Abstract: As we know, most differential equations concerning
physical phenomenon could not be solved by analytical method. Even if we use Series Method, some times we need an appropriate change of variable, and even when we can, their closed form solution may be
so complicated that using it to obtain an image or to examine the structure of the system is impossible. For example, if we consider Schrodinger equation, i.e.,
We come to a three-term recursion relations, which work with it takes, at least, a little bit time to get a series solution[6]. For this
reason we use a change of variable such as or when we consider the orbital angular momentum[1], it will be
necessary to solve. As we can observe, working with this equation is tedious. In this paper, after introducing Clenshaw method, which is a kind of Spectral method, we try to solve some of such equations.
Abstract: This paper presents data annotation models at
five levels of granularity (database, relation, column, tuple, and cell) of relational data to address the problem of unsuitability of most relational databases to express annotations. These models
do not require any structural and schematic changes to the
underlying database. These models are also flexible, extensible,
customizable, database-neutral, and platform-independent. This paper also presents an SQL-like query language, named Annotation Query Language (AnQL), to query annotation documents. AnQL is simple to understand and exploits the already-existent wide knowledge and skill set of SQL.
Abstract: The aim of the paper work is to investigate and predict
the static performance of journal bearing in turbulent flow condition
considering micropolar lubrication. The Reynolds equation has been
modified considering turbulent micropolar lubrication and is solved
for steady state operations. The Constantinescu-s turbulence model is
adopted using the coefficients. The analysis has been done for a
parallel and inertia less flow. Load capacity and friction factor have
been evaluated for various operating parameters.
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: Biplot can be used to evaluate cultivars for their oil
percent potential and stability and to evaluate trial sites for their
discriminating ability and representativeness. Multi-environmental
trial (MET) data for oil percent of 10 open pollinating sunflower
cultivars were analyzed to investigate the genotype-environment
interactions. The genotypes were evaluated in four locations with
different climatic conditions in Iran in 2010. In each location, a
Randomized Complete Block design with four replications was used.
According to both mean and stability, Zaria, Master and R453, had
highest performances among all cultivars. The graphical analysis
identified best cultivar for each environment. Cultivars Berezans and
Record performed best in Khoy and Islamabad. Zaria and R453 were
the best genotypes in Sari and Karaj followed by Master and Favorit.
The GGE bi-plot indicated two mega-environments, group one
contained Karaj, Khoy and Islamabad and the second group
contained Sari. The best discriminating location was Karaj followed
with Khoy, Islamabad and Sari. The best representative genotypes
were Zaria, R453, Master and Favorit. Ranking of ten cultivars based
their oil percent was as Zaria > R453 ≈ Master ≈ Favorit > Record ≈
Berezans > Sor > Lakumka > Bulg3 > Bulg5.
Abstract: Stairway Ushtobin Village is one of the five villages with original and sustainable architecture in Northwest of Iran along the border of Armenia, which has been able to maintain its environment and sustainable ecosystem. Studying circulation, function and scale (grand, medium and minor) of space, ratio of full and empty spaces, number and height of stairs, ratio of compound volume to luxury spaces, openings, type of local masonry (stone, mud, wood) and form of covering elements have been carried out in four houses of this village comparatively as some samples in this article, and furthermore, this article analyzes that the architectural shapes and organic texture of the village meet the needs of cold and dry climate. Finally, some efficient plans are offered suiting the present needs of the village to have a sustainable architecture.
Abstract: This article explores the self-identity of the Kazakh
people by way of identifying the roots of self-understanding in
Kazakh culture. Unfortunately, Western methods of ethno
psychology cannot fully capture what is unique about identity in
Kazakh culture. Although Kazakhstan is the ninth largest country in
terms of geographical space, Kazakh cultural identity is not wellknown
in the West. In this article we offer an account of the national
psychological features of the Kazakh people, in order to reveal the
spiritual, mental, ethical dimensions of modern Kazakhs. These
factors play a central role in the revival of forms of identity that are
central to the Kazakh people.
Abstract: In this paper, numerical simulations are performed to investigate the effect of disturbance block on flow field of the classical square lid-driven cavity. Attentions are focused on vortex formation and studying the effect of block position on its structure. Corner vortices are different upon block position and new vortices are produced because of the block. Finite volume method is used to solve Navier-Stokes equations and PISO algorithm is employed for the linkage of velocity and pressure. Verification and grid independency of results are reported. Stream lines are sketched to visualize vortex structure in different block positions.
Abstract: A new hybrid method to realise high-precision
distortion determination for optical ultra-precision 3D measurement
systems based on stereo cameras using active light projection is
introduced. It consists of two phases: the basic distortion
determination and the refinement. The refinement phase of the
procedure uses a plane surface and projected fringe patterns as
calibration tools to determine simultaneously the distortion of both
cameras within an iterative procedure. The new technique may be
performed in the state of the device “ready for measurement" which
avoids errors by a later adjustment. A considerable reduction of
distortion errors is achieved and leads to considerable improvements
of the accuracy of 3D measurements, especially in the precise
measurement of smooth surfaces.
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: The trend in the world of Information Technology
(IT) is getting increasingly large and difficult projects rather than
smaller and easier. However, the data on large-scale IT project
success rates provide cause for concern. This paper seeks to answer
why large-scale IT projects are different from and more difficult than
other typical engineering projects. Drawing on the industrial
experience, a compilation of the conditions that influence failure is
presented. With a view to improve success rates solutions are
suggested.
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: Water samples were collected from river Pandu at six
stations where human and animal activities were high. Composite
samples were analyzed for dissolved oxygen (DO), biochemical
oxygen demand (BOD), chemical oxygen demand (COD) , pH values
during dry and wet seasons as well as the harmattan period. The total
data points were used to establish relationships between the
parameters and data were also subjected to statistical analysis and
expressed as mean ± standard error of mean (SEM) at a level of
significance of p
Abstract: Accurate demand forecasting is one of the most key
issues in inventory management of spare parts. The problem of
modeling future consumption becomes especially difficult for lumpy
patterns, which characterized by intervals in which there is no
demand and, periods with actual demand occurrences with large
variation in demand levels. However, many of the forecasting
methods may perform poorly when demand for an item is lumpy.
In this study based on the characteristic of lumpy demand patterns
of spare parts a hybrid forecasting approach has been developed,
which use a multi-layered perceptron neural network and a
traditional recursive method for forecasting future demands. In the
described approach the multi-layered perceptron are adapted to
forecast occurrences of non-zero demands, and then a conventional
recursive method is used to estimate the quantity of non-zero
demands. In order to evaluate the performance of the proposed
approach, their forecasts were compared to those obtained by using
Syntetos & Boylan approximation, recently employed multi-layered
perceptron neural network, generalized regression neural network
and elman recurrent neural network in this area. The models were
applied to forecast future demand of spare parts of Arak
Petrochemical Company in Iran, using 30 types of real data sets. The
results indicate that the forecasts obtained by using our proposed
mode are superior to those obtained by using other methods.
Abstract: Precast concrete has been widely adopted in public
housing construction of Hong Kong since the mid-1980s. While
pre-casting is considered an environmental friendly solution, there is
lack of study to investigate the life cycle performance of precast
concrete units. This study aims to bridge the knowledge gap by
providing a comprehensive life cycle assessment (LCA) study for two
precast elements namely façade and bathroom. The results show that
raw material is the most significant contributor of environmental
impact accounting for about 90% to the total impact. Furthermore,
human health is more affected by the production of precast concrete
than the ecosystems.
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: Binary Decision Diagrams (BDDs) are useful data
structures for symbolic Boolean manipulations. BDDs are used in
many tasks in VLSI/CAD, such as equivalence checking, property
checking, logic synthesis, and false paths. In this paper we describe a
new approach for the realization of a BDD package. To perform
manipulations of Boolean functions, the proposed approach does not
depend on the recursive synthesis operation of the IF-Then-Else
(ITE). Instead of using the ITE operation, the basic synthesis
algorithm is done using Boolean NOR operation.
Abstract: Gas turbine systems with wet compression have a
potential for future power generation, since they can offer a high
efficiency and a high specific power with a relatively low cost. In this
study influence of ambient condition on the performance of the wet
compression process is investigated with a non-equilibrium analytical
modeling based on droplet evaporation. Transient behaviors of droplet
diameter and temperature of mixed air are investigated for various
ambient temperatures. Special attention is paid for the effects of
ambient temperature, pressure ratio, and water injection ratios on the
important wet compression variables including compressor outlet
temperature and compression work. Parametric studies show that
downing of the ambient temperature leads to lower compressor outlet
temperature and consequently lower consumption of compression
work even in wet compression processes.
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.