abstract: Undular hydraulic jumps are illustrated by a smooth
rise of the free surface followed by a train of stationary waves. They
are sometimes experienced in natural waterways and rivers. The
characteristics of undular hydraulic jumps are studied here. The
height, amplitude and the main characteristics of undular jump is
depended on the upstream Froude number and aspect ratio. The
experiments were done on the smooth bed flume. These results
compared with other researches and the main characteristics of the
undular hydraulic jump were studied in this article.
Abstract: Pharmaceutical industries and effluents of sewage treatment plants are the main sources of residual pharmaceuticals in water resources. These emergent pollutants may adversely impact the biophysical environment. Pharmaceutical industries often generate wastewater that changes in characteristics and quantity depending on the used manufacturing processes. Carbamazepine (CBZ), {5Hdibenzo [b,f]azepine-5-carboxamide, (C15H12N2O)}, is a significant non-biodegradable pharmaceutical contaminant in the Jordanian pharmaceutical wastewater, which is not removed by the activated sludge processes in treatment plants. Activated carbon may potentially remove that pollutant from effluents, but the high cost involved suggests that more attention should be given to the potential use of low-cost materials in order to reduce cost and environmental contamination. Powders of Jordanian non-metallic raw materials namely, Azraq Bentonite (AB), Kaolinite (K), and Zeolite (Zeo) were activated (acid and thermal treatment) and evaluated by removing CBZ. The results of batch and column techniques experiments showed around 46% and 67% removal of CBZ respectively.
Abstract: The belief K-modes method (BKM) approach is a new
clustering technique handling uncertainty in the attribute values of
objects in both the cluster construction task and the classification one.
Like the standard version of this method, the BKM results depend on
the chosen initial modes. So, one selection method of initial modes
is developed, in this paper, aiming at improving the performances of
the BKM approach. Experiments with several sets of real data show
that by considered the developed selection initial modes method, the
clustering algorithm produces more accurate results.
Abstract: For more than 120 years, gold mining formed the
backbone the South Africa-s economy. The consequence of mine
closure was observed in large-scale land degradation and widespread
pollution of surface water and groundwater. This paper investigates
the feasibility of using natural zeolite in removing heavy metals
contaminating the Wonderfonteinspruit Catchment Area (WCA), a
water stream with high levels of heavy metals and radionuclide
pollution. Batch experiments were conducted to study the adsorption
behavior of natural zeolite with respect to Fe2+, Mn2+, Ni2+, and Zn2+.
The data was analysed using the Langmuir and Freudlich isotherms.
Langmuir was found to correlate the adsorption of Fe2+, Mn2+, Ni2+,
and Zn2+ better, with the adsorption capacity of 11.9 mg/g, 1.2 mg/g,
1.3 mg/g, and 14.7 mg/g, respectively. Two kinetic models namely,
pseudo-first order and pseudo second order were also tested to fit the
data. Pseudo-second order equation was found to be the best fit for
the adsorption of heavy metals by natural zeolite. Zeolite
functionalization with humic acid increased its uptake ability.
Abstract: This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.
Abstract: Modeling of the dynamic behavior and motion are
renewed interest in the improved tractive performance of an
intelligent air-cushion tracked vehicle (IACTV). This paper presents
a new dynamical model for the forces on the developed small scale
intelligent air-cushion tracked vehicle moving over swamp peat. The
air cushion system partially supports the 25 % of vehicle total weight
in order to make the vehicle ground contact pressure 7 kN/m2. As the
air-cushion support system can adjust automatically on the terrain, so
the vehicle can move over the terrain without any risks. The springdamper
system is used with the vehicle body to control the aircushion
support system on any undulating terrain by making the
system sinusoidal form. Experiments have been carried out to
investigate the relationships among tractive efficiency, slippage,
traction coefficient, load distribution ratio, tractive effort, motion
resistance and power consumption in given terrain conditions.
Experiment and simulation results show that air-cushion system
improves the vehicle performance by keeping traction coefficient of
71% and tractive efficiency of 62% and the developed model can
meet the demand of transport efficiency with the optimal power
consumption.
Abstract: In order to evaluation the effects of soil organic
matter and biofertilizer on chickpea quality and biological
nitrogen fixation, field experiments were carried out in 2007
and 2008 growing seasons. In this research the effects of
different strategies for soil fertilization were investigated on
grain yield and yield component, minerals, organic compounds
and cooking time of chickpea. Experimental units were
arranged in split-split plots based on randomized complete
blocks with three replications. Main plots consisted of (G1):
establishing a mixed vegetation of Vicia panunica and
Hordeum vulgare and (G2): control, as green manure levels.
Also, five strategies for obtaining the base fertilizer
requirement including (N1): 20 t.ha-1 farmyard manure; (N2):
10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate;
(N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5):
10 t.ha-1 farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1
triple super phosphate were considered in sub plots.
Furthermoree four levels of biofertilizers consisted of (B1):
Bacillus lentus + Pseudomonas putida; (B2): Trichoderma
harzianum; (B3): Bacillus lentus + Pseudomonas putida +
Trichoderma harzianum; and (B4): control (without
biofertilizers) were arranged in sub-sub plots. Results showed
that integrating biofertilizers (B3) and green manure (G1)
produced the highest grain yield. The highest amounts of yield
were obtained in G1×N5 interaction. Comparison of all 2-way
and 3-way interactions showed that G1N5B3 was determined
as the superior treatment. Significant increasing of N, P2O5,
K2O, Fe and Mg content in leaves and grains emphasized on
superiority of mentioned treatment because each one of these
nutrients has an approved role in chlorophyll synthesis and
photosynthesis abilities of the crops. The combined application
of compost, farmyard manure and chemical phosphorus (N5)
in addition to having the highest yield, had the best grain
quality due to high protein, starch and total sugar contents, low
crude fiber and reduced cooking time.
Abstract: DNA shuffling is a powerful method used for in vitro
evolute molecules with specific functions and has application in areas
such as, for example, pharmaceutical, medical and agricultural
research. The success of such experiments is dependent on a variety
of parameters and conditions that, sometimes, can not be properly
pre-established. Here, two computational models predicting DNA
shuffling results is presented and their use and results are evaluated
against an empirical experiment. The in silico and in vitro results
show agreement indicating the importance of these two models and
motivating the study and development of new models.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Abstract: This paper applies Bayesian Networks to support
information extraction from unstructured, ungrammatical, and
incoherent data sources for semantic annotation. A tool has been
developed that combines ontologies, machine learning, and
information extraction and probabilistic reasoning techniques to
support the extraction process. Data acquisition is performed with the
aid of knowledge specified in the form of ontology. Due to the
variable size of information available on different data sources, it is
often the case that the extracted data contains missing values for
certain variables of interest. It is desirable in such situations to
predict the missing values. The methodology, presented in this paper,
first learns a Bayesian network from the training data and then uses it
to predict missing data and to resolve conflicts. Experiments have
been conducted to analyze the performance of the presented
methodology. The results look promising as the methodology
achieves high degree of precision and recall for information
extraction and reasonably good accuracy for predicting missing
values.
Abstract: The POD-assisted projective integration method based on the equation-free framework is presented in this paper. The method is essentially based on the slow manifold governing of given system. We have applied two variants which are the “on-line" and “off-line" methods for solving the one-dimensional viscous Bergers- equation. For the on-line method, we have computed the slow manifold by extracting the POD modes and used them on-the-fly along the projective integration process without assuming knowledge of the underlying slow manifold. In contrast, the underlying slow manifold must be computed prior to the projective integration process for the off-line method. The projective step is performed by the forward Euler method. Numerical experiments show that for the case of nonperiodic system, the on-line method is more efficient than the off-line method. Besides, the online approach is more realistic when apply the POD-assisted projective integration method to solve any systems. The critical value of the projective time step which directly limits the efficiency of both methods is also shown.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: The common bean is the most important grain legume for direct human consumption in the world and BCMV is one of the world's most serious bean diseases that can reduce yield and quality of harvested product. To determine the best tolerance index to BCMV and recognize tolerant genotypes, 2 experiments were conducted in field conditions. Twenty five common bean genotypes were sown in 2 separate RCB design with 3 replications under contamination and non-contamination conditions. On the basis of the results of indices correlations GMP, MP and HARM were determined as the most suitable tolerance indices. The results of principle components analysis indicated 2 first components totally explained 98.52% of variations among data. The first and second components were named potential yield and stress susceptible respectively. Based on the results of BCMV tolerance indices assessment and biplot analysis WA8563-4, WA8563-2 and Cardinal were the genotypes that exhibited potential seed yield under contamination and noncontamination conditions.
Abstract: Nanostructured Iron Oxide with different
morphologies of rod-like and granular have been suc-cessfully
prepared via a solid-state reaction in the presence of NaCl, NaBr, NaI
and NaN3, respectively. The added salts not only prevent a drastic
increase in the size of the products but also provide suitable
conditions for the oriented growth of primary nanoparticles. The
formation mechanisms of these materials by solid-state reaction at
ambient temperature are proposed. The photocatalytic experiments
for congo red (CR) have demonstrated that the mixture of α-Fe2O3
and Fe3O4 nanostructures were more efficient than α-Fe2O3
nanostructures.
Abstract: In this paper, we generalize several techniques in
developing Fault Tolerant Software. We introduce property
“Correctness" in evaluating N-version Systems and compare it to
some commonly used properties such as reliability or availability.
We also find out the relation between this property and the number of
versions of system. Our experiments to verify the correctness and the
applicability of the relation are also presented.
Abstract: In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.