Abstract: Injection forging is a Nett-shape manufacturing
process in which one or two punches move axially causing a radial
flow into a die cavity in a form which is prescribed by the exitgeometry,
such as pulley, flanges, gears and splines on a shaft. This
paper presents an experimental and numerical study of the injection
forging of splines in terms of load requirement and material flow.
Three dimensional finite element analyses are used to investigate the
effect of some important parameters in this process. The experiment
has been carried out using solid commercial lead billets with two
different billet diameters and four different dies.
Abstract: The purpose of this work is measurement of the
system presampling MTF of a variable resolution x-ray (VRX) CT
scanner. In this paper, we used the parameters of an actual VRX CT
scanner for simulation and study of effect of different focal spot sizes
on system presampling MTF by Monte Carlo method (GATE
simulation software). Focal spot size of 0.6 mm limited the spatial
resolution of the system to 5.5 cy/mm at incident angles of below 17º
for cell#1. By focal spot size of 0.3 mm the spatial resolution
increased up to 11 cy/mm and the limiting effect of focal spot size
appeared at incident angles of below 9º. The focal spot size of 0.3
mm could improve the spatial resolution to some extent but because
of magnification non-uniformity, there is a 10 cy/mm difference
between spatial resolution of cell#1 and cell#256. The focal spot size
of 0.1 mm acted as an ideal point source for this system. The spatial
resolution increased to more than 35 cy/mm and at all incident angles
the spatial resolution was a function of incident angle. By the way
focal spot size of 0.1 mm minimized the effect of magnification nonuniformity.
Abstract: The dental composites are preferably used as filling
materials due to their esthetic appearances. Nevertheless one of the
major problems, during the application of the dental composites, is
shape change named as “polymerisation shrinkage" affecting clinical
success of the dental restoration while photo-polymerisation.
Polymerisation shrinkage of composites arises basically from the
formation of a polymer due to the monomer transformation which
composes of an organic matrix phase. It was sought, throughout this
study, to detect and evaluate the structural polymerisation shrinkage
of prepared dental composites in order to optimize the effects of
various fillers included in hydroxyapatite (HA)-reinforced dental
composites and hence to find a means to modify the properties of
these dental composites prepared with defined parameters. As a
result, the shrinkage values of the experimental dental composites
were decreased by increasing the filler content of composites and the
composition of different fillers used had effect on the shrinkage of
the prepared composite systems.
Abstract: Nowadays, butyl acetate, a pineapple flavor has been applied widely in food, beverage, cosmetic and pharmaceutical industries. In this study, Butyl acetate, a flavor ester was successfully synthesized via green synthesis of enzymatic reaction route. Commercial immobilized lipase from Rhizomucor miehei (Lipozyme RMIM) was used as biocatalyst in the esterification reaction between acetic acid and butanol. Various reaction parameters such as reaction time (RT), temperature (T) and amount of enzyme (E) were chosen to optimize the reaction synthesis in solvent-free system. The optimum condition to produce butyl acetate was at reaction time (RT), 18 hours; temperature (T), 37°C and amount of enzyme, 25 % (w/w of total substrate). Analysis of yield showed that at optimum condition, >78 % of butyl acetate was produced. The product was confirmed as butyl acetate from FTIR analysis whereby the presence of an ester group was observed at wavenumber of 1742 cm-1.
Abstract: The new technology of fuzzy neural networks for identification of parameters for mathematical models of geofields is proposed and checked. The effectiveness of that soft computing technology is demonstrated, especially in the early stage of modeling, when the information is uncertain and limited.
Abstract: The modeling of inelastic behavior of plastic materials requires measurements providing information on material response to different multiaxial loading conditions. Different triaxiality conditions and values of Lode parameters have to be
covered for complex description of the material plastic behavior.
Samples geometries providing material plastic behavoiur over the range of interest are proposed with the use of FEM analysis. Round samples with 3 different notches and smooth surface are used
together with butterfly type of samples tested at angle ranging for 0 to
90°. Identification of ductile damage parameters is carried out on
the basis of obtained experimental data for austenitic stainless steel.
The obtained material plastic damage parameters are subsequently applied to FEM simulation of notched CT normally samples used for
fracture mechanics testing and results from the simulation are
compared with real tests.
Abstract: The energy consumption and delay in read/write
operation of conventional SRAM is investigated analytically as well
as by simulation. Explicit analytical expressions for the energy
consumption and delay in read and write operation as a function of
device parameters and supply voltage are derived. The expressions are
useful in predicting the effect of parameter changes on the energy
consumption and speed as well as in optimizing the design of
conventional SRAM. HSPICE simulation in standard 0.25μm CMOS
technology confirms precision of analytical expressions derived from
this paper.
Abstract: Modeling of a manufacturing system enables one to
identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper
proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a
static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few
parameters such as utilization, cycle time, throughput, and batch size.
The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far
below the limit value 32%. Therefore, the model developed in this
study is a valuable alternative model in evaluating a manufacturing system
Abstract: We have developed a computer program consisting of
6 subtests assessing the children hand dexterity applicable in the
rehabilitation medicine. We have carried out a normative study on a
representative sample of 285 children aged from 7 to 15 (mean age
11.3) and we have proposed clinical standards for three age groups
(7-9, 9-11, 12-15 years). We have shown statistical significance of
differences among the corresponding mean values of the task time
completion. We have also found a strong correlation between the task
time completion and the age of the subjects, as well as we have
performed the test-retest reliability checks in the sample of 84
children, giving the high values of the Pearson coefficients for the
dominant and non-dominant hand in the range 0.740.97 and
0.620.93, respectively.
A new MATLAB-based programming tool aiming at analysis of
cardiologic RR intervals and blood pressure descriptors, is worked
out, too. For each set of data, ten different parameters are extracted: 2
in time domain, 4 in frequency domain and 4 in Poincaré plot
analysis. In addition twelve different parameters of baroreflex
sensitivity are calculated. All these data sets can be visualized in time
domain together with their power spectra and Poincaré plots. If
available, the respiratory oscillation curves can be also plotted for
comparison. Another application processes biological data obtained
from BLAST analysis.
Abstract: In this paper, we analyze the effect of noise in a single- ended input differential amplifier working at high frequencies. Both extrinsic and intrinsic noise are analyzed using time domain method employing techniques from stochastic calculus. Stochastic differential equations are used to obtain autocorrelation functions of the output noise voltage and other solution statistics like mean and variance. The analysis leads to important design implications and suggests changes in the device parameters for improved noise characteristics of the differential amplifier.
Abstract: In this paper usefulness of quasi-Newton iteration
procedure in parameters estimation of the conditional variance
equation within BHHH algorithm is presented. Analytical solution of
maximization of the likelihood function using first and second
derivatives is too complex when the variance is time-varying. The
advantage of BHHH algorithm in comparison to the other
optimization algorithms is that requires no third derivatives with
assured convergence. To simplify optimization procedure BHHH
algorithm uses the approximation of the matrix of second derivatives
according to information identity. However, parameters estimation in
a/symmetric GARCH(1,1) model assuming normal distribution of
returns is not that simple, i.e. it is difficult to solve it analytically.
Maximum of the likelihood function can be founded by iteration
procedure until no further increase can be found. Because the
solutions of the numerical optimization are very sensitive to the
initial values, GARCH(1,1) model starting parameters are defined.
The number of iterations can be reduced using starting values close
to the global maximum. Optimization procedure will be illustrated in
framework of modeling volatility on daily basis of the most liquid
stocks on Croatian capital market: Podravka stocks (food industry),
Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla
stocks (information-s-communications industry).
Abstract: Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.
Abstract: The relationship between tropical cyclogenesis and solar activity is addressed in this paper, analyzing the relationship between important parameters in the evolution of tropical cyclones as the CAPE, wind shear and relative vorticity, and the Dst geomagnetic index as a parameter of solar activity. The apparent relationship between all this phenomena has a different response depending on the phase of the solar cycles.
Abstract: Energy dissipation in drops has been investigated by
physical models. After determination of effective parameters on the
phenomenon, three drops with different heights have been
constructed from Plexiglas. They have been installed in two existing
flumes in the hydraulic laboratory. Several runs of physical models
have been undertaken to measured required parameters for
determination of the energy dissipation. Results showed that the
energy dissipation in drops depend on the drop height and discharge.
Predicted relative energy dissipations varied from 10.0% to 94.3%.
This work has also indicated that the energy loss at drop is mainly
due to the mixing of the jet with the pool behind the jet that causes
air bubble entrainment in the flow. Statistical model has been
developed to predict the energy dissipation in vertical drops denotes
nonlinear correlation between effective parameters. Further an
artificial neural networks (ANNs) approach was used in this paper to
develop an explicit procedure for calculating energy loss at drops
using NeuroSolutions. Trained network was able to predict the
response with R2 and RMSE 0.977 and 0.0085 respectively. The
performance of ANN was found effective when compared to
regression equations in predicting the energy loss.
Abstract: In this paper, we will implement three-dimensional pursuit guidance law with feedback linearization control method and study the effects of parameters. First, we introduce guidance laws and equations of motion of a missile. Pursuit guidance law is our highlight. We apply feedback linearization control method to obtain the accelerations to implement pursuit guidance law. The solution makes warhead direction follow with line-of-sight. Final, the simulation results show that the exact solution derived in this paper is correct and some factors e.g. control gain, time delay, are important to implement pursuit guidance law.
Abstract: This paper analyses the unsteady, two-dimensional
stagnation point flow of an incompressible viscous fluid over a flat
sheet when the flow is started impulsively from rest and at the same
time, the sheet is suddenly stretched in its own plane with a velocity
proportional to the distance from the stagnation point. The partial
differential equations governing the laminar boundary layer forced
convection flow are non-dimensionalised using semi-similar
transformations and then solved numerically using an implicit finitedifference
scheme known as the Keller-box method. Results
pertaining to the flow and heat transfer characteristics are computed
for all dimensionless time, uniformly valid in the whole spatial region
without any numerical difficulties. Analytical solutions are also
obtained for both small and large times, respectively representing the
initial unsteady and final steady state flow and heat transfer.
Numerical results indicate that the velocity ratio parameter is found
to have a significant effect on skin friction and heat transfer rate at
the surface. Furthermore, it is exposed that there is a smooth
transition from the initial unsteady state flow (small time solution) to
the final steady state (large time solution).
Abstract: With optimized bandwidth and latency discrepancy ratios, Node Gain Scores (NGSs) are determined and used as a basis for shaping the max-heap overlay. The NGSs - determined as the respective bandwidth-latency-products - govern the construction of max-heap-form overlays. Each NGS is earned as a synergy of discrepancy ratio of the bandwidth requested with respect to the estimated available bandwidth, and latency discrepancy ratio between the nodes and the source node. The tree leads to enhanceddelivery overlay multicasting – increasing packet delivery which could, otherwise, be hindered by induced packet loss occurring in other schemes not considering the synergy of these parameters on placing the nodes on the overlays. The NGS is a function of four main parameters – estimated available bandwidth, Ba; individual node's requested bandwidth, Br; proposed node latency to its prospective parent (Lp); and suggested best latency as advised by source node (Lb). Bandwidth discrepancy ratio (BDR) and latency discrepancy ratio (LDR) carry weights of α and (1,000 - α ) , respectively, with arbitrary chosen α ranging between 0 and 1,000 to ensure that the NGS values, used as node IDs, maintain a good possibility of uniqueness and balance between the most critical factor between the BDR and the LDR. A max-heap-form tree is constructed with assumption that all nodes possess NGS less than the source node. To maintain a sense of load balance, children of each level's siblings are evenly distributed such that a node can not accept a second child, and so on, until all its siblings able to do so, have already acquired the same number of children. That is so logically done from left to right in a conceptual overlay tree. The records of the pair-wise approximate available bandwidths as measured by a pathChirp scheme at individual nodes are maintained. Evaluation measures as compared to other schemes – Bandwidth Aware multicaSt architecturE (BASE), Tree Building Control Protocol (TBCP), and Host Multicast Tree Protocol (HMTP) - have been conducted. This new scheme generally performs better in terms of trade-off between packet delivery ratio; link stress; control overhead; and end-to-end delays.
Abstract: Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.
Abstract: Direct fermentation of 226 white rose tapioca stem to
ethanol by Fusarium oxysporum was studied in a batch reactor.
Fermentation of ethanol can be achieved by sequential pretreatment
using dilute acid and dilute alkali solutions using 100 mesh tapioca
stem particles. The quantitative effects of substrate concentration, pH
and temperature on ethanol concentration were optimized using a full
factorial central composite design experiment. The optimum process
conditions were then obtained using response surface methodology.
The quadratic model indicated that substrate concentration of 33g/l,
pH 5.52 and a temperature of 30.13oC were found to be optimum for
maximum ethanol concentration of 8.64g/l. The predicted optimum
process conditions obtained using response surface methodology was
verified through confirmatory experiments. Leudeking-piret model
was used to study the product formation kinetics for the production
of ethanol and the model parameters were evaluated using
experimental data.
Abstract: On the basis of Bayesian inference using the
maximizer of the posterior marginal estimate, we carry out phase
unwrapping using multiple interferograms via generalized mean-field
theory. Numerical calculations for a typical wave-front in remote
sensing using the synthetic aperture radar interferometry, phase
diagram in hyper-parameter space clarifies that the present method
succeeds in phase unwrapping perfectly under the constraint of
surface- consistency condition, if the interferograms are not corrupted
by any noises. Also, we find that prior is useful for extending a phase
in which phase unwrapping under the constraint of the
surface-consistency condition. These results are quantitatively
confirmed by the Monte Carlo simulation.