Abstract: This analysis investigates the distortion of flow
measurement and the increase of cavitation along orifice
flowmeter. The analysis using the numerical method (CFD)
validated the distortion of flow measurement through the inlet
velocity profile considering the convergence and grid
dependency. Realizable k-e model was selected and y+ was
about 50 in this numerical analysis. This analysis also estimated
the vulnerability of cavitation effect due to inlet velocity profile.
The investigation concludes that inclined inlet velocity profile
could vary the pressure which was measured at pressure tab
near pipe wall and it led to distort the pressure values ranged
from -3.8% to 5.3% near the orifice plate and to make the
increase of cavitation. The investigation recommends that the
fully developed inlet velocity flow is beneficial to accurate flow
measurement in orifice flowmeter.
Abstract: Understanding of how and where NOx formation
occurs in industrial burner is very important for efficient and clean
operation of utility burners. Also the importance of this problem is
mainly due to its relation to the pollutants produced by more burners
used widely of gas turbine in thermal power plants and glass and steel
industry.
In this article, a numerical model of an industrial burner operating
in MILD combustion is validated with experimental data.. Then
influence of air flow rate and air temperature on combustor
temperature profiles and NOX product are investigated. In order to
modification this study reports on the effects of fuel and air dilution
(with inert gases H2O, CO2, N2), and also influence of lean-premixed
of fuel, on the temperature profiles and NOX emission.
Conservation equations of mass, momentum and energy, and
transport equations of species concentrations, turbulence, combustion
and radiation modeling in addition to NO modeling equations were
solved together to present temperature and NO distribution inside the
burner.
The results shows that dilution, cause to a reduction in value of
temperature and NOX emission, and suppresses any flame
propagation inside the furnace and made the flame inside the furnace
invisible. Dilution with H2O rather than N2 and CO2 decreases further
the value of the NOX. Also with raise of lean-premix level, local
temperature of burner and the value of NOX product are decreases
because of premixing prevents local “hot spots" within the combustor
volume that can lead to significant NOx formation. Also leanpremixing
of fuel with air cause to amount of air in reaction zone is
reach more than amount that supplied as is actually needed to burn
the fuel and this act lead to limiting NOx formation
Abstract: A new numerical method for solving the twodimensional,
steady, incompressible, viscous flow equations on a
Curvilinear staggered grid is presented in this paper. The proposed
methodology is finite difference based, but essentially takes
advantage of the best features of two well-established numerical
formulations, the finite difference and finite volume methods. Some
weaknesses of the finite difference approach are removed by
exploiting the strengths of the finite volume method. In particular,
the issue of velocity-pressure coupling is dealt with in the proposed
finite difference formulation by developing a pressure correction
equation in a manner similar to the SIMPLE approach commonly
used in finite volume formulations. However, since this is purely a
finite difference formulation, numerical approximation of fluxes is
not required. Results obtained from the present method are based on
the first-order upwind scheme for the convective terms, but the
methodology can easily be modified to accommodate higher order
differencing schemes.
Abstract: Automatic keyphrase extraction is useful in efficiently
locating specific documents in online databases. While several
techniques have been introduced over the years, improvement on
accuracy rate is minimal. This research examines attribute scores for
author-supplied keyphrases to better understand how the scores affect
the accuracy rate of automatic keyphrase extraction. Five attributes
are chosen for examination: Term Frequency, First Occurrence, Last
Occurrence, Phrase Position in Sentences, and Term Cohesion
Degree. The results show that First Occurrence is the most reliable
attribute. Term Frequency, Last Occurrence and Term Cohesion
Degree display a wide range of variation but are still usable with
suggested tweaks. Only Phrase Position in Sentences shows a totally
unpredictable pattern. The results imply that the commonly used
ranking approach which directly extracts top ranked potential phrases
from candidate keyphrase list as the keyphrases may not be reliable.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.
Abstract: Distributed Computing Systems are usually considered the most suitable model for practical solutions of many parallel algorithms. In this paper an enhanced distributed system is presented to improve the time complexity of Binary Indexed Trees (BIT). The proposed system uses multi-uniform processors with identical architectures and a specially designed distributed memory system. The analysis of this system has shown that it has reduced the time complexity of the read query to O(Log(Log(N))), and the update query to constant complexity, while the naive solution has a time complexity of O(Log(N)) for both queries. The system was implemented and simulated using VHDL and Verilog Hardware Description Languages, with xilinx ISE 10.1, as the development environment and ModelSim 6.1c, similarly as the simulation tool. The simulation has shown that the overhead resulting by the wiring and communication between the system fragments could be fairly neglected, which makes it applicable to practically reach the maximum speed up offered by the proposed model.
Abstract: The present paper deals with the experimental and
computational study of axial collapse of the aluminum metallic shells
having combined tube-frusta geometry between two parallel plates.
Shells were having bottom two third lengths as frusta and remaining
top one third lengths as tube. Shells were compressed to recognize
their modes of collapse and associated energy absorption capability.
An axisymmetric Finite Element computational model of collapse
process is presented and analysed, using a non-linear FE code
FORGE2. Six noded isoparametric triangular elements were used to
discretize the deforming shell. The material of the shells was
idealized as rigid visco-plastic. To validate the computational model
experimental and computed results of the deformed shapes and their
corresponding load-compression and energy-compression curves
were compared. With the help of the obtained results progress of the
axisymmetric mode of collapse has been presented, analysed and
discussed.
Abstract: This study shows the effect of carbon towards
molybdenum carbide alloy when exposed to Microwave. This
technique is also known as Microwave Induced Alloying (MIA) for
the preparation of molybdenum carbide. In this study ammonium
heptamolybdate solution and carbon black powder were
heterogeneously mixed and exposed to microwave irradiation for 2
minutes. The effect on amount of carbon towards the produced alloy
on morphological and oxidation states changes during microwave is
presented. In this experiment, it is expected carbon act as a reducing
agent with the ratio 2:7 molybdenum to carbon as the optimum for
the production of molybdenum carbide alloy. All the morphological
transformations and changes in this experiment were followed and
characterized using X-Ray Diffraction and FESEM.
Abstract: Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
observed.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: Risk Assessment Tool (RAT) is an expert system that
assesses, monitors, and gives preliminary treatments automatically
based on the project plan. In this paper, a review was taken out for
the current project time management risk assessment tools for SME
software development projects, analyze risk assessment parameters,
conditions, scenarios, and finally propose risk assessment tool (RAT)
model to assess, treat, and monitor risks. An implementation prototype
system is developed to validate the model.
Abstract: In order to enhance the knowledge of certain
phytochemical Algerian plants that are widely used in traditional
medicine and to exploit their therapeutic potential in modern
medicine, we have done a specific extraction of terpenes and
alkaloids from the leaves of Euphorbia granulata to evaluate the
antioxidant and antibacterial activity of this extracts. After the
extraction it was found that the terpene extract gave the highest yield
59.72% compared with alkaloids extracts.
The disc diffusion method was used to determine the antibacterial
activity against different bacterial strains: Escherichia coli
(ATCC25922), Pseudomonas aeruginosa (ATCC27853) and
Staphylococcus aureus (ATCC25923). All extracts have shown
inhibition of growth bacteria. The different zones of inhibition have
varied from (7 -10 mm) according to the concentrations of extract
used.
Testing the antiradical activity on DPPH-TLC plates indicated the
presence of substances that have potent anti-free radical. As against,
the BC-TLC revealed that only terpenes extract which was reacted
positively. These results can validate the importance of Euphorbia
granulata in traditional medicine.
Abstract: This study assesses the vulnerability of Bulgarian
agriculture to drought using the WINISAREG model and seasonal
standard precipitation index SPI(2) for the period 1951-2004. This
model was previously validated for maize on soils of different water
holding capacity (TAW) in various locations. Simulations are
performed for Plovdiv, Stara Zagora and Sofia. Results relative to
Plovdiv show that in soils of large TAW (180 mm m-1) net irrigation
requirements (NIRs) range 0-40 mm in wet years and 350-380 mm in
dry years. In soils of small TAW (116 mm m-1), NIRs reach 440 mm
in the very dry year. NIRs in Sofia are about 80 mm smaller. Rainfed
maize is associated with great yield variability (29%
Abstract: Many supervised induction algorithms require discrete
data, even while real data often comes in a discrete
and continuous formats. Quality discretization of continuous
attributes is an important problem that has effects on speed,
accuracy and understandability of the induction models. Usually,
discretization and other types of statistical processes are applied
to subsets of the population as the entire population is practically
inaccessible. For this reason we argue that the discretization
performed on a sample of the population is only an estimate of
the entire population. Most of the existing discretization methods,
partition the attribute range into two or several intervals using
a single or a set of cut points. In this paper, we introduce a
technique by using resampling (such as bootstrap) to generate
a set of candidate discretization points and thus, improving the
discretization quality by providing a better estimation towards
the entire population. Thus, the goal of this paper is to observe
whether the resampling technique can lead to better discretization
points, which opens up a new paradigm to construction of
soft decision trees.
Abstract: This paper presents parametric probability density
models for call holding times (CHTs) into emergency call center
based on the actual data collected for over a week in the public
Emergency Information Network (EIN) in Mongolia. When the set of
chosen candidates of Gamma distribution family is fitted to the call
holding time data, it is observed that the whole area in the CHT
empirical histogram is underestimated due to spikes of higher
probability and long tails of lower probability in the histogram.
Therefore, we provide the Gaussian parametric model of a mixture of
lognormal distributions with explicit analytical expressions for the
modeling of CHTs of PSNs. Finally, we show that the CHTs for
PSNs are fitted reasonably by a mixture of lognormal distributions
via the simulation of expectation maximization algorithm. This result
is significant as it expresses a useful mathematical tool in an explicit
manner of a mixture of lognormal distributions.
Abstract: The most widely used semiconductor memory types
are the Dynamic Random Access Memory (DRAM) and Static
Random Access memory (SRAM). Competition among memory
manufacturers drives the need to decrease power consumption and
reduce the probability of read failure. A technology that is relatively
new and has not been explored is the FinFET technology. In this
paper, a single cell Schmitt Trigger Based Static RAM using FinFET
technology is proposed and analyzed. The accuracy of the result is
validated by means of HSPICE simulations with 32nm FinFET
technology and the results are then compared with 6T SRAM using
the same technology.
Abstract: Existing experiences indicate that one of the most
prominent reasons that some ERP implementations fail is related to
selecting an improper ERP package. Among those important factors
resulting in inappropriate ERP selections, one is to ignore preliminary
activities that should be done before the evaluation of ERP packages.
Another factor yielding these unsuitable selections is that usually
organizations employ prolonged and costly selection processes in
such extent that sometimes the process would never be finalized
or sometimes the evaluation team might perform many key final
activities in an incomplete or inaccurate way due to exhaustion, lack
of interest or out-of-date data. In this paper, a systematic approach
that recommends some activities to be done before and after the
main selection phase is introduced for choosing an ERP package. On
the other hand, the proposed approach has utilized some ideas that
accelerates the selection process at the same time that reduces the
probability of an erroneous final selection.
Abstract: With constraints on data availability and for study of power system stability it is adequate to model the synchronous generator with field circuit and one equivalent damper on q-axis known as the model 1.1. This paper presents a systematic procedure for modelling and simulation of a single-machine infinite-bus power system installed with a thyristor controlled series compensator (TCSC) where the synchronous generator is represented by model 1.1, so that impact of TCSC on power system stability can be more reasonably evaluated. The model of the example power system is developed using MATLAB/SIMULINK which can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, the parameters of the TCSC controller are optimized using genetic algorithm. The non-linear simulation results are presented to validate the effectiveness of the proposed approach.
Abstract: The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.
Abstract: To date, theoretical studies concerning the Carbon
Fiber Reinforced Polymer (CFRP) strengthening of RC beams with
openings have been rather limited. In addition, various numerical
analyses presented so far have effectively simulated the behaviour of
solid beam strengthened by FRP material. In this paper, a two
dimensional nonlinear finite element analysis is presented to validate
against the laboratory test results of six RC beams. All beams had the
same rectangular cross-section geometry and were loaded under four
point bending. The crack pattern results of the finite element model
show good agreement with the crack pattern of the experimental
beams. The load midspan deflection curves of the finite element
models exhibited a stiffer result compared to the experimental beams.
The possible reason may be due to the perfect bond assumption used
between the concrete and steel reinforcement.