Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
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: 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: In the past researchers have questioned the
effectiveness of ethics training in higher education. Also, there are
observations that support the view that ethical behaviour (range of
actions)/ethical decision making models used in the past make use of
vignettes to explain ethical behaviour. The understanding remains in
the perspective that these vignettes play a limited role in determining
individual intentions and not actions. Some authors have also agreed
that there are possibilities of differences in one’s intentions and
actions. This paper makes an attempt to fill those gaps by evaluating
real actions rather than intentions. In a way this study suggests the
use of an experiential methodology to explore Berlo’s model of
communication as an action along with orchestration of various
principles. To this endeavor, an attempt was made to use
conversational analysis in the pursuance of evaluating ethical
decision making behaviour among students and middle level
managers. The process was repeated six times with the set of an
average of 15 participants. Similarities have been observed in the
behaviour of students and middle level managers that calls for
understanding that both the groups of individuals have no cognizance
of their actual actions. The deliberations derived out of conversation
were taken a step forward for meta-ethical evaluations to portray a
clear picture of ethical behaviour among participants. This study
provides insights for understanding demonstrated unconscious human
behaviour which may fortuitously be termed both ethical and
unethical.
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: 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: 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: 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: 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.