Abstract: According to celebrated Hurwitz theorem, there exists
four division algebras consisting of R (real numbers), C (complex
numbers), H (quaternions) and O (octonions). Keeping in view
the utility of octonion variable we have tried to extend the three
dimensional vector analysis to seven dimensional one. Starting with
the scalar and vector product in seven dimensions, we have redefined
the gradient, divergence and curl in seven dimension. It is shown
that the identity n(n - 1)(n - 3)(n - 7) = 0 is satisfied only
for 0, 1, 3 and 7 dimensional vectors. We have tried to write all
the vector inequalities and formulas in terms of seven dimensions
and it is shown that same formulas loose their meaning in seven
dimensions due to non-associativity of octonions. The vector formulas
are retained only if we put certain restrictions on octonions and split
octonions.
Abstract: This communication is intended to provide some issues for thought on the importance of implementation of Blended Learning in traditional universities, particularly in the Spanish university system. In this respect, we believe that virtual environments are likely to meet some of the needs raised by the Bologna agreement, trying to maintain the quality of teaching and at the same time taking advantage of the functionalities that virtual learning platforms offer. We are aware that an approach of learning from an open and constructivist nature in universities is a complex process that faces significant technological, administrative and human barriers. Therefore, in order to put plans in our universities, it is necessary to analyze the state of the art of some indicators relating to the use of ICT, with special attention to virtual teaching and learning, so that we can identify the main obstacles and design adaptive strategies for their full integration in the education system. Finally, we present major initiatives launched in the European and state framework for the effective implementation of new virtual environments in the area of higher education.
Abstract: In a metal forming process, the friction between the
material and the tools influences the process by modifying the stress
distribution of the workpiece. This frictional behaviour is often taken
into account by using a constant coefficient of friction in the finite
element simulations of sheet metal forming processes. However,
friction coefficient varies in time and space with many parameters.
The Stribeck friction model is investigated in this study to predict
springback behaviour of AA6061-T4 sheets during V-bending
process. The coefficient of friction in Stribeck curve depends on
sliding velocity and contact pressure. The plane-strain bending
process is simulated in ABAQUS/Standard. We compared the
computed punch load-stroke curves and springback related to the
constant coefficient of friction with the defined friction model. The
results clearly showed that the new friction model provides better
agreement between experiments and results of numerical simulations.
The influence of friction models on stress distribution in the
workpiece is also studied numerically
Abstract: We investigate nonfactorizable contributions to
D → ¤Ç¤Ç decay modes. We perform isospin analysis of the
nonfactorizable contributions to these decays. Obtaining the
factorizable contributions from spectator-quark diagrams using
= 3 C N , we determine nonfactorizable amplitudes for these decays
and predict their branching ratios.
Abstract: This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.
Abstract: In this paper comparison of Reflector Antenna
analyzing techniques based on wave and ray nature of optics is
presented for an offset reflector antenna using GRASP (General
Reflector antenna Analysis Software Package) software. The results
obtained using PO (Physical Optics), PTD (Physical theory of
Diffraction), and GTD (Geometrical Theory of Diffraction) are
compared. The validity of PO and GTD techniques in regions around
the antenna, caustic behavior of GTD in main beam, and deviation of
GTD in case of near-in sidelobes of radiation pattern are discussed.
The comparison for far-out sidelobes predicted by PO, PO + PTD
and GTD is described. The effect of Direct Radiations from feed
which results in feed selection for the system is addressed.
Abstract: The problem of incompressible steady flow simulation around an airfoil is discussed. For some simplest airfoils (circular, elliptical, Zhukovsky airfoils) the exact solution is known from complex analysis. It allows to compute the intensity of vortex layer which simulates the airfoil. Some modifications of the vortex element method are proposed and test computations are carried out. It-s shown that the these approaches are much more effective in comparison with the classical numerical scheme.
Abstract: We present an Electronic Nose (ENose), which is
aimed at identifying the presence of one out of two gases, possibly
detecting the presence of a mixture of the two. Estimation of the
concentrations of the components is also performed for a volatile
organic compound (VOC) constituted by methanol and acetone, for
the ranges 40-400 and 22-220 ppm (parts-per-million), respectively.
Our system contains 8 sensors, 5 of them being gas sensors (of the
class TGS from FIGARO USA, INC., whose sensing element is a tin
dioxide (SnO2) semiconductor), the remaining being a temperature
sensor (LM35 from National Semiconductor Corporation), a
humidity sensor (HIH–3610 from Honeywell), and a pressure sensor
(XFAM from Fujikura Ltd.).
Our integrated hardware–software system uses some machine
learning principles and least square regression principle to identify at
first a new gas sample, or a mixture, and then to estimate the
concentrations. In particular we adopt a training model using the
Support Vector Machine (SVM) approach with linear kernel to teach
the system how discriminate among different gases. Then we apply
another training model using the least square regression, to predict
the concentrations.
The experimental results demonstrate that the proposed
multiclassification and regression scheme is effective in the
identification of the tested VOCs of methanol and acetone with
96.61% correctness. The concentration prediction is obtained with
0.979 and 0.964 correlation coefficient for the predicted versus real
concentrations of methanol and acetone, respectively.
Abstract: In the present analysis an unsteady laminar
forced convection water boundary layer flow is considered.
The fluid properties such as viscosity and Prandtl number are
taken as variables such that those are inversely proportional to
temperature. By using quasi-linearization technique the nonlinear
coupled partial differential equations are linearized and
the numerical solutions are obtained by using implicit finite
difference scheme with the appropriate selection of step sizes.
Non-similar solutions have been obtained from the starting
point of the stream-wise coordinate to the point where skin
friction value vanishes. The effect non-uniform mass transfer
along the surface of the cylinder through slot is studied on the
skin friction and heat transfer coefficients.
Abstract: In medical therapy, laser has been widely used to conduct cosmetic, tumor and other treatments. During the process of laser irradiation, there may be thermal damage caused by excessive laser exposure. Thus, the establishment of a complete thermal analysis model is clinically helpful to physicians in reference data. In this study, porcine liver in place of tissue was subjected to laser irradiation to set up the experimental data considering the explored impact on surface thermal field and thermal damage region under different conditions of power, laser irradiation time, and distance between laser and porcine liver. In the experimental process, the surface temperature distribution of the porcine lever was measured by the infrared thermal imager. In the part of simulation, the bio heat transfer Pennes-s equation was solved by software SYSWELD applying in welding process. The double ellipsoid function as a laser source term is firstly considered in the prediction for surface thermal field and internal tissue damage. The simulation results are compared with the experimental data to validate the mathematical model established here in.
Abstract: This article deals with the numerical simulation of the
floor heating convector in 3D. Presented convector can operate in
two modes – cooling mode and heating mode. This initial numerical
simulation is focused on cooling mode of the convector. Models with
different temperature of the fins are compared and three various
shapes of the fins are examined as well. The objective of the work is
to predict air flow and heat transfer inside convector for further
optimalization of these devices. For the numerical simulation was
used commercial software Ansys Fluent.
Abstract: Fuzzy logic approach is used in this study to predict
the tractive performance in terms of traction force, and motion
resistance for an intelligent air cushion track vehicle while it operates
in the swamp peat. The system is effective to control the intelligent
air –cushion system with measuring the vehicle traction force (TF),
motion resistance (MR), cushion clearance height (CH) and cushion
pressure (CP). Sinkage measuring sensor, magnetic switch, pressure
sensor, micro controller, control valves and battery are incorporated
with the Fuzzy logic system (FLS) to investigate experimentally the
TF, MR, CH, and CP. In this study, a comparison for tractive
performance of an intelligent air cushion track vehicle has been
performed with the results obtained from the predicted values of FLS
and experimental actual values. The mean relative error of actual and
predicted values from the FLS model on traction force, and total
motion resistance are found as 5.58 %, and 6.78 % respectively. For
all parameters, the relative error of predicted values are found to be
less than the acceptable limits. The goodness of fit of the prediction
values from the FLS model on TF, and MR are found as 0.90, and
0.98 respectively.
Abstract: Aggression is a multi- factorial concept and multilevel
in nature. The Young Adolescent is being influenced by family,
school and community. This paper is aimed to determine the
following: aggression level among young adolescents, difference of
level of aggression on school and year levels and to determine the
correlates of aggression. There were 142 high school students from
two different national highs schools (Region 3 and National Capital
Region).Convenience sampling was use in this study. The following
measures were used namely: Aggression Scale, Parental Support
Fighting Scale, Positive Behavior Scale and Exposure to Violence
and Trauma questionnaire. There was no significant difference in
aggression level among different year level and schools. The
findings of the study suggested that high level of community violence
and having low parental support for non-aggressive behavior
contribute to the prediction of aggression.
Abstract: SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.
Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: Inspired by the recent experiments [1]-[3] indicating
unusual doubly magic nucleus 24O which lies just at the neutron
drip-line and encouraged by the success of our relativistic mean-field
(RMF) plus state dependent BCS approach for the description of
the ground state properties of the drip-line nuclei [23]-[27], we have
further employed this approach, across the entire periodic table, to
explore the unusual shell closures in exotic nuclei. In our RMF+BCS
approach the single particle continuum corresponding to the RMF is
replaced by a set of discrete positive energy states for the calculations
of pairing energy. Detailed analysis of the single particle spectrum,
pairing energies and densities of the nuclei predict the unusual proton
shell closures at Z = 6, 14, 16, 34, and unusual neutron shell closures
at N = 6, 14, 16, 34, 40, 70, 112.
Abstract: Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.
Abstract: An HPLC-UV analytical method was developed to
determine ethylenediaminetetraacetic acid (EDTA) in dairy
wastewater and surface water. The optimizing separation was achieved
by reversed–phase ion-pair liquid chromatography on a C18 column
using methanol as mobile phase solvent, tetrabutylammonium bromide
as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate
of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca,
Mg or NO3
- was detected. Method performance was evaluated in terms
of linearity, repeatability and reproducibility. The method detection
limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~
261 μg L-1 at a large dairy site. A change of EDTA concentration was
observed downstream of the dairy effluent discharge, but this was well
under the predicted no effect concentration for aquatic ecosystem.
Abstract: The use of a Geographic Information System (GIS) in
roadway lighting to show the state of street-lighting and nighttime
accident is demonstrated. Geographical maps were generated
showing colored streets based on how much of the street's length is
illuminated. The night to daytime accidents ratio at intersections
were found along with the state of lighting at those intersections.
The result is a method to show the state of street-lighting at roads and
intersections and a quick guide for decision makers to implement
strategies for better street-lighting to reduce night time traffic
accidents in a particular district.
Abstract: We depend upon explanation in order to “make sense"
out of our world. And, making sense is all the more important when
dealing with change. But, what happens if our explanations are
wrong? This question is examined with respect to two types of
explanatory model. Models based on labels and categories we shall
refer to as “representations." More complex models involving
stories, multiple algorithms, rules of thumb, questions, ambiguity we
shall refer to as “compressions." Both compressions and
representations are reductions. But representations are far more
reductive than compressions. Representations can be treated as a set
of defined meanings – coherence with regard to a representation is
the degree of fidelity between the item in question and the definition
of the representation, of the label. By contrast, compressions contain
enough degrees of freedom and ambiguity to allow us to make
internal predictions so that we may determine our potential actions in
the possibility space. Compressions are explanatory via mechanism.
Representations are explanatory via category. Managers are often
confusing their evocation of a representation (category inclusion) as
the creation of a context of compression (description of mechanism).
When this type of explanatory error occurs, more errors follow. In
the drive for efficiency such substitutions are all too often proclaimed
– at the manager-s peril..