Abstract: Natural gas is defined as gas obtained from a natural underground reservoir. It generally contains a large quantity of methane along with heavier hydrocarbons such as ethane, propane, isobutene, normal butane; also in the raw state it often contains a considerable amount of non hydrocarbons, such as nitrogen and the acid gases (carbon dioxide and hydrogen sulfide). The acid gases must be removed from natural gas before use. One of the processes witch are use in the industry to remove the acid gases from natural gas is the use of alkanolamine process. In this present paper, a simulation study for an industrial gas sweetening plant has been investigated. The aim of the study is to investigate the effect of using mixing amines as solvent on the gas treatment process using the software Hysys.
Abstract: The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. Biodiesel is a renewable, domestically produced fuel that has been shown to reduce particulate, hydrocarbon, and carbon monoxide emissions from combustion. In the present study an experimental investigation on emission characteristic of a liquid burner system operating on several percentage of biodiesel and gas oil is carried out. Samples of exhaust gas are analysed with Testo 350 Xl. The results show that biodiesel can lower some pollutant such as CO, CO2 and particulate matter emissions while NOx emission would increase in comparison with gas oil. The results indicate there may be benefits to using biodiesel in industrial processes.
Abstract: The motivation of this work was to find a suitable 3D
scanner for human body parts digitalization in the field of prosthetics
and orthotics. The main project objective is to compare the three
hand-held portable scanners (two optical and one laser) and two
optical tripod scanners. The comparison was made with respect of
scanning detail, simplicity of operation and ability to scan directly on
the human body. Testing was carried out on a plaster cast of the
upper limb and directly on a few volunteers. The objective monitored
parameters were time of digitizing and post-processing of 3D data
and resulting visual data quality. Subjectively, it was considered level
of usage and handling of the scanner. The new tripod was developed
to improve the face scanning conditions. The results provide an
overview of the suitability of different types of scanners.
Abstract: Activity-Based Costing (ABC) represents an
alternative paradigm to traditional cost accounting system and
it often provides more accurate cost information for decision
making such as product pricing, product mix, and make-orbuy
decisions. ABC models the causal relationships between
products and the resources used in their production and traces
the cost of products according to the activities through the use
of appropriate cost drivers. In this paper, the implementation
of the ABC in a manufacturing system is analyzed and a
comparison with the traditional cost based system in terms of
the effects on the product costs are carried out to highlight the
difference between two costing methodologies. By using this
methodology, a valuable insight into the factors that cause the
cost is provided, helping to better manage the activities of the
company.
Abstract: Automatic Extraction of Event information from
social text stream (emails, social network sites, blogs etc) is a vital
requirement for many applications like Event Planning and
Management systems and security applications. The key information
components needed from Event related text are Event title, location,
participants, date and time. Emails have very unique distinctions over
other social text streams from the perspective of layout and format
and conversation style and are the most commonly used
communication channel for broadcasting and planning events.
Therefore we have chosen emails as our dataset. In our work, we
have employed two statistical NLP methods, named as Finite State
Machines (FSM) and Hidden Markov Model (HMM) for the
extraction of event related contextual information. An application
has been developed providing a comparison among the two methods
over the event extraction task. It comprises of two modules, one for
each method, and works for both bulk as well as direct user input.
The results are evaluated using Precision, Recall and F-Score.
Experiments show that both methods produce high performance and
accuracy, however HMM was good enough over Title extraction and
FSM proved to be better for Venue, Date, and time.
Abstract: In the paper the study of synthetic transmit aperture
method applying the Golay coded transmission for medical
ultrasound imaging is presented. Longer coded excitation allows to
increase the total energy of the transmitted signal without increasing
the peak pressure. Moreover signal-to-noise ratio and penetration
depth are improved while maintaining high ultrasound image
resolution. In the work the 128-element linear transducer array with
0.3 mm inter-element spacing excited by one cycle and the 8 and 16-
bit Golay coded sequences at nominal frequency 4 MHz was used. To
generate a spherical wave covering the full image region a single
element transmission aperture was used and all the elements received
the echo signals. The comparison of 2D ultrasound images of the
tissue mimicking phantom and in vitro measurements of the beef liver
is presented to illustrate the benefits of the coded transmission. The
results were obtained using the synthetic aperture algorithm with
transmit and receive signals correction based on a single element
directivity function.
Abstract: Current spectrums of a high power induction machine was calculated for the cases of full symmetry, static and dynamic eccentricity. The calculations involve integration of 93 electrical plus four mechanical ordinary differential equations. Electrical equations account for variable inductances affected by slotting and eccentricities. The calculations were followed by Fourier analysis of the stator currents in steady state operation. The paper presents the stator current spectrums in full symmetry, static and dynamic eccentricity cases, and demonstrates the harmonics present in each case. The effect of dynamic eccentricity is demonstrating via comparing the current spectrums related to dynamic eccentricity cases with the full symmetry one. The paper includes one case study, refers to dynamic eccentricity, to present the spectrum of the measured current and demonstrate the existence of the harmonics related to dynamic eccentricity. The zooms of current spectrums around the main slot harmonic zone are included to simplify the comparison and prove the existence of the dynamic eccentricity harmonics in both calculated and measured current spectrums.
Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: The dominant judgment for earthquake damaged reinforced concrete (RC) structures is to rebuild them with the new ones. Consequently, this paper estimates if there is chance to repair earthquake RC beams and obtain economical contribution to modern day society. Therefore, the totally damaged (damaged in shear under cyclic load) reinforced concrete (RC) beams repaired and strengthened by externally bonded carbon fibre reinforced polymer (CFRP) strips in this study. Four specimens, apart from the reference beam, were separated into two distinct groups. Two experimental beams in the first group primarily tested up to failure then appropriately repaired and strengthened with CFRP strips. Two undamaged specimens from the second group were not repaired but strengthened by the identical strengthening scheme as the first group for comparison. This study studies whether earthquake damaged RC beams that have been repaired and strengthened will validate similar strength and behavior to equally strengthened, undamaged RC beams. Accordingly, a strength correspondence according to strengthened specimens was acquired for the repaired and strengthened specimens. Test results confirmed that repair and strengthening, which were estimated in the experimental program, were effective for the specimens with the cracking patterns considered in the experimental program.
Abstract: Plasma Wind Tunnels (PWT) are extensively used for screening and qualification of re-entry Thermel Protection System (TPS) materials. Proper design of a supersonic diffuser for plasma wind tunnel is of importance for achieving good pressurerecovery (thereby reducing vacuum pumping requirement & run time costs) and isolating downstream stream fluctuations from propagating costs) and isolating downstream stream fluctuationnts the details of a rapid design methodology successfully employed for designing supersonic diffuser for high power (several megawatts)plasma wind tunnels and numerical performance analysis of a diffuser configuration designed for one megawatt power rated plasma wind tunnel(enthalpy ~ 30 MJ/kg) using FLUENT 6.3® solver for different diffuser operating sub-atmospheric back-pressures.
Abstract: The crystallization kinetics and phase transformation
of SiO2.Al2O3.0,56P2O5.1,8CaO.0,56CaF2 glass have been
investigated using differential thermal analysis (DTA), x-ray
diffraction (XRD), and scanning electron microscopy (SEM). Glass
samples were obtained by melting the glass mixture at 14500С/120
min. in platinum crucibles. The mixture were prepared from
chemically pure reagents: SiO2, Al(OH)3, H3PO4, CaCO3 and CaF2.
The non-isothermal kinetics of crystallization was studied by
applying the DTA measurements carried out at various heating rates.
The activation energies of crystallization and viscous flow were
measured as 348,4 kJ.mol–1 and 479,7 kJ.mol–1 respectively. Value of
Avrami parameter n ≈ 3 correspond to a three dimensional of crystal
growth mechanism. The major crystalline phase determined by XRD
analysis was fluorapatite (Ca(PO4)3F) and as the minor phases –
fluormargarite (CaAl2(Al2SiO2)10F2) and vitlokite (Ca9P6O24). The
resulting glass-ceramic has a homogeneous microstructure, composed
of prismatic crystals, evenly distributed in glass phase.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: In the present study, a steady-state simulation model
has been developed to evaluate the system performance of a
transcritical carbon dioxide heat pump system for simultaneous water
cooling and heating. Both the evaporator (including both two-phase
and superheated zone) and gas cooler models consider the highly
variable heat transfer characteristics of CO2 and pressure drop. The
numerical simulation model of transcritical CO2 heat pump has been
validated by test data obtained from experiments on the heat pump
prototype. Comparison between the test results and the model
prediction for system COP variation with compressor discharge
pressure shows a modest agreement with a maximum deviation of
15% and the trends are fairly similar. Comparison for other operating
parameters also shows fairly similar deviation between the test
results and the model prediction. Finally, the simulation results are
presented to study the effects of operating parameters such as,
temperature of heat exchanger fluid at the inlet, discharge pressure,
compressor speed on system performance of CO2 heat pump, suitable
in a dairy plant where simultaneous cooling at 4oC and heating at
73oC are required. Results show that good heat transfer properties of
CO2 for both two-phase and supercritical region and efficient
compression process contribute a lot for high system COPs.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.
Abstract: This paper presents a novel approach to finding a
priori interesting regions in mammograms. In order to delineate those
regions of interest (ROI-s) in mammograms, which appear to be
prominent, a topographic representation called the iso-level contour
map consisting of iso-level contours at multiple intensity levels and
region segmentation based-thresholding have been proposed. The
simulation results indicate that the computed boundary gives the
detection rate of 99.5% accuracy.
Abstract: this paper presented a survey analysis subjected on
network bandwidth management from published papers referred in
IEEE Explorer database in three years from 2009 to 2011. Network
Bandwidth Management is discussed in today-s issues for computer
engineering applications and systems. Detailed comparison is
presented between published papers to look further in the IP based
network critical research area for network bandwidth management.
Important information such as the network focus area, a few
modeling in the IP Based Network and filtering or scheduling used in
the network applications layer is presented. Many researches on
bandwidth management have been done in the broad network area
but fewer are done in IP Based network specifically at the
applications network layer. A few researches has contributed new
scheme or enhanced modeling but still the issue of bandwidth
management still arise at the applications network layer. This survey
is taken as a basic research towards implementations of network
bandwidth management technique, new framework model and
scheduling scheme or algorithm in an IP Based network which will
focus in a control bandwidth mechanism in prioritizing the network
traffic the applications layer.
Abstract: This paper proposes a declarative language for
knowledge representation (Ibn Rochd), and its environment of
exploitation (DeGSE). This DeGSE system was designed and
developed to facilitate Ibn Rochd writing applications. The system
was tested on several knowledge bases by ascending complexity,
culminating in a system for recognition of a plant or a tree, and
advisors to purchase a car, for pedagogical and academic guidance,
or for bank savings and credit. Finally, the limits of the language and
research perspectives are stated.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: One of the most common practices for strengthening
the reinforced concrete structures is the application of FRP (Fiber
Reinforce Plastic) sheets to increase the flexural and shear strengths
of the member. The elastic modulus of FRP is considerably higher
than that of concrete. This will result in debonding between the FRP
sheets and concrete surface. With conventional surface preparation of
concrete, the ultimate capacity of the FRP sheets can hardly be
achieved. New methods for preparation of the bonding surface have
shown improvements in reducing the premature debonding of FRP
sheets from concrete surface. The present experimental study focuses
on the application of grooving method to postpone debonding of the
FRP sheets attached to the side faces of concrete beams for shear
strengthening. Comparison has also been made with conventional
surface preparation method. This study clearly shows the efficiency
of grooving method compared to surface preparation method, in
preventing the debonding phenomenon and in increasing the load
carrying capacity of FRP.