Abstract: PDMS (Polydimethylsiloxane) polymer is a suitable material for biological and MEMS (Microelectromechanical systems) designers, because of its biocompatibility, transparency and high resistance under plasma treatment. PDMS round channel is always been of great interest due to its ability to confine the liquid with membrane type micro valves. In this paper we are presenting a very simple way to form round shapemicrofluidic channel, which is based on reflow of positive photoresist AZ® 40 XT. With this method, it is possible to obtain channel of different height simply by varying the spin coating parameters of photoresist.
Abstract: Studies on Simultaneous Saccharification and Fermentation (SSF) of corn flour, a major agricultural product as the substrate using starch digesting glucoamylase enzyme derived from Aspergillus niger and non starch digesting and sugar fermenting Saccharomyces cerevisiae in a batch fermentation. Experiments based on Central Composite Design (CCD) were conducted to study the effect of substrate concentration, pH, temperature, enzyme concentration on Ethanol Concentration and the above parameters were optimized using Response Surface Methodology (RSM). The optimum values of substrate concentration, pH, temperature and enzyme concentration were found to be 160 g/l, 5.5, 30°C and 50 IU respectively. The effect of inoculums age on ethanol concentration was also investigated. The corn flour solution equivalent to 16% initial starch concentration gave the highest ethanol concentration of 63.04 g/l after 48 h of fermentation at optimum conditions of pH and temperature. Monod model and Logistic model were used for growth kinetics and Leudeking – Piret model was used for product formation kinetics.
Abstract: Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. Exclusive breastfeeding during the first 6 months of life is of fundamental importance because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in developed countries, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we study the factors that influence exclusive breastfeeding and use the Generalized Poisson regression model to analyze the practices of exclusive breastfeeding in Mauritius. We develop two sets of quasi-likelihood equations (QLE)to estimate the parameters.
Abstract: The present paper considers the steady free convection
boundary layer flow of a viscoelastic fluid on solid sphere with
Newtonian heating. The boundary layer equations are an order higher
than those for the Newtonian (viscous) fluid and the adherence
boundary conditions are insufficient to determine the solution of
these equations completely. Thus, the augmentation an extra
boundary condition is needed to perform the numerical
computational. The governing boundary layer equations are first
transformed into non-dimensional form by using special
dimensionless group and then solved by using an implicit finite
difference scheme. The results are displayed graphically to illustrate
the influence of viscoelastic K and Prandtl Number Pr parameters on
skin friction, heat transfer, velocity profiles and temperature profiles.
Present results are compared with the published papers and are found
to concur very well.
Abstract: In this paper, the full state feedback controllers
capable of regulating and tracking the speed trajectory are presented.
A fourth order nonlinear mean value model of a 448 kW turbocharged
diesel engine published earlier is used for the purpose.
For designing controllers, the nonlinear model is linearized and
represented in state-space form. Full state feedback controllers
capable of meeting varying speed demands of drivers are presented.
Main focus here is to investigate sensitivity of the controller to the
perturbations in the parameters of the original nonlinear model.
Suggested controller is shown to be highly insensitive to the
parameter variations. This indicates that the controller is likely
perform with same accuracy even after significant wear and tear of
engine due to its use for years.
Abstract: This article presents the simulation, parameterization and optimization of an electromagnet with the C–shaped configuration, intended for the study of magnetic properties of materials. The electromagnet studied consists of a C-shaped yoke, which provides self–shielding for minimizing losses of magnetic flux density, two poles of high magnetic permeability and power coils wound on the poles. The main physical variable studied was the static magnetic flux density in a column within the gap between the poles, with 4cm2 of square cross section and a length of 5cm, seeking a suitable set of parameters that allow us to achieve a uniform magnetic flux density of 1x104 Gaussor values above this in the column, when the system operates at room temperature and with a current consumption not exceeding 5A. By means of a magnetostatic analysis by the finite element method, the magnetic flux density and the distribution of the magnetic field lines were visualized and quantified. From the results obtained by simulating an initial configuration of electromagnet, a structural optimization of the geometry of the adjustable caps for the ends of the poles was performed. The magnetic permeability effect of the soft magnetic materials used in the poles system, such as low– carbon steel (0.08% C), Permalloy (45% Ni, 54.7% Fe) and Mumetal (21.2% Fe, 78.5% Ni), was also evaluated. The intensity and uniformity of the magnetic field in the gap showed a high dependence with the factors described above. The magnetic field achieved in the column was uniform and its magnitude ranged between 1.5x104 Gauss and 1.9x104 Gauss according to the material of the pole used, with the possibility of increasing the magnetic field by choosing a suitable geometry of the cap, introducing a cooling system for the coils and adjusting the spacing between the poles. This makes the device a versatile and scalable tool to generate the magnetic field necessary to perform magnetic characterization of materials by techniques such as vibrating sample magnetometry (VSM), Hall-effect, Kerr-effect magnetometry, among others. Additionally, a CAD design of the modules of the electromagnet is presented in order to facilitate the construction and scaling of the physical device.
Abstract: Border Gateway Protocol (BGP) is the standard routing protocol between various autonomous systems (AS) in the internet. In the event of failure, a considerable delay in the BGP convergence has been shown by empirical measurements. During the convergence time the BGP will repeatedly advertise new routes to some destination and withdraw old ones until it reach a stable state. It has been found that the KEEPALIVE message timer and the HOLD time are tow parameters affecting the convergence speed. This paper aims to find the optimum value for the KEEPALIVE timer and the HOLD time that maximally reduces the convergence time without increasing the traffic. The KEEPALIVE message timer optimal value founded by this paper is 30 second instead of 60 seconds, and the optimal value for the HOLD time is 90 seconds instead of 180 seconds.
Abstract: This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
Abstract: Interpretation of aerial images is an important task in
various applications. Image segmentation can be viewed as the essential
step for extracting information from aerial images. Among many
developed segmentation methods, the technique of clustering has been
extensively investigated and used. However, determining the number
of clusters in an image is inherently a difficult problem, especially
when a priori information on the aerial image is unavailable. This
study proposes a support vector machine approach for clustering
aerial images. Three cluster validity indices, distance-based index,
Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative
measures of the quality of clustering results. Comparisons on the
effectiveness of these indices and various parameters settings on the
proposed methods are conducted. Experimental results are provided
to illustrate the feasibility of the proposed approach.
Abstract: In this paper, an analytical modeling is presentated to
describe the channel noise in GME SGT/CGT MOSFET, based on
explicit functions of MOSFETs geometry and biasing conditions for
all channel length down to deep submicron and is verified with the
experimental data. Results shows the impact of various parameters
such as gate bias, drain bias, channel length ,device diameter and gate
material work function difference on drain current noise spectral
density of the device reflecting its applicability for circuit design
applications.
Abstract: This paper presents the convergence analysis
of a prediction based blind equalizer for IIR channels.
Predictor parameters are estimated by using the recursive
least squares algorithm. It is shown that the prediction
error converges almost surely (a.s.) toward a scalar
multiple of the unknown input symbol sequence. It is
also proved that the convergence rate of the parameter
estimation error is of the same order as that in the iterated
logarithm law.
Abstract: The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.
Abstract: The integrity and issues related to electrostatic performance associated with scaling Si MOSFET bulk sub 10nm channel length promotes research in new device architectures such as SOI, double gate and GAA MOSFET. In this paper, we present some novel characteristic of horizontal rectangular gate\gate all around MOSFETs with dual metal of gate we obtained using SILVACO TCAD tools. We will also exhibit some simulation results we obtained relating to the influence of some parameters variation on our structure, that having a direct impact on their threshold voltage and drain current. In addition, our TFET showed reasonable ION/IOFF ratio of (104) and low drain induced barrier lowering (DIBL) of 39 mV/V.
Abstract: At the present, auto part industries have become higher challenge in strategy market. As this consequence, manufacturers need to have better response to customers in terms of quality, cost, and delivery time. Moreover, they need to have a good management in factory to comply with international standard maximum capacity and lower cost. This would lead companies to have to order standard part from aboard and become the major cost of inventory. The development of auto part research by recycling materials experiment is to compare the auto parts from recycle materials to international auto parts (CKD). Factors studied in this research were the recycle material ratios of PU-foam, felt, and fabric. Results of recycling materials were considered in terms of qualities and properties on the parameters such as weight, sound absorption, water absorption, tensile strength, elongation, and heat resistance with the CKD. The results were showed that recycling materials would be used to replace for the CKD.
Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.
Abstract: Design and modeling of nonlinear systems require the
knowledge of all inside acting parameters and effects. An empirical
alternative is to identify the system-s transfer function from input and
output data as a black box model. This paper presents a procedure
using least squares algorithm for the identification of a feed drive
system coefficients in time domain using a reduced model based on
windowed input and output data. The command and response of the
axis are first measured in the first 4 ms, and then least squares are
applied to predict the transfer function coefficients for this
displacement segment. From the identified coefficients, the next
command response segments are estimated. The obtained results
reveal a considerable potential of least squares method to identify the
system-s time-based coefficients and predict accurately the command
response as compared to measurements.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.
Abstract: The equilibrium, thermodynamics and kinetics of the
biosorption of Cd (II) and Pb(II) by a Spore Forming Bacillus (MGL
75) were investigated at different experimental conditions. The
Langmuir and Freundlich, and Dubinin-Radushkevich (D-R)
equilibrium adsorption models were applied to describe the
biosorption of the metal ions by MGL 75 biomass. The Langmuir
model fitted the equilibrium data better than the other models.
Maximum adsorption capacities q max for lead (II) and cadmium (II)
were found equal to 158.73mg/g and 91.74 mg/g by Langmuir model.
The values of the mean free energy determined with the D-R equation
showed that adsorption process is a physiosorption process. The
thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°),
and entropy (ΔS°) changes were also calculated, and the values
indicated that the biosorption process was exothermic and
spontaneous. Experiment data were also used to study biosorption
kinetics using pseudo-first-order and pseudo-second-order kinetic
models. Kinetic parameters, rate constants, equilibrium sorption
capacities and related correlation coefficients were calculated and
discussed. The results showed that the biosorption processes of both
metal ions followed well pseudo-second-order kinetics.
Abstract: This frame work describes a computationally more
efficient and adaptive threshold estimation method for image
denoising in the wavelet domain based on Generalized Gaussian
Distribution (GGD) modeling of subband coefficients. In this
proposed method, the choice of the threshold estimation is carried out
by analysing the statistical parameters of the wavelet subband
coefficients like standard deviation, arithmetic mean and geometrical
mean. The noisy image is first decomposed into many levels to
obtain different frequency bands. Then soft thresholding method is
used to remove the noisy coefficients, by fixing the optimum
thresholding value by the proposed method. Experimental results on
several test images by using this method show that this method yields
significantly superior image quality and better Peak Signal to Noise
Ratio (PSNR). Here, to prove the efficiency of this method in image
denoising, we have compared this with various denoising methods
like wiener filter, Average filter, VisuShrink and BayesShrink.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.