Abstract: Significant quota of Municipal Electrical Energy
consumption is related to Decentralized Air Conditioning which is
mostly provided by evaporative coolers. So the aim is to optimize
design of air conditioners to increase their efficiencies. To achieve
this goal, results of practical standardized tests for 40 evaporative
coolers in different types collected and simultaneously results for
same coolers based on one of EER (Energy Efficiency Ratio)
modeling styles are figured out. By comparing experimental results
of different coolers standardized tests with modeling results,
preciseness of used model is assessed and after comparing gained
preciseness with international standards based on EER for cooling
capacity, aeration, and also electrical energy consumption, energy
label from A (most effective) to G (less effective) is classified; finally
needed methods to optimize energy consumption and coolers’
classification are provided.
Abstract: This exploratory study gives an overview of the
evolution of the main financial and performance indicators of the
Academic Spin-Off’s and High Growth Academic Spin-Off’s in year
3 and year 6 after its creation in the region of Catalonia in Spain. The
study compares and evaluates results of these different measures of
performance and the degree of success of these companies for each
University.
We found that the average Catalonian Academic Spin-Off is small
and have not achieved the sustainability stage at year 6. On the
contrary, a small group of High Growth Academic Spin-Off’s
exhibits robust performance with high profits in year 6. Our results
support the need to increase selectivity and support for these
companies especially near year 3, because are the ones that will bring
wealth and employment. University role as an investor has rigid
norms and habits that impede an efficient economic return from their
ASO investment.
Universities with high performance on sales and employment in
year 3 not always could sustain this growth in year 6 because their
ASO’s are not profitable. On the contrary, profitable ASO exhibit
superior performance in all measurement indicators in year 6. We
advocate the need of a balanced growth (with profits) as a way to
obtain subsequent continuous growth.
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: 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: Rice husk and kenaf filled with calcium carbonate
(CaCO3) and high density polyethylene (HDPE) composite were
prepared separately using twin-screw extruder at 50rpm. Different
filler loading up to 30 parts of rice husk particulate and kenaf fiber
were mixed with the fixed 30% amount of CaCO3 mineral filler to
produce rice husk/CaCO3/HDPE and kenaf/CaCO3/HDPE hybrid
composites. In this study, the effects of natural fiber for both rice
husk and kenaf in CaCO3/HDPE composite on physical, mechanical
and morphology properties were investigated. Field Emission
Scanning Microscope (FeSEM) was used to investigate the impact
fracture surfaces of the hybrid composite. The property analyses
showed that water absorption increased with the presence of kenaf
and rice husk fillers. Natural fibers in composite significantly
influence water absorption properties due to natural characters of
fibers which contain cellulose, hemicellulose and lignin structures.
The result showed that 10% of additional natural fibers into hybrid
composite had caused decreased flexural strength, however additional
of high natural fiber (>10%) filler loading has proved to increase its
flexural strength.
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 paper, a direct power control (DPC)
strategies have been investigated in order to control a high
power AC/DC converter with time variable load. This converter
is composed of a three level three phase neutral point clamped
(NPC) converter as rectifier and an H-bridge four quadrant
current control converter. In the high power application,
controller not only must adjust the desire outputs but also
decrease the level of distortions which are injected to the network
from the converter. Regarding to this reason and nonlinearity
of the power electronic converter, the conventional controllers
cannot achieve appropriate responses. In this research, the
precise mathematical analysis has been employed to design the
appropriate controller in order to control the time variable
load. A DPC controller has been proposed and simulated using
Matlab/ Simulink. In order to verify the simulation result, a real
time simulator- OPAL-RT- has been employed. In this paper,
the dynamic response and stability of the high power NPC
with variable load has been investigated and compared with
conventional types using a real time simulator. The results proved
that the DPC controller is more stable and has more precise
outputs in comparison with conventional controller.
Abstract: Rural tourism is usually associated with rural
development because it has strong linkages to rural resources; but it
remains underdeveloped compared to urban tourism. This
underdevelopment of rural tourism serves as a motivation for this
study whose aim is to examine the factors affecting the perceived
satisfaction of rural tourists. The objectives of this study are: to
identify and design theories and models on rural tourism satisfaction,
and to empirically validate these models and theories through a
survey of tourists from the Malealea Lodge which is located in the
Mafeteng District, in the Mountain Kingdom of Lesotho. Data
generated by the collection of questionnaires used by this survey was
analyzed quantitatively using descriptive statistics and correlations in
SPSS after checking the validity and the reliability of the
questionnaire. The main hypothesis behind this study is the
relationship between the demographics of rural tourists, their
motivation, and their satisfaction, as supported by existing literature;
except that motivation is measured in this study according to three
dimensions: push factors, pull factors, and perceived usefulness of
ICTs in the rural tourism experience. Findings from this study
indicate that among the demographics factors, continent of origin and
marital status influence the satisfaction of rural tourists; and their
occupation affects their perceptions on the use of ICTs in rural
tourism. Moreover, only pull factors were found to influence the
satisfaction of rural tourists.
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: 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: 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: This paper introduces an original method for
guaranteed estimation of the accuracy for an ensemble of Lipschitz
classifiers. The solution was obtained as a finite closed set of
alternative hypotheses, which contains an object of classification with
probability of not less than the specified value. Thus, the
classification is represented by a set of hypothetical classes. In this
case, the smaller the cardinality of the discrete set of hypothetical
classes is, the higher is the classification accuracy. Experiments have
shown that if cardinality of the classifiers ensemble is increased then
the cardinality of this set of hypothetical classes is reduced. The
problem of the guaranteed estimation of the accuracy for an ensemble
of Lipschitz classifiers is relevant in multichannel classification of
target events in C-OTDR monitoring systems. Results of suggested
approach practical usage to accuracy control in C-OTDR monitoring
systems are present.
Abstract: The adaptation of social networking sites within
higher education has garnered significant interest in the recent years
with numerous researches considering it as a possible shift from the
traditional classroom based learning paradigm. Notwithstanding this
increase in research and conducted studies however, the adaption of
SNS based modules have failed to proliferate within Universities.
This paper commences its contribution by analyzing the various
models and theories proposed in literature and amalgamate together
various effective aspects for the inclusion of social technology within
e-Learning. A three phased framework is further proposed which
details the necessary considerations for the successful adaptation of
SNS in enhancing the students learning experience. This proposal
outlines the theoretical foundations which will be analyzed in
practical implementation across international university campuses.
Abstract: Improved resource efficiency of production is a key
requirement for sustainable growth, worldwide. In this regards, by
considering the energy and tourism as the extra inputs to the classical
Coub-Douglas production function, this study aims at investigating
the efficiency changes in the North African countries. To this end, the
study uses panel data for the period 1995-2010 and adopts the
Malmquist index based on the data envelopment analysis. Results
show that tourism increases technical and scale efficiencies, while it
decreases technological and total factor productivity changes. On the
other hand, when the production function is augmented by the energy
input; technical efficiency change decreases, while the technological
change, scale efficiency change and total factor productivity change
increase. Thus, in order to satisfy the needs for sustainable growth,
North African governments should take some measures for increasing
the contribution that the tourism makes to economic growth and some
others for efficient use of resources in the energy sector.
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%).