Abstract: In the present study, RBF neural networks were used
for predicting the performance and emission parameters of a
biodiesel engine. Engine experiments were carried out in a 4 stroke
diesel engine using blends of diesel and Honge methyl ester as the
fuel. Performance parameters like BTE, BSEC, Tex and emissions
from the engine were measured. These experimental results were
used for ANN modeling.
RBF center initialization was done by random selection and by
using Clustered techniques. Network was trained by using fixed and
varying widths for the RBF units. It was observed that RBF results
were having a good agreement with the experimental results.
Networks trained by using clustering technique gave better results
than using random selection of centers in terms of reduced MRE and
increased prediction accuracy. The average MRE for the performance
parameters was 3.25% with the prediction accuracy of 98% and for
emissions it was 10.4% with a prediction accuracy of 80%.
Abstract: To understand the friction stir welding process, it is
very important to know the nature of the material flow in and around
the tool. The process is a combination of both thermal as well as
mechanical work i.e. it is a coupled thermo-mechanical process.
Numerical simulations are very much essential in order to obtain a
complete knowledge of the process as well as the physics underlying
it. In the present work a model based approach is adopted in order to
study material flow. A thermo-mechanical based CFD model is
developed using a Finite Element package, Comsol Multiphysics.
The fluid flow analysis is done. The model simultaneously predicts
shear strain fields, shear strain rates and shear stress over the entire
workpiece for the given conditions. The flow fields generated by the
streamline plot give an idea of the material flow. The variation of
dynamic viscosity, velocity field and shear strain fields with various
welding parameters is studied. Finally the result obtained from the
above mentioned conditions is discussed elaborately and concluded.
Abstract: In this research article of modeling Underwater
Wireless Sensor Network Simulators, we provide a comprehensive
overview of the various currently available simulators used in UWSN
modeling. In this work, we compare their working environment,
software platform, simulation language, key features, limitations and
corresponding applications. Based on extensive experimentation and
performance analysis, we provide their efficiency for specific
applications. We have also provided guidelines for developing
protocols in different layers of the protocol stack, and finally these
parameters are also compared and tabulated. This analysis is
significant for researchers and designers to find the right simulator
for their research activities.
Abstract: Kidney cancer is the most lethal urological cancer
accounting for 3% of adult malignancies. VHL, a tumor-suppressor
gene, is best known to be associated with renal cell carcinoma
(RCC). The VHL functions as negative regulator of hypoxia inducible
factors. Recent sequencing efforts have identified several novel
frequent mutations of histone modifying and chromatin remodeling
genes in ccRCC (clear cell RCC) including PBRM1 and SETD2. The
PBRM1 gene encodes the BAF180 protein, which involved in
transcriptional activation and repression of selected genes. SETD2
encodes a histone methyltransferase, which may play a role in
suppressing tumor development. In this study, RNAs of 30 paired
tumor and normal samples that were grouped according to the types
of kidney cancer and clinical characteristics of patients, including
gender and average age were examined by RT-PCR, SSCP and
sequencing techniques. VHL, PBRM1 and SETD2 expressions were
relatively down-regulated. However, statistically no significance was
found (Wilcoxon signed rank test, p>0.05). Interestingly, no mutation
was observed on the contrary of previous studies. Understanding the
molecular mechanisms involved in the pathogenesis of RCC has
aided the development of molecular-targeted drugs for kidney cancer.
Further analysis is required to identify the responsible genes rather
than VHL, PBRM1 and SETD2 in kidney cancer.
Abstract: Networking is important among students to achieve
better understanding. Social networking plays an important role in the
education. Realizing its huge potential, various organizations,
including institutions of higher learning have moved to the area of
social networks to interact with their students especially through
Facebook. Therefore, measuring the effectiveness of Facebook as a
learning tool has become an area of interest to academicians and
researchers. Therefore, this study tried to integrate and propose new
theoretical and empirical evidences by linking the western idea of
adopting Facebook as an alternative learning platform from a
Malaysian perspective. This study, thus, aimed to fill a gap by being
among the pioneering research that tries to study the effectiveness of
adopting Facebook as a learning platform across other cultural
settings, namely Malaysia. Structural equation modeling was
employed for data analysis and hypothesis testing. This study finding
has provided some insights that would likely affect students’
awareness towards using Facebook as an alternative learning
platform in the Malaysian higher learning institutions. At the end,
future direction is proposed.
Abstract: A mathematical model of the additional effects of the
liquid in the hydrodynamic gap is presented in the paper. An
incompressible viscous fluid is considered. Based on computational
modeling are determined the matrices of mass, stiffness and damping.
The mathematical model is experimentally verified.
Abstract: High density electrical prospecting has been widely
used in groundwater investigation, civil engineering and
environmental survey. For efficient inversion, the forward modeling
routine, sensitivity calculation, and inversion algorithm must be
efficient. This paper attempts to provide a brief summary of the past
and ongoing developments of the method. It includes reviews of the
procedures used for data acquisition, processing and inversion of
electrical resistivity data based on compilation of academic literature.
In recent times there had been a significant evolution in field survey
designs and data inversion techniques for the resistivity method. In
general 2-D inversion for resistivity data is carried out using the
linearized least-square method with the local optimization technique
.Multi-electrode and multi-channel systems have made it possible to
conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve
complex geological structures that were not possible with traditional
1-D surveys. 3-D surveys play an increasingly important role in very
complex areas where 2-D models suffer from artifacts due to off-line
structures. Continued developments in computation technology, as
well as fast data inversion techniques and software, have made it
possible to use optimization techniques to obtain model parameters to
a higher accuracy. A brief discussion on the limitations of the
electrical resistivity method has also been presented.
Abstract: Structural Equation Modeling (SEM) was used to test
a hypothesized model explaining Malaysian hypermarket customers’
perceptions of brand trust (BT), customer perceived value (CPV) and
perceived service quality (PSQ) on building their brand loyalty
(CBL) and generating positive word-of-mouth communication
(WOM). Self-administered questionnaires were used to collect data
from 374 Malaysian hypermarket customers from Mydin, Tesco,
Aeon Big and Giant in Kuala Lumpur, a metropolitan city of
Malaysia. The data strongly supported the model exhibiting that BT,
CPV and PSQ are prerequisite factors in building customer brand
loyalty, while PSQ has the strongest effect on prediction of customer
brand loyalty compared to other factors. Besides, the present study
suggests the effect of the aforementioned factors via customer brand
loyalty strongly contributes to generate positive word of mouth
communication.
Abstract: The development of adaptive user interfaces (UI)
presents for a long time an important research area in which
researcher attempt to call upon the full resources and skills of several
disciplines, The adaptive UI community holds a thorough knowledge
regarding the adaptation of UIs with users and with contexts of use.
Several solutions, models, formalisms, techniques and mechanisms
were proposed to develop adaptive UI. In this paper, we propose an
approach based on the fuzzy set theory for modeling the concept of
the appropriateness of different solutions of UI adaptation with
different situations for which interactive systems have to adapt their
UIs.
Abstract: Micro-electromechanical system (MEMS)
accelerometers and gyroscopes are suitable for the inertial navigation
system (INS) of many applications due to low price, small
dimensions and light weight. The main disadvantage in a comparison
with classic sensors is a worse long term stability. The estimation
accuracy is mostly affected by the time-dependent growth of inertial
sensor errors, especially the stochastic errors. In order to eliminate
negative effects of these random errors, they must be accurately
modeled. In this paper, the Allan variance technique will be used in
modeling the stochastic errors of the inertial sensors. By performing
a simple operation on the entire length of data, a characteristic curve
is obtained whose inspection provides a systematic characterization
of various random errors contained in the inertial-sensor output data.
Abstract: This paper analyzes the conceptual framework of three
statistical methods, multiple regression, path analysis, and structural
equation models. When establishing research model of the statistical
modeling of complex social phenomenon, it is important to know the
strengths and limitations of three statistical models. This study
explored the character, strength, and limitation of each modeling and
suggested some strategies for accurate explaining or predicting the
causal relationships among variables. Especially, on the studying of
depression or mental health, the common mistakes of research
modeling were discussed.
Abstract: Polymer Electrolyte Membrane Fuel Cell (PEMFC) is
such a time-vary nonlinear dynamic system. The traditional linear
modeling approach is hard to estimate structure correctly of PEMFC
system. From this reason, this paper presents a nonlinear modeling of
the PEMFC using Neural Network Auto-regressive model with
eXogenous inputs (NNARX) approach. The multilayer perception
(MLP) network is applied to evaluate the structure of the NNARX
model of PEMFC. The validity and accuracy of NNARX model are
tested by one step ahead relating output voltage to input current from
measured experimental of PEMFC. The results show that the obtained
nonlinear NNARX model can efficiently approximate the dynamic
mode of the PEMFC and model output and system measured output
consistently.
Abstract: The article presents two mathematical models of the
interaction between a rotating shaft and an incompressible fluid. The
mathematical model includes both the journal bearings and the
axially traversed hydrodynamic sealing gaps of hydraulic machines.
A method is shown for the identification of additional effects of the
fluid acting on the rotor of the machine, both for a linear and a nonlinear
model. The interaction is expressed by matrices of mass,
stiffness and damping.
Abstract: During the post-Civil War era, the city of Nashville,
Tennessee, had the highest mortality rate in the United States. The
elevated death and disease rates among former slaves were
attributable to lack of quality healthcare. To address the paucity of
healthcare services, Meharry Medical College, an institution with the
mission of educating minority professionals and serving the
underserved population, was established in 1876.
Purpose: The social ecological framework and partial least squares
(PLS) path modeling were used to quantify the impact of
socioeconomic status and adverse health outcome on primary care
professionals serving the disadvantaged community. Thus, the study
results could demonstrate the accomplishment of the College’s
mission of training primary care professionals to serve in underserved
areas.
Methods: Various statistical methods were used to analyze alumni
data from 1975 – 2013. K-means cluster analysis was utilized to
identify individual medical and dental graduates in the cluster groups
of the practice communities (Disadvantaged or Non-disadvantaged
Communities). Discriminant analysis was implemented to verify the
classification accuracy of cluster analysis. The independent t-test was
performed to detect the significant mean differences of respective
clustering and criterion variables. Chi-square test was used to test if
the proportions of primary care and non-primary care specialists are
consistent with those of medical and dental graduates practicing in
the designated community clusters. Finally, the PLS path model was
constructed to explore the construct validity of analytic model by
providing the magnitude effects of socioeconomic status and adverse
health outcome on primary care professionals serving the
disadvantaged community.
Results: Approximately 83% (3,192/3,864) of Meharry Medical
College’s medical and dental graduates from 1975 to 2013 were
practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the
PLS path modeling demonstrated that alumni served as primary care
professionals in communities with significantly lower socioeconomic
status and higher adverse health outcome (p < .001). The PLS path
modeling exhibited the meaningful interrelation between primary
care professionals practicing communities and surrounding
environments (socioeconomic statues and adverse health outcome),
which yielded model reliability, validity, and applicability.
Conclusion: This study applied social ecological theory and
analytic modeling approaches to assess the attainment of Meharry
Medical College’s mission of training primary care professionals to
serve in underserved areas, particularly in communities with low
socioeconomic status and high rates of adverse health outcomes. In
summary, the majority of medical and dental graduates from Meharry
Medical College provided primary care services to disadvantaged
communities with low socioeconomic status and high adverse health
outcome, which demonstrated that Meharry Medical College has
fulfilled its mission. The high reliability, validity, and applicability of
this model imply that it could be replicated for comparable
universities and colleges elsewhere.
Abstract: Objects are usually horizontally sliced when printed by 3D printers. Therefore, if an object to be printed, such as a collection of fibers, originally has natural direction in shape, the printed direction contradicts with the natural direction. By using proper tools, such as field-oriented 3D paint software, field-oriented solid modelers, field-based tool-path generation software, and non-horizontal FDM 3D printers, the natural direction can be modeled and objects can be printed in a direction that is consistent with the natural direction. This consistence results in embodiment of momentum or force in expressions of the printed object. To achieve this goal, several design and manufacturing problems, but not all, have been solved. An application of this method is (Japanese) 3D calligraphy.
Abstract: This paper is part of a study to develop robots for
farming. As such power requirement to operate equipment attach to
such robots become an important factor. Soil-tool interaction plays
major role in power consumption, thus predicting accurately the
forces which act on the blade during the farming is very important for
optimal designing of farm equipment. In this paper, a finite element
investigation for tillage tools and soil interaction is described by
using an inelastic constitutive material law for agriculture
application. A 3-dimensional (3D) nonlinear finite element analysis
(FEA) is developed to examine behavior of a blade with different
rake angles moving in a block of soil, and to estimate the blade force.
The soil model considered is an elastic-plastic with non-associated
Drucker-Prager material model. Special use of contact elements are
employed to consider connection between soil-blade and soil-soil
surfaces. The FEA results are compared with experimental ones,
which show good agreement in accurately predicting draft forces
developed on the blade when it moves through the soil. Also a very
good correlation was obtained between FEA results and analytical
results from classical soil mechanics theories for straight blades.
These comparisons verified the FEA model developed. For analyzing
complicated soil-tool interactions and for optimum design of blades,
this method will be useful.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: The present research work investigates the seismic
response of reinforced concrete (RC) frame building considering the
effect of modeling masonry infill (MI) walls. The seismic behavior of
a residential 6-storey RC frame building, considering and ignoring
the effect of masonry, is numerically investigated using response
spectrum (RS) analysis. The considered herein building is designed
as a moment resisting frame (MRF) system following the Egyptian
code (EC) requirements. Two developed models in terms of bare
frame and infill walls frame are used in the study. Equivalent
diagonal strut methodology is used to represent the behavior of infill
walls, whilst the well-known software package ETABS is used for
implementing all frame models and performing the analysis. The
results of the numerical simulations such as base shear,
displacements, and internal forces for the bare frame as well as the
infill wall frame are presented in a comparative way. The results of
the study indicate that the interaction between infill walls and frames
significantly change the responses of buildings during earthquakes
compared to the results of bare frame building model. Specifically,
the seismic analysis of RC bare frame structure leads to
underestimation of base shear and consequently damage or even
collapse of buildings may occur under strong shakings. On the other
hand, considering infill walls significantly decrease the peak floor
displacements and drifts in both X and Y-directions.
Abstract: Reflux condensation occurs in vertical channels and tubes when there is an upward core flow of vapour (or gas-vapour mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapour-gas mixture (or pure vapour) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapour core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces a sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on finite volume method and co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and gas mass fraction profiles, as well as axial variations of film thickness.
Abstract: This paper deals with the theoretical and numerical
investigation of magneto hydrodynamic boundary layer flow of a
nanofluid past a wedge shaped wick in heat pipe used for the cooling
of electronic components and different type of machines. To
incorporate the effect of nanoparticle diameter, concentration of
nanoparticles in the pure fluid, nanothermal layer formed around the
nanoparticle and Brownian motion of nanoparticles etc., appropriate
models are used for the effective thermal and physical properties of
nanofluids. To model the rotation of nanoparticles inside the base
fluid, microfluidics theory is used. In this investigation ethylene
glycol (EG) based nanofluids, are taken into account. The non-linear
equations governing the flow and heat transfer are solved by using a
very effective particle swarm optimization technique along with
Runge-Kutta method. The values of heat transfer coefficient are
found for different parameters involved in the formulation viz.
nanoparticle concentration, nanoparticle size, magnetic field and
wedge angle etc. It is found that, the wedge angle, presence of
magnetic field, nanoparticle size and nanoparticle concentration etc.
have prominent effects on fluid flow and heat transfer characteristics
for the considered configuration.