Abstract: Gypsum (CaSO4.2H2O) is a mineral that is found in
large quantities in the Turkey and in the World. In this study, the
dissolution of this mineral in the diammonium hydrogen phosphate
solutions has been studied. The dissolution and dissolution kinetics of
gypsum in diammonium hydrogen phosphate solutions will be useful
for evaluating of solid wastes containing gypsum. Parameters such as
diammonium hydrogen phosphate concentration, temperature and
stirring speed affecting on the dissolution rate of the gypsum in
diammonium hydrogen phosphate solutions were investigated. In
experimental studies have researched effectiveness of the selected
parameters. The dissolution of gypsum were examined in two parts at
low and high temperatures. The experimental results were
successfully correlated by linear regression using Statistica program.
Dissolution curves were evaluated shrinking core models for solidfluid
systems. The activation energy was found to be 34.58 kJ/mol
and 44.45 kJ/mol for the low and the high temperatures. The
dissolution of gypsum was controlled by chemical reaction both low
temperatures and high temperatures.
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: 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 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: 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: 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: R.C.C. buildings with dual structural system
consisting of shear walls (or braces) and moment resisting frames
have been widely used to resist lateral forces during earthquakes. The
dual systems are designed to resist the total design lateral force in
proportion to their lateral stiffness. The response of combination of
braces and shear walls has not yet been studied. The combination
may prove to be more effective to resist lateral forces during
earthquakes. This concept has been applied to regular R.C.C.
buildings provided with shear walls, braces and their combinations.
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: This study analyzes the innovative orientation of the
Croatian entrepreneurs. Innovative orientation is represented by the
perceived extent to which an entrepreneur’s product or service or
technology is new, and no other businesses offer the same product.
The sample is extracted from the GEM Croatia Adult Population
Survey dataset for the years 2003-2013. We apply descriptive
statistics, t-test, Chi-square test and logistic regression. Findings
indicate that innovative orientations vary with personal, firm, meso
and macro level variables, and between different stages in
entrepreneurship process. Significant predictors are occupation of the
entrepreneurs, size of the firm and export aspiration for both early
stage and established entrepreneurs. In addition, fear of failure,
expecting to start a new business and seeing an entrepreneurial career
as a desirable choice are predictors of innovative orientation among
early stage entrepreneurs.
Abstract: In this article we will study the elliptic curve defined
over the ring An and we define the mathematical operations of ECC,
which provides a high security and advantage for wireless
applications compared to other asymmetric key cryptosystem.
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: Wireless Sensor Networks (WSNs) have wide variety
of applications and provide limitless future potentials. Nodes in
WSNs are prone to failure due to energy depletion, hardware failure,
communication link errors, malicious attacks, and so on. Therefore,
fault tolerance is one of the critical issues in WSNs. We study how
fault tolerance is addressed in different applications of WSNs. Fault
tolerant routing is a critical task for sensor networks operating in
dynamic environments. Many routing, power management, and data
dissemination protocols have been specifically designed for WSNs
where energy awareness is an essential design issue. The focus,
however, has been given to the routing protocols which might differ
depending on the application and network architecture.
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.
Abstract: Flash Floods, together with landslides, are a common
natural threat for people living in mountainous regions and foothills.
One way to deal with this constant menace is the use of Early
Warning Systems, which have become a very important mitigation
strategy for natural disasters.
In this work we present our proposal for a pilot Flash Flood Early
Warning System for Santiago, Chile, the first stage of a more
ambitious project that in a future stage shall also include early
warning of landslides.
To give a context for our approach, we first analyze three existing
Flash Flood Early Warning Systems, focusing on their general
architectures. We then present our proposed system, with main focus
on the decision support system, a system that integrates empirical
models and fuzzy expert systems to achieve reliable risk estimations.