Abstract: In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Abstract: The performance and the plasma created by a pulsed
magnetoplasmadynamic thruster for small satellite application is
studied to understand better the ablation and plasma propagation
processes occurring during the short-time discharge. The results can
be applied to improve the quality of the thruster in terms of efficiency,
and to tune the propulsion system to the needs required by the satellite
mission. Therefore, plasma measurements with a high-speed camera
and induction probes, and performance measurements of mass bit
and impulse bit were conducted. Values for current sheet propagation
speed, mean exhaust velocity and thrust efficiency were derived from
these experimental data. A maximum in current sheet propagation
was found by the high-speed camera measurements for a medium
energy input and confirmed by the induction probes. A quasilinear
tendency between the mass bit and the energy input, the current
action integral respectively, was found, as well as a linear tendency
between the created impulse and the discharge energy. The highest
mean exhaust velocity and thrust efficiency was found for the highest
energy input.
Abstract: This paper proposes a method, combining color and layout features, for identifying documents captured from low-resolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. Our identification method first uses the color information in the documents in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining of the search space.
Abstract: Design and modeling of nonlinear systems require the
knowledge of all inside acting parameters and effects. An empirical
alternative is to identify the system-s transfer function from input and
output data as a black box model. This paper presents a procedure
using least squares algorithm for the identification of a feed drive
system coefficients in time domain using a reduced model based on
windowed input and output data. The command and response of the
axis are first measured in the first 4 ms, and then least squares are
applied to predict the transfer function coefficients for this
displacement segment. From the identified coefficients, the next
command response segments are estimated. The obtained results
reveal a considerable potential of least squares method to identify the
system-s time-based coefficients and predict accurately the command
response as compared to measurements.
Abstract: The paper presents a simple and an accurate formula
that has been developed for the conduction angle (δ) of a single
phase half-wave or full-wave controlled rectifier with RL load. This
formula can be also used for calculating the conduction angle (δ) in
case of A.C. voltage regulator with inductive load under
discontinuous current mode. The simulation results shows that the
conduction angle calculated from the developed formula agree very
well with that obtained from the exact solution arrived from the
iterative method. Applying the developed formula can reduce the
computational time and reduce the time for manual classroom
calculation. In addition, the proposed formula is attractive for real
time implementations.
Abstract: To investigate the energy performance of solar shading devices, this paper carried out a survey on the current status of solar shading utilization in buildings in Ningbo and performed building simulations to evaluate the energy savings potential by adopting different solar shading devices. Results show that solar shading utilization in this area is not popular and effective, and should be considered firstly in the design stage since the potential for energy savings is up to 6.8% for residential buildings and 9.4% for commercial buildings.
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: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: As the gradual increase of the enterprise scale, the
firms may possess many manufacturing plants located in different
places geographically. This change will result in the multi-site
production planning problems under the environment of multiple
plants or production resources. Our research proposes the structural
framework to analyze the multi-site planning problems. The analytical
framework is composed of six elements: multi-site conceptual model,
product structure (bill of manufacturing), production strategy,
manufacturing capability and characteristics, production planning
constraints, and key performance indicators. As well as the discussion
of these six ingredients, we also review related literatures in this paper
to match our analytical framework. Finally we take a real-world
practical example of a TFT-LCD manufacturer in Taiwan to explain
our proposed analytical framework for the multi-site production
planning problems.
Abstract: In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.
Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.
Abstract: This paper addresses the problem of the partial state
feedback stabilization of a class of nonlinear systems. In order to
stabilization this class systems, the especial place of this paper is
to reverse designing the state feedback control law from the method
of judging system stability with the center manifold theory. First of
all, the center manifold theory is applied to discuss the stabilization
sufficient condition and design the stabilizing state control laws for a
class of nonlinear. Secondly, the problem of partial stabilization for a
class of plane nonlinear system is discuss using the lyapunov second
method and the center manifold theory. Thirdly, we investigate specially
the problem of the stabilization for a class of homogenous plane
nonlinear systems, a class of nonlinear with dual-zero eigenvalues and
a class of nonlinear with zero-center using the method of lyapunov
function with homogenous derivative, specifically. At the end of this
paper, some examples and simulation results are given show that the
approach of this paper to this class of nonlinear system is effective
and convenient.
Abstract: The equilibrium, thermodynamics and kinetics of the
biosorption of Cd (II) and Pb(II) by a Spore Forming Bacillus (MGL
75) were investigated at different experimental conditions. The
Langmuir and Freundlich, and Dubinin-Radushkevich (D-R)
equilibrium adsorption models were applied to describe the
biosorption of the metal ions by MGL 75 biomass. The Langmuir
model fitted the equilibrium data better than the other models.
Maximum adsorption capacities q max for lead (II) and cadmium (II)
were found equal to 158.73mg/g and 91.74 mg/g by Langmuir model.
The values of the mean free energy determined with the D-R equation
showed that adsorption process is a physiosorption process. The
thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°),
and entropy (ΔS°) changes were also calculated, and the values
indicated that the biosorption process was exothermic and
spontaneous. Experiment data were also used to study biosorption
kinetics using pseudo-first-order and pseudo-second-order kinetic
models. Kinetic parameters, rate constants, equilibrium sorption
capacities and related correlation coefficients were calculated and
discussed. The results showed that the biosorption processes of both
metal ions followed well pseudo-second-order kinetics.
Abstract: This frame work describes a computationally more
efficient and adaptive threshold estimation method for image
denoising in the wavelet domain based on Generalized Gaussian
Distribution (GGD) modeling of subband coefficients. In this
proposed method, the choice of the threshold estimation is carried out
by analysing the statistical parameters of the wavelet subband
coefficients like standard deviation, arithmetic mean and geometrical
mean. The noisy image is first decomposed into many levels to
obtain different frequency bands. Then soft thresholding method is
used to remove the noisy coefficients, by fixing the optimum
thresholding value by the proposed method. Experimental results on
several test images by using this method show that this method yields
significantly superior image quality and better Peak Signal to Noise
Ratio (PSNR). Here, to prove the efficiency of this method in image
denoising, we have compared this with various denoising methods
like wiener filter, Average filter, VisuShrink and BayesShrink.
Abstract: This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation.
Abstract: Selection of the best possible set of suppliers has a
significant impact on the overall profitability and success of any
business. For this reason, it is usually necessary to optimize all
business processes and to make use of cost-effective alternatives for
additional savings. This paper proposes a new efficient context-aware
supplier selection model that takes into account possible changes of
the environment while significantly reducing selection costs. The
proposed model is based on data clustering techniques while
inspiring certain principles of online algorithms for an optimally
selection of suppliers. Unlike common selection models which re-run
the selection algorithm from the scratch-line for any decision-making
sub-period on the whole environment, our model considers the
changes only and superimposes it to the previously defined best set
of suppliers to obtain a new best set of suppliers. Therefore, any recomputation
of unchanged elements of the environment is avoided
and selection costs are consequently reduced significantly. A
numerical evaluation confirms applicability of this model and proves
that it is a more optimal solution compared with common static
selection models in this field.
Abstract: In the present work we report a gram negative
bacterial isolate, from soil of a dye industry, with promising
biorefining and bioremediation potential. This isolate (GBS.5) could
utilize carbazole (nitrogen containing polycyclic aromatic
hydrocarbon) as the sole source of nitrogen and carbon and utilize
almost 98% of 3mM carbazole in 100 hours. The specific activity of
our GBS.5 isolate for carbazole degradation at 30°C and pH 7.0 was
found to be 11.36 μmol/min/g dry cell weight as compared to 10.4
μmol/min/g dry cell weight, the highest reported specific activity till
date. The presence of car genes (the genes involved in
denitrogenation of carbazole) was confirmed through PCR
amplification.
Abstract: This study determines the effect of naked and heparinbased
super-paramagnetic iron oxide nanoparticles on the human
cancer cell lines of A2780. Doxorubicin was used as the anticancer
drug, entrapped in the SPIO-NPs. This study aimed to decorate
nanoparticles with heparin, a molecular ligand for 'active' targeting
of cancerous cells and the application of modified-nanoparticles in
cancer treatment. The nanoparticles containing the anticancer drug
DOX were prepared by a solvent evaporation and emulsification
cross-linking method. The physicochemical properties of the
nanoparticles were characterized by various techniques, and uniform
nanoparticles with an average particle size of 110±15 nm with high
encapsulation efficiencies (EE) were obtained. Additionally, a
sustained release of DOX from the SPIO-NPs was successful.
Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell
toxicity than the individual HP and confocal microscopy analysis
confirmed excellent cellular uptake efficiency. These results indicate
that HP based SPIO-NPs have potential uses as anticancer drug
carriers and also have an enhanced anticancer effect.
Abstract: This paper features the modeling and design of a Fast
Output Sampling (FOS) Feedback control technique for the Active
Vibration Control (AVC) of a smart flexible aluminium cantilever
beam for a Single Input Single Output (SISO) case. Controllers are
designed for the beam by bonding patches of piezoelectric layer as
sensor / actuator to the master structure at different locations along
the length of the beam by retaining the first 2 dominant vibratory
modes. The entire structure is modeled in state space form using the
concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite
Element Method (FEM) and the state space techniques by dividing
the structure into 3, 4, 5 finite elements, thus giving rise to three
types of systems, viz., system 1 (beam divided into 3 finite
elements), system 2 (4 finite elements), system 3 (5 finite elements).
The effect of placing the sensor / actuator at various locations along
the length of the beam for all the 3 types of systems considered is
observed and the conclusions are drawn for the best performance and
for the smallest magnitude of the control input required to control the
vibrations of the beam. Simulations are performed in MATLAB. The
open loop responses, closed loop responses and the tip displacements
with and without the controller are obtained and the performance of
the proposed smart system is evaluated for vibration control.
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 purpose of this study is to identify ideal urban
design elements of waterfronts and to analyze the differences in users-
cognition among these elements. This study follows three steps as
following: first is identifying the urban design elements of waterfronts
from literature review and second is evaluating intended users-
cognition of urban design elements in urban waterfronts. Lastly, third
is analyzing the users- cognition differences. As the result, evaluations
of waterfront areas by users show similar features that non-waterfront
urban design elements contain the highest degree of importance. This
indicates the difference of users- cognition has dimensions of
frequency and distance, and demonstrates differences in the aspect of
importance than of satisfaction. Multi-Dimensional Scaling Method
verifies differences among their cognition. This study provides
elements to increase satisfaction of users from differences of their
cognition on design elements for waterfronts. It also suggests
implications on elements when waterfronts are built.