Abstract: Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).
Abstract: It is well recognized that the green house gases such
as Chlorofluoro Carbon (CFC), CH4, CO2 etc. are responsible
directly or indirectly for the increase in the average global temperature
of the Earth. The presence of CFC is responsible for
the depletion of ozone concentration in the atmosphere due to
which the heat accompanied with the sun rays are less absorbed
causing increase in the atmospheric temperature of the Earth. The
gases like CH4 and CO2 are also responsible for the increase in
the atmospheric temperature. The increase in the temperature level
directly or indirectly affects the dynamics of interacting species
systems. Therefore, in this paper a mathematical model is proposed
and analysed using stability theory to asses the effects of increasing
temperature due to greenhouse gases on the survival or extinction of
populations in a prey-predator system. A threshold value in terms
of a stress parameter is obtained which determines the extinction or
existence of populations in the underlying system.
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: Ultra-low-power (ULP) circuits have received
widespread attention due to the rapid growth of biomedical
applications and Battery-less Electronics. Subthreshold region of
transistor operation is used in ULP circuits. Major research challenge
in the subthreshold operating region is to extract the ULP benefits
with minimal degradation in speed and robustness. Process, Voltage
and Temperature (PVT) variations significantly affect the
performance of subthreshold circuits. Designed performance
parameters of ULP circuits may vary largely due to temperature
variations. Hence, this paper investigates the effect of temperature
variation on device and circuit performance parameters at different
biasing voltages in the subthreshold region. Simulation results clearly
demonstrate that in deep subthreshold and near threshold voltage
regions, performance parameters are significantly affected whereas in
moderate subthreshold region, subthreshold circuits are more
immune to temperature variations. This establishes that moderate
subthreshold region is ideal for temperature immune circuits.
Abstract: This paper discusses two observers, which are used
for the estimation of parameters of PMSM. Former one, reduced
order observer, which is used to estimate the inaccessible parameters
of PMSM. Later one, full order observer, which is used to estimate
all the parameters of PMSM even though some of the parameters are
directly available for measurement, so as to meet with the
insensitivity to the parameter variation. However, the state space
model contains some nonlinear terms i.e. the product of different
state variables. The asymptotic state observer, which approximately
reconstructs the state vector for linear systems without uncertainties,
was presented by Luenberger. In this work, a modified form of such
an observer is used by including a non-linear term involving the
speed. So, both the observers are designed in the framework of
nonlinear control; their stability and rate of convergence is discussed.
Abstract: In this paper, we present the video quality measure
estimation via a neural network. This latter predicts MOS (mean
opinion score) by providing height parameters extracted from
original and coded videos. The eight parameters that are used are: the
average of DFT differences, the standard deviation of DFT
differences, the average of DCT differences, the standard deviation
of DCT differences, the variance of energy of color, the luminance
Y, the chrominance U and the chrominance V. We chose Euclidean
Distance to make comparison between the calculated and estimated
output.
Abstract: In the present work, a study has been made on the combination of the electrical discharge machining (EDM) with ultrasonic vibrations to improve the machining efficiency. In experiments the graphite used as tool electrode and material of workpiece was AISIH13 tool steel. The parameters such as discharge peak current and pulse duration were changed to explore their effect on the material removal rate (MRR), relative tool wear ratio (TWR) and surface roughness. From the experimental result it can be seen that ultrasonic vibration of the workpiece can significantly reduces the inactive pulses and improves the stability of process. It was found that ultrasonic assisted EDM (US-EDM) is effective in attaining a high material removal rate (MRR) in finishing regime.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: This paper presents a new sufficient condition for the
existence, uniqueness and global asymptotic stability of the equilibrium point for Cohen-Grossberg neural networks with multiple time delays. The results establish a relationship between the network parameters
of the neural system independently of the delay parameters. The results are also compared with the previously reported results in
the literature.
Abstract: Multi-loop (De-centralized) Proportional-Integral-
Derivative (PID) controllers have been used extensively in process
industries due to their simple structure for control of multivariable
processes. The objective of this work is to design multiple-model
adaptive multi-loop PID strategy (Multiple Model Adaptive-PID)
and neural network based multi-loop PID strategy (Neural Net
Adaptive-PID) for the control of multivariable system. The first
method combines the output of multiple linear PID controllers,
each describing process dynamics at a specific level of operation.
The global output is an interpolation of the individual multi-loop
PID controller outputs weighted based on the current value of the
measured process variable. In the second method, neural network
is used to calculate the PID controller parameters based on the
scheduling variable that corresponds to major shift in the process
dynamics. The proposed control schemes are simple in structure with
less computational complexity. The effectiveness of the proposed
control schemes have been demonstrated on the CSTR process,
which exhibits dynamic non-linearity.
Abstract: Stability of functionally graded beams with piezoelectric layers subjected to axial compressive load that is simply supported at both ends is studied in this paper. The displacement field of beam is assumed based on first order shear deformation beam theory. Applying the Hamilton's principle, the governing equation is established. The influences of applied voltage, dimensionless geometrical parameter, functionally graded index and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.
Abstract: We study a long-range percolation model in the hierarchical
lattice ΩN of order N where probability of connection between
two nodes separated by distance k is of the form min{αβ−k, 1},
α ≥ 0 and β > 0. The parameter α is the percolation parameter,
while β describes the long-range nature of the model. The ΩN is
an example of so called ultrametric space, which has remarkable
qualitative difference between Euclidean-type lattices. In this paper,
we characterize the sizes of large clusters for this model along the
line of some prior work. The proof involves a stationary embedding
of ΩN into Z. The phase diagram of this long-range percolation is
well understood.
Abstract: Abrasive waterjet cutting (AWJ) is a highly efficient
method for cutting almost any type of material. When holes shall be
cut the waterjet first needs to pierce the material.This paper presents a
vast experimental analysis of piercing parameters effect on piercing
time. Results from experimentation on feed rates, work piece
thicknesses, abrasive flow rates, standoff distances and water
pressure are also presented as well as studies on three methods for
dynamic piercing. It is shown that a large amount of time and
resources can be saved by choosing the piercing parameters in a
correct way. The large number of experiments puts demands on the
experimental setup. An automated experimental setup including
piercing detection is presented to enable large series of experiments
to be carried out efficiently.
Abstract: The mountain road slope failures triggered by
earthquake activities and torrential rain namely to create the disaster.
Province Road No. 24 is a main route to the Wutai Township. The area
of the study is located at the mileages between 46K and 47K along the
road. However, the road has been suffered frequent damages as a result
of landslide and slope failures during typhoon seasons. An
understanding of the sliding behaviors in the area appears to be
necessary. Slope failures triggered by earthquake activities and heavy
rainfalls occur frequently. The study is to understand the mechanism
of slope failures and to look for the way to deal with the situation. In
order to achieve these objectives, this paper is based on theoretical and
structural geology data interpretation program to assess the potential
slope sliding behavior. The study showed an intimate relationship
between the landslide behavior of the slopes and the stratum materials,
based on structural geology analysis method to analysis slope stability
and finds the slope safety coefficient to predict the sites of destroyed
layer. According to the case study and parameter analyses results, the
slope mainly slips direction compared to the site located in the
southeast area. Find rainfall to result in the rise of groundwater level is
main reason of the landslide mechanism. Future need to set up
effective horizontal drain at corrective location, that can effective
restrain mountain road slope failures and increase stability of slope.
Abstract: In this paper we will develop further the sequential
life test approach presented in a previous article by [1] using an
underlying two parameter Weibull sampling distribution. The
minimum life will be considered equal to zero. We will again provide
rules for making one of the three possible decisions as each
observation becomes available; that is: accept the null hypothesis H0;
reject the null hypothesis H0; or obtain additional information by
making another observation. The product being analyzed is a new
type of a low alloy-high strength steel product. To estimate the shape
and the scale parameters of the underlying Weibull model we will use
a maximum likelihood approach for censored failure data. A new
example will further develop the proposed sequential life testing
approach.
Abstract: In this paper, mathematical modeling of detonation in the ground is studied. Estimation of flow parameters such as velocity, maximum velocity, acceleration, maximum acceleration, shock pressure as a result of an explosion in the ground have been computed in an appropriate dynamic model approach. The variation of these parameters with the diameter of detonation place (L), density of earth or stone (¤ü), time decay of detonation (T), peak pressure (Pm), and time (t) have been analyzed. The model has been developed from the concept of underwater explosions [Refs. [1]-[3]] with appropriate changes to the present model requirements.
Abstract: This paper present a new method for design of power
system stabilizer (PSS) based on sliding mode control (SMC)
technique. The control objective is to enhance stability and improve
the dynamic response of the multi-machine power system. In order to
test effectiveness of the proposed scheme, simulation will be carried
out to analyze the small signal stability characteristics of the system
about the steady state operating condition following the change in
reference mechanical torque and also parameters uncertainties. For
comparison, simulation of a conventional control PSS (lead-lag
compensation type) will be carried out. The main approach is
focusing on the control performance which later proven to have the
degree of shorter reaching time and lower spike.
Abstract: The tree structured approach of non-uniform filterbank
(NUFB) is normally used in perfect reconstruction (PR). The PR is
not always feasible due to certain limitations, i.e, constraints in
selecting design parameters, design complexity and some times
output is severely affected by aliasing error if necessary and
sufficient conditions of PR is not satisfied perfectly. Therefore, there
has been generalized interest of researchers to go for near perfect
reconstruction (NPR). In this proposed work, an optimized tree
structure technique is used for the design of NPR non-uniform
filterbank. Window functions of Blackman family are used to design
the prototype FIR filter. A single variable linear optimization is used
to minimize the amplitude distortion. The main feature of the
proposed design is its simplicity with linear phase property.
Abstract: Authentication of multimedia contents has gained much attention in recent times. In this paper, we propose a secure semi-fragile watermarking, with a choice of two watermarks to be embedded. This technique operates in integer wavelet domain and makes use of semi fragile watermarks for achieving better robustness. A self-recovering algorithm is employed, that hides the image digest into some Wavelet subbands to detect possible malevolent object manipulation undergone by the image (object replacing and/or deletion). The Semi-fragility makes the scheme tolerant for JPEG lossy compression as low as quality of 70%, and locate the tempered area accurately. In addition, the system ensures more security because the embedded watermarks are protected with private keys. The computational complexity is reduced using parameterized integer wavelet transform. Experimental results show that the proposed scheme guarantees the safety of watermark, image recovery and location of the tempered area accurately.