Abstract: In this research, Response Surface Methodology (RSM) is used to investigate the effect of four controllable input variables namely: discharge current, pulse duration, pulse off time and applied voltage Surface Roughness (SR) of on Electrical Discharge Machined surface. To study the proposed second-order polynomial model for SR, a Central Composite Design (CCD) is used to estimation the model coefficients of the four input factors, which are alleged to influence the SR in Electrical Discharge Machining (EDM) process. Experiments were conducted on AISI D2 tool steel with copper electrode. The response is modeled using RSM on experimental data. The significant coefficients are obtained by performing Analysis of Variance (ANOVA) at 5% level of significance. It is found that discharge current, pulse duration, and pulse off time and few of their interactions have significant effect on the SR. The model sufficiency is very satisfactory as the Coefficient of Determination (R2) is found to be 91.7% and adjusted R2-statistic (R2 adj ) 89.6%.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.
Abstract: The psychological and physical trauma associated with the loss of a human limb can severely impact on the quality of life of an amputee rendering even the most basic of tasks very difficult. A prosthetic device can be of great benefit to the amputee in the performance of everyday human tasks. This paper outlines a proposed mechanical design of a 12 degree-of-freedom SMA actuated artificial hand. It is proposed that the SMA wires be embedded intrinsically within the hand structure which will allow for significant flexibility for use either as a prosthetic hand solution, or as part of a complete lower arm prosthetic solution. A modular approach is taken in the design facilitating ease of manufacture and assembly, and more importantly, also allows the end user to easily replace SMA wires in the event of failure. A biomimetric approach has been taken during the design process meaning that the artificial hand should replicate that of a human hand as far as is possible with due regard to functional requirements. The proposed design has been exposed to appropriate loading through the use of finite element analysis (FEA) to ensure that it is structurally sound. Theoretical analysis of the mechanical framework was also carried out to establish the limits of the angular displacement and velocity of the finger tip as well finger tip force generation. A combination of various polymers and Titanium, which are suitably lightweight, are proposed for the manufacture of the design.
Abstract: ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression (AR) model based on binomial smoothing (BS) technique which is efficient in data processing, which is called BSRBFAR. This method is examined by using the data of Canadian Lynx data. Empirical results indicate that the over-fitting problem can be eased using RBF neural network based on binomial smoothing which is called BS-RBF, and the hybrid model–BS-RBFAR can be an effective way to improve forecasting accuracy achieved by BSRBF used separately.
Abstract: Fractional Fourier Transform is a generalization of the
classical Fourier Transform. The Fractional Fourier span in general
depends on the amplitude and phase functions of the signal and varies
with the transform order. However, with the development of the
Fractional Fourier filter banks, it is advantageous in some cases to
have different transform orders for different filter banks to achieve
better decorrelation of the windowed and overlapped time signal. We
present an expression that is useful for finding the perturbation in the
Fractional Fourier span due to the erroneous transform order and the
possible variation in the window shape and length. The expression is
based on the dependency of the time-Fractional Fourier span
Uncertainty on the amplitude and phase function of the signal. We
also show with the help of the developed expression that the
perturbation of span has a varying degree of sensitivity for varying
degree of transform order and the window coefficients.
Abstract: In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.
Abstract: –In this paper the damage in clamped-free, clampedclamped and free-free beam are analyzed considering samples
without and with structural modifications. The damage location is
investigated by the use of the bispectrum and wavelet analysis. The
mathematical models are obtained using 2D elasticity theory and the
Finite Element Method (FEM). The numerical and experimental data
are approximated using the Particle Swarm Optimizer (PSO) method
and this way is possible to adjust the localization and the severity of
the damage. The experimental data are obtained through
accelerometers placed along the sample. The system is excited using
impact hammer.
Abstract: This project relates to a two-wheeled self balancing
robot for transferring loads on different locations along a path. This
robot specifically functions as a dual mode navigation to navigate
efficiently along a desired path. First, as a plurality of distance
sensors mounted at both sides of the body for collecting information
on tilt angle of the body and second, as a plurality of speed sensors
mounted at the bottom of the body for collecting information of the
velocity of the body in relative to the ground. A microcontroller for
processing information collected from the sensors and configured to
set the path and to balance the body automatically while a processor
operatively coupled to the microcontroller and configured to compute
change of the tilt and velocity of the body. A direct current motor
operatively coupled to the microcontroller for controlling the wheels
and characterized in that a remote control is operatively coupled to
the microcontroller to operate the robot in dual navigation modes.
Abstract: Effect of geometry on crushing behavior, energy absorption and failure mode of woven roving jute fiber/epoxy laminated composite tubes were experimentally studied. Investigations were carried out on three different geometrical types of composite tubes (circular, square and radial corrugated) subjected to axial compressive loading. It was observed in axial crushing study that the load bearing capability is significantly influenced by corrugation geometry. The influence of geometries of specimens was supported by the plotted load – displacement curves of the tests.
Abstract: This paper introduces a method of calculating the
quantities of construction materials and construction waste on site in
city of Novi Sad. In buildings is about 40% of the total weight of
materials that are in circulation in the world economic space. The
best solution for this waste is to be stored at source, at the point of
generation. There are several treatment options for this type of waste,
reduction at source, reuse, recycling. Beside its negative effects on
the environment, construction waste can be and resource. Novi Sad is
divided in 16 single family resident zones and 10 multi family
resident zones. For every zone of the city, quantities of used
construction materials and construction waste were obtained.
Rational use of natural resources is an essential factor in applying the
principles of development with savings.
Abstract: Antiseismic property of telecommunication equipment
is very important for the grasp of the damage and the restoration after
earthquake. Telecommunication business operators are regulating
seismic standard for their equipments. These standards are organized
to simulate the real seismic situations and usually define the minimum
value of first natural frequency of the equipments or the allowable
maximum displacement of top of the equipments relative to bottom.
Using the finite element analysis, natural frequency can be obtained
with high accuracy but the relative displacement of top of the
equipments is difficult to predict accurately using the analysis.
Furthermore, in the case of simulating the equipments with access
floor, predicting the relative displacement of top of the equipments
become more difficult.
In this study, using enormous experimental datum, an empirical
formula is suggested to forecast the relative displacement of top of the
equipments. Also it can be known that which physical quantities are
related with the relative displacement.
Abstract: Machine Translation, (hereafter in this document
referred to as the "MT") faces a lot of complex problems from its
origination. Extracting multiword expressions is also one of the
complex problems in MT. Finding multiword expressions during
translating a sentence from English into Urdu, through existing
solutions, takes a lot of time and occupies system resources. We have
designed a simple relational data approach, in which we simply set a
bit in dictionary (database) for multiword, to find and handle
multiword expression. This approach handles multiword efficiently.
Abstract: The flow field around a flat plate of infinite span has
been investigated for several values of the angle of attack. Numerical
predictions have been compared to experimental measurements, in
order to examine the effect of turbulence model and grid resolution
on the resultant aerodynamic forces acting on the plate. Also the
influence of the free-stream turbulence intensity, at the entrance of
the computational domain, has been investigated. A full campaign of
simulations has been conducted for three inclination angles (9°, 15°
and 30°), in order to obtain some practical guidelines to be used for
the simulation of the flow field around inclined plates and discs.
Abstract: In this work, the autoregressive vectors are used to
know dynamics of the Agricultural export and import, and the real
effective exchange rate (REER). In order to analyze the interactions,
the impulse- response function is used in decomposition of variance,
causality of Granger as well as the methodology of Johansen to know
the relations co integration. The REER causes agricultural export and
import in the sense of Granger. The influence displays the
innovations of the REER on the agricultural export and import is not
very great and the duration of the effects is short. It displays that
REER has an immediate positive effect, after the tenth year it
displays smooth results on the agricultural export. Evidence of a
vector exists co integration, In short run, REER has smaller effects
on export and import, compared to the long-run effects.
Abstract: This evaluation of land supply system performance in
China shall examine the combination of government functions and
national goals in order to perform a cost-benefit analysis of system
results. From the author's point of view, it is most productive to
evaluate land supply system performance at moments of system
transformation for the following reasons. The behavior and
input-output change of beneficial results at different times can be
observed when the system or policy changes and system performance
can be evaluated through a cost-benefit analysis during the process of
system transformation. Moreover, this evaluation method can avoid
the influence of land resource endowment. Different land resource
endowment methods and different economy development periods
result in different systems. This essay studies the contents, principles
and methods of land supply system performance evaluation. Taking
Beijing as an example, this essay optimizes and classifies the land
supply index, makes a quantitative evaluation of land supply system
performance through principal component analysis (PCA), and finally
analyzes the factors that influence land supply system performance at
times of system transformation.
Abstract: Here, in this work we study correspondence the energy density New agegraphic and the energy density Gauss- Bonnet models in flat universe. We reconstruct Λ and Λ ω for them with 0 ( ) 0 h a t = a t .
Abstract: The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Abstract: In this paper, we analyze and test a scheme for the
estimation of electrical fundamental frequency signals from the
harmonic load current and voltage signals.
The scheme was based on using two different Multi Layer
Artificial Neural Networks (ML-ANN) one for the current and the
other for the voltage.
This study also analyzes and tests the effect of choosing the
optimum artificial neural networks- sizes which determine the quality
and accuracy of the estimation of electrical fundamental frequency
signals.
The simulink tool box of the Matlab program for the simulation of
the test system and the test of the neural networks has been used.