Abstract: An iterative definition of any n variable mean function is given in this article, which iteratively uses the two-variable form of the corresponding two-variable mean function. This extension method omits recursivity which is an important improvement compared with certain recursive formulas given before by Ando-Li-Mathias, Petz- Temesi. Furthermore it is conjectured here that this iterative algorithm coincides with the solution of the Riemann centroid minimization problem. Certain simulations are given here to compare the convergence rate of the different algorithms given in the literature. These algorithms will be the gradient and the Newton mehod for the Riemann centroid computation.
Abstract: The aim of this paper is to express the input-output
matrix as a linear ordering problem which is classified as an NP-hard
problem. We then use a Tabu search algorithm to find the best
permutation among sectors in the input-output matrix that will give
an optimal solution. This optimal permutation can be useful in
designing policies and strategies for economists and government in
their goal of maximizing the gross domestic product.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: This paper presents comparative study on recent
integer DCTs and a new method to construct a low sensitive structure
of integer DCT for colored input signals. The method refers to
sensitivity of multiplier coefficients to finite word length as an
indicator of how word length truncation effects on quality of output
signal. The sensitivity is also theoretically evaluated as a function of
auto-correlation and covariance matrix of input signal. The structure of
integer DCT algorithm is optimized by combination of lower sensitive
lifting structure types of IRT. It is evaluated by the sensitivity of
multiplier coefficients to finite word length expression in a function of
covariance matrix of input signal. Effectiveness of the optimum
combination of IRT in integer DCT algorithm is confirmed by quality
improvement comparing with existing case. As a result, the optimum
combination of IRT in each integer DCT algorithm evidently improves
output signal quality and it is still compatible with the existing one.
Abstract: Retrieval image by shape similarity, given a template
shape is particularly challenging, owning to the difficulty to derive a
similarity measurement that closely conforms to the common
perception of similarity by humans. In this paper, a new method for the
representation and comparison of shapes is present which is based on
the shape matrix and snake model. It is scaling, rotation, translation
invariant. And it can retrieve the shape images with some missing or
occluded parts. In the method, the deformation spent by the template
to match the shape images and the matching degree is used to evaluate
the similarity between them.
Abstract: Active Vibration Control (AVC) is an important
problem in structures. One of the ways to tackle this problem is to
make the structure smart, adaptive and self-controlling. The objective
of active vibration control is to reduce the vibration of a system by
automatic modification of the system-s structural response. This
paper features the modeling and design of a Periodic Output
Feedback (POF) control technique for the active vibration control of
a flexible Timoshenko cantilever beam for a multivariable case with
2 inputs and 2 outputs by retaining the first 2 dominant vibratory
modes using the smart structure concept. The entire structure is
modeled in state space form using the concept of piezoelectric
theory, Timoshenko beam theory, Finite Element Method (FEM) and
the state space techniques. Simulations are performed in MATLAB.
The effect of placing the sensor / actuator at 2 finite element
locations along the length of the beam is observed. The open loop
responses, closed loop responses and the tip displacements with and
without the controller are obtained and the performance of the smart
system is evaluated for active vibration control.
Abstract: Novel acrylated epoxidized hemp oil (AEHO) based
bioresins were successfully synthesised, characterized and applied to
biocomposites reinforced with woven jute fibre. Characterisation of
the synthesised AEHO consisted of acid number titrations and FTIR
spectroscopy to assess the success of the acrylation reaction. Three
different matrices were produced (vinylester (VE), 50/50 blend of
AEHO/VE and 100% AEHO) and reinforced with jute fibre to form
three different types of biocomposite samples. Mechanical properties
in the form of flexural and interlaminar shear strength (ILSS) were
investigated and compared for the different samples. Results from the
mechanical tests showed that AEHO and 50/50 based neat bioresins
displayed lower flexural properties compared with the VE samples.
However when applied to biocomposites and compared with VE
based samples, AEHO biocomposites demonstrated comparable
flexural performance and improved ILSS. These results are attributed
to improved fibre-matrix interfacial adhesion due to surface-chemical
compatibility between the natural fibres and bioresin.
Abstract: In this paper, we have proposed a Haar wavelet quasilinearization
method to solve the well known Blasius equation. The
method is based on the uniform Haar wavelet operational matrix
defined over the interval [0, 1]. In this method, we have proposed the
transformation for converting the problem on a fixed computational
domain. The Blasius equation arises in the various boundary layer
problems of hydrodynamics and in fluid mechanics of laminar
viscous flows. Quasi-linearization is iterative process but our
proposed technique gives excellent numerical results with quasilinearization
for solving nonlinear differential equations without any
iteration on selecting collocation points by Haar wavelets. We have
solved Blasius equation for 1≤α ≤ 2 and the numerical results are
compared with the available results in literature. Finally, we
conclude that proposed method is a promising tool for solving the
well known nonlinear Blasius equation.
Abstract: Results in one field necessarily give insight into the
others, and all have much potential for scientific and technological
application. The Hadamard-transform technique once been applied to
the spectrometry also has its use in the SNR Enhancement of OTDR.
In this report, a new set of code (Simplex-codes) is discussed and
where the addition gain of SNR come from is implied.
Abstract: Clustering in high dimensional space is a difficult
problem which is recurrent in many fields of science and
engineering, e.g., bioinformatics, image processing, pattern
reorganization and data mining. In high dimensional space some of
the dimensions are likely to be irrelevant, thus hiding the possible
clustering. In very high dimensions it is common for all the objects in
a dataset to be nearly equidistant from each other, completely
masking the clusters. Hence, performance of the clustering algorithm
decreases.
In this paper, we propose an algorithmic framework which
combines the (reduct) concept of rough set theory with the k-means
algorithm to remove the irrelevant dimensions in a high dimensional
space and obtain appropriate clusters. Our experiment on test data
shows that this framework increases efficiency of the clustering
process and accuracy of the results.
Abstract: The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.
Abstract: Particle boards were prepared from Maize cob (MC) and urea-formaldehyde resin (UFR) on compression moulding machine. The amount of MC was varied from 50-120g while 30g of UFR was kept constant. Some mechanical properties of the particle boards were tested using the standard ASM methods. The results show that as the MC content increased from 50- 120g in 30g UFR, the hardness increased from about 6.89 x 102 to7.51 x 102MPa. Impact strength decreased from 3.3x 10-2 to 0.45 x 10-2J/M2, while tensile strength initially increased from 2.63 x 102 to 3.14 x 102 MPa as the MC increased from 50 to 60g in 30g UFR, thereafter, it decreased to about 1.35 x 102MPa at 120g in 30g content.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in the form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studied with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: Many computational techniques were applied to
solution of heat conduction problem. Those techniques were the
finite difference (FD), finite element (FE) and recently meshless
methods. FE is commonly used in solution of equation of heat
conduction problem based on the summation of stiffness matrix of
elements and the solution of the final system of equations. Because
of summation process of finite element, convergence rate was
decreased. Hence in the present paper Cellular Automata (CA)
approach is presented for the solution of heat conduction problem.
Each cell considered as a fixed point in a regular grid lead to the
solution of a system of equations is substituted by discrete systems of
equations with small dimensions. Results show that CA can be used
for solution of heat conduction problem.
Abstract: A complete spectral representation for the
electromagnetic field of planar multilayered waveguides
inhomogeneously filled with omega media is presented. The problem
of guided electromagnetic propagation is reduced to an eigenvalue
equation related to a 2 ´ 2 matrix differential operator. Using the
concept of adjoint waveguide, general bi-orthogonality relations for
the hybrid modes (either from the discrete or from the continuous
spectrum) are derived. For the special case of homogeneous layers
the linear operator formalism is reduced to a simple 2 ´ 2 coupling
matrix eigenvalue problem. Finally, as an example of application, the
surface and the radiation modes of a grounded omega slab waveguide
are analyzed.
Abstract: Today we tend to go back to the past to our root
relation to nature. Therefore in search of friendly spaces there are
elements of natural environment introduced as elements of spatial
composition. Though reinvented through the use of the new
substance such as greenery, water etc. made possible by state of the
art technologies, still, in principal, they remain the same. As a result,
sustainable design, based upon the recognized means of composition
in addition to the relation of architecture and urbanism vs. nature
introduces a new aesthetical values into architectural and urban
space.
Abstract: This paper proposed a stiffness analysis method for a
3-PRS mechanism for welding thick aluminum plate using FSW
technology. In the molding process, elastic deformation of lead-screws
and links are taken into account. This method is based on the virtual
work principle. Through a survey of the commonly used stiffness
performance indices, the minimum and maximum eigenvalues of the
stiffness matrix are used to evaluate the stiffness of the 3-PRS
mechanism. Furthermore, A FEA model has been constructed to verify
the method. Finally, we redefined the workspace using the stiffness
analysis method.
Abstract: Concerning the inpatient care the present situation is
characterized by intense charges of medical technology into the
clinical daily routine and an ever stronger integration of special
techniques into the clinical workflow. Medical technology is by now
an integral part of health care according to consisting general
accepted standards. Purchase and operation thereby represent an
important economic position and both are subject of everyday
optimisation attempts. For this purpose by now exists a huge number
of tools which conduce more likely to a complexness of the problem
by a comprehensive implementation. In this paper the advantages of
an integrative information-workflow on the life-cycle-management in
the region of medical technology are shown.
Abstract: In order to research Internet quantificationally and
better model the performance of network, this paper proposes a novel
AS level network performance model (MNPM), it takes autonomous
system (AS) as basic modeling unit, measures E2E performance
between any two outdegrees of an AS and organizes measurement
results into matrix form which called performance matrix (PM).
Inter-AS performance calculation is defined according to performance
information stored in PM. Simulation has been implemented to verify
the correctness of MNPM and a practical application of MNPM
(network congestion detection) is given.