Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: In this paper, the problem of steady laminar boundary
layer flow and heat transfer over a permeable exponentially
stretching/shrinking sheet with generalized slip velocity is
considered. The similarity transformations are used to transform the
governing nonlinear partial differential equations to a system of
nonlinear ordinary differential equations. The transformed equations
are then solved numerically using the bvp4c function in MATLAB.
Dual solutions are found for a certain range of the suction and
stretching/shrinking parameters. The effects of the suction parameter,
stretching/shrinking parameter, velocity slip parameter, critical shear
rate and Prandtl number on the skin friction and heat transfer
coefficients as well as the velocity and temperature profiles are
presented and discussed.
Abstract: Long Distance Truck Drivers (LDTDs) have been
found to be a high risk group in the spread of HIV/AIDS globally;
perhaps, due to their high Sexual Risk Behaviours (SRBs).
Interventions for reducing SRBs in trucking population have not been
fully exploited. A quasi-experimental control group pretest-posttest
design was used to assess the efficacy of psycho-education and
behavioural skills training in reducing SRBs among LDTDs. Sixteen
drivers rivers were randomly assigned into either experimental or
control groups using balloting technique. Questionnaire was used as
an instrument for data collection. Repeated measures t-test and
independent t-test were used to test hypotheses. Intervention had
significant effect on the SRBs among LDTDs at post-test (t{7}=
6.01, p
Abstract: Co-crystal is believed to improve the solubility and
dissolution rates and thus, enhanced the bioavailability of poor water
soluble drugs particularly during the oral route of administration.
With the existing of poorly soluble drugs in pharmaceutical industry,
the screening of co-crystal formation using carbamazepine (CBZ) as
a model drug compound with dicarboxylic acids co-crystal formers
(CCF) namely fumaric (FA) and succinic (SA) acids in ethanol has
been studied. The co-crystal formations were studied by varying the
mol ratio values of CCF to CBZ to access the effect of CCF
concentration on the formation of the co-crystal. Solvent evaporation,
slurry and cooling crystallization which representing the solution
based method co-crystal screening were used. Based on the
differential scanning calorimetry (DSC) analysis, the melting point of
CBZ-SA in different ratio was in the range between 188oC-189oC.
For CBZ-FA form A and CBZ-FA form B the melting point in
different ratio were in the range of 174oC-175oC and 185oC-186oC
respectively. The product crystal from the screening was also
characterized using X-ray powder diffraction (XRPD). The XRPD
pattern profile analysis has shown that the CBZ co-crystals with FA
and SA were successfully formed for all ratios studied. The findings
revealed that CBZ-FA co-crystal were formed in two different
polymorphs. It was found that CBZ-FA form A and form B were
formed from evaporation and slurry crystallization methods
respectively. On the other hand, in cooling crystallization method,
CBZ-FA form A was formed at lower mol ratio of CCF to CBZ and
vice versa. This study disclosed that different methods and mol ratios
during the co-crystal screening can affect the outcome of co-crystal
produced such as polymorphic forms of co-crystal and thereof. Thus,
it was suggested that careful attentions is needed during the screening
since the co-crystal formation is currently one of the promising
approach to be considered in research and development for
pharmaceutical industry to improve the poorly soluble drugs.
Abstract: The convective heat and mass transfer in nanofluid
flow through a porous media due to a permeable stretching sheet with
magnetic field, viscous dissipation, chemical reaction and Soret
effects are numerically investigated. Two types of nanofluids, namely
Cu-water and Ag-water were studied. The governing boundary layer
equations are formulated and reduced to a set of ordinary differential
equations using similarity transformations and then solved
numerically using the Keller box method. Numerical results are
obtained for the skin friction coefficient, Nusselt number and
Sherwood number as well as for the velocity, temperature and
concentration profiles for selected values of the governing
parameters. Excellent validation of the present numerical results has
been achieved with the earlier linearly stretching sheet problems in
the literature.
Abstract: Incineration of municipal solid waste (MSW) is one of
the key scopes in the global clean energy strategy. A computational
fluid dynamics (CFD) model was established in order to reveal these
features of the combustion process in a fixed porous bed of MSW.
Transporting equations and process rate equations of the waste bed
were modeled and set up to describe the incineration process,
according to the local thermal conditions and waste property
characters. Gas phase turbulence was modeled using k-ε turbulent
model and the particle phase was modeled using the kinetic theory of
granular flow. The heterogeneous reaction rates were determined
using Arrhenius eddy dissipation and the Arrhenius-diffusion
reaction rates. The effects of primary air flow rate and temperature in
the burning process of simulated MSW are investigated
experimentally and numerically. The simulation results in bed are
accordant with experimental data well. The model provides detailed
information on burning processes in the fixed bed, which is otherwise
very difficult to obtain by conventional experimental techniques.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: In this study, a computational fluid dynamics (CFD)
model has been developed for studying the effect of surface
roughness profile on the EHL problem. The cylinders contact
geometry, meshing and calculation of the conservation of mass and
momentum equations are carried out using the commercial software
packages ICEMCFD and ANSYS Fluent. The user defined functions
(UDFs) for density, viscosity and elastic deformation of the cylinders
as the functions of pressure and temperature are defined for the CFD
model. Three different surface roughness profiles are created and
incorporated into the CFD model. It is found that the developed CFD
model can predict the characteristics of fluid flow and heat transfer in
the EHL problem, including the main parameters such as pressure
distribution, minimal film thickness, viscosity, and density changes.
The results obtained show that the pressure profile at the center of the
contact area directly relates to the roughness amplitude. A rough
surface with kurtosis value of more than 3 has greater influence over
the fluctuated shape of pressure distribution than in other cases.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: These days customer satisfaction plays vital role in
any business. When customer searches for a product, significantly a
junk of irrelevant information is what is given, leading to customer
dissatisfaction. To provide exactly relevant information on the
searched product, we are proposing a model of KaaS (Knowledge as
a Service), which pre-processes the information using decision
making paradigm using Multi-agents.
Information obtained from various sources is taken to derive
knowledge and they are linked to Cloud to capture new idea. The
main focus of this work is to acquire relevant information
(knowledge) related to product, then convert this knowledge into a
service for customer satisfaction and deploy on cloud.
For achieving these objectives we are have opted to use multi
agents. They are communicating and interacting with each other,
manipulate information, provide knowledge, to take decisions. The
paper discusses about KaaS as an intelligent approach for Knowledge
acquisition.
Abstract: This paper describes an Action Research project
which was undertaken to inform professional practice in order to
develop a newly created Centre for Student Success in the specific
context of transnational medical and nursing education in the Middle
East. The objectives were to enhance the academic performance,
persistence, integration and personal and professional development of
a multinational study body, in particular in relation to pre-clinical
medical students, and to establish a comfortable, friendly and
student-driven environment within an Irish medical university
recently established in Bahrain. The outcomes of the project resulted
in the development of a specific student success ‘signature’ for this
particular transnational higher education context.
Abstract: A three-dimensional numerical model of
thermoelectric generator (TEG) modules attached to a large chimney
plate is proposed and solved numerically using a control volume based
finite difference formulation. The TEG module consists of a
thermoelectric generator, an elliptical pin-fin heat sink, and a cold
plate for water cooling. In the chimney, the temperature of flue gases is
450-650K. Although the TEG hot-side temperature and thus the
electric power output can be increased by inserting an elliptical pin-fin
heat sink into the chimney tunnel to increase the heat transfer area, the
pin fin heat sink would cause extra pumping power at the same time.
The main purpose of this study is to analyze the effects of geometrical
parameters on the electric power output and chimney pressure drop
characteristics. The effects of different operating conditions, including
various inlet velocities (Vin= 1, 3, 5 m/s), inlet temperatures (Tgas = 450,
550, 650K) and different fin height (0 to 150 mm) are discussed in
detail. The predicted numerical data for the power vs. current (P-I)
curve are in good agreement (within 11%) with the experimental data.
Abstract: The aim of software maintenance is to maintain
the software system in accordance with advancement in software
and hardware technology. One of the early works on software
maintenance is to extract information at higher level of abstraction. In
this paper, we present the process of how to design an information
extraction tool for software maintenance. The tool can extract the
basic information from old programs such as about variables, based
classes, derived classes, objects of classes, and functions. The tool
have two main parts; the lexical analyzer module that can read the
input file character by character, and the searching module which
users can get the basic information from the existing programs. We
implemented this tool for a patterned sub-C++ language as an input
file.
Abstract: An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.
Abstract: Parabolic solar trough systems have seen limited
deployments in cold northern climates as they are more suitable for
electricity production in southern latitudes. A numerical dynamic
model is developed to simulate troughs installed in cold climates and
validated using a parabolic solar trough facility in Winnipeg. The
model is developed in Simulink and will be utilized to simulate a trigeneration
system for heating, cooling and electricity generation in
remote northern communities. The main objective of this simulation
is to obtain operational data of solar troughs in cold climates and use
the model to determine ways to improve the economics and address
cold weather issues.
In this paper the validated Simulink model is applied to simulate a
solar assisted absorption cooling system along with electricity
generation using Organic Rankine Cycle (ORC) and thermal storage.
A control strategy is employed to distribute the heated oil from solar
collectors among the above three systems considering the
temperature requirements. This modelling provides dynamic
performance results using measured meteorological data recorded
every minute at the solar facility location. The purpose of this
modeling approach is to accurately predict system performance at
each time step considering the solar radiation fluctuations due to
passing clouds. Optimization of the controller in cold temperatures is
another goal of the simulation to for example minimize heat losses in
winter when energy demand is high and solar resources are low.
The solar absorption cooling is modeled to use the generated heat
from the solar trough system and provide cooling in summer for a
greenhouse which is located next to the solar field.
The results of the simulation are presented for a summer day in
Winnipeg which includes comparison of performance parameters of
the absorption cooling and ORC systems at different heat transfer
fluid (HTF) temperatures.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Abstract: In this paper, the exergy analysis of vapor absorption
refrigeration system using LiBr-H2O as working fluid is carried out
with the modified Gouy-Stodola approach rather than the classical
Gouy-Stodola equation and effect of varying input parameters is also
studied on the performance of the system. As the modified approach
uses the concept of effective temperature, the mathematical
expressions for effective temperature have been formulated and
calculated for each component of the system. Various constraints and
equations are used to develop program in EES to solve these
equations. The main aim of this analysis is to determine the
performance of the system and the components having major
irreversible loss. Results show that exergy destruction rate is
considerable in absorber and generator followed by evaporator and
condenser. There is an increase in exergy destruction in generator,
absorber and condenser and decrease in the evaporator by the
modified approach as compared to the conventional approach. The
value of exergy determined by the modified Gouy-Stodola equation
deviates maximum i.e. 26% in the generator as compared to the
exergy calculated by the classical Gouy-Stodola method.
Abstract: Essential oils have a significant antimicrobial activity.
These oils can successfully replace the antibiotics. So, the
microorganisms show their inefficiencies resistant for the antibiotics.
For this reason, we study the physicochemical analysis and
antimicrobial activity of the essential oil of Daucus carota. The
extraction is done by steam distillation of water which brought us a
very significant return of 4.65%. The analysis of the essential oil is
performed by GC / MS and has allowed us to identify 32 compounds
in the oil of D. carota flowering tops of Bouira. Three of which are in
the majority are the α-Pinene (22.3%), the carotol (21.7%) and the
limonene (15.8%).
Abstract: Cloud computing is a new technology in industry and
academia. The technology has grown and matured in last half decade
and proven their significant role in changing environment of IT
infrastructure where cloud services and resources are offered over the
network. Cloud technology enables users to use services and
resources without being concerned about the technical implications of
technology. There are substantial research work has been performed
for the usage of cloud computing in educational institutes and
majority of them provides cloud services over high-end blade servers
or other high-end CPUs. However, this paper proposes a new stack
called “CiCKAStack” which provide cloud services over unutilized
computing resources, named as commodity computers.
“CiCKAStack” provides IaaS and PaaS using underlying commodity
computers. This will not only increasing the utilization of existing
computing resources but also provide organize file system, on
demand computing resource and design and development
environment.