Abstract: In this paper, we propose a robust controller design method for discrete-time systems with sector-bounded nonlinearities and time-varying delay. Based on the Lyapunov theory, delaydependent stabilization criteria are obtained in terms of linear matrix inequalities (LMIs) by constructing the new Lyapunov-Krasovskii functional and using some inequalities. A robust state feedback controller is designed by LMI framework and a reciprocally convex combination technique. The effectiveness of the proposed method is verified throughout a numerical example.
Abstract: This paper examines the forced convection flow of
incompressible, electrically conducting viscous fluid past a sharp
wedge in the presence of heat generation or absorption with an
applied magnetic field. The system of partial differential equations
governing Falkner - Skan wedge flow and heat transfer is first
transformed into a system of ordinary differential equations using
similarity transformations which is later solved using an implicit
finite - difference scheme, along with quasilinearization technique.
Numerical computations are performed for air (Pr = 0.7) and
displayed graphically to illustrate the influence of pertinent physical
parameters on local skin friction and heat transfer coefficients and,
also on, velocity and temperature fields. It is observed that the
magnetic field increases both the coefficients of skin friction and heat
transfer. The effect of heat generation or absorption is found to be
very significant on heat transfer, but its effect on the skin friction is
negligible. Indeed, the occurrence of overshoot is noticed in the
temperature profiles during heat generation process, causing the
reversal in the direction of heat transfer.
Abstract: This paper proposes a zero-voltage transition (ZVT) PWM synchronous buck converter, which is designed to operate at low output voltage and high efficiency typically required for portable systems. To make the DC-DC converter efficient at lower voltage, synchronous converter is an obvious choice because of lower conduction loss in the diode. The high-side MOSFET is dominated by the switching losses and it is eliminated by the soft switching technique. Additionally, the resonant auxiliary circuit designed is also devoid of the switching losses. The suggested procedure ensures an efficient converter. Theoretical analysis, computer simulation, and experimental results are presented to explain the proposed schemes.
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. To predict faultproneness
of modules different techniques have been proposed which
includes statistical methods, machine learning techniques, neural
network techniques and clustering techniques. The aim of proposed
study is to explore whether metrics available in the early lifecycle
(i.e. requirement metrics), metrics available in the late lifecycle (i.e.
code metrics) and metrics available in the early lifecycle (i.e.
requirement metrics) combined with metrics available in the late
lifecycle (i.e. code metrics) can be used to identify fault prone
modules using Genetic Algorithm technique. This approach has been
tested with real time defect C Programming language datasets of
NASA software projects. The results show that the fusion of
requirement and code metric is the best prediction model for
detecting the faults as compared with commonly used code based
model.
Abstract: This paper addresses an efficient technique to embed and detect digital fingerprint code. Orthogonal modulation method is a straightforward and widely used approach for digital fingerprinting but shows several limitations in computational cost and signal efficiency. Coded modulation method can solve these limitations in theory. However it is difficult to perform well in practice if host signals are not available during tracing colluders, other kinds of attacks are applied, and the size of fingerprint code becomes large. In this paper, we propose a hybrid modulation method, in which the merits of or-thogonal modulation and coded modulation method are combined so that we can achieve low computational cost and high signal efficiency. To analyze the performance, we design a new fingerprint code based on GD-PBIBD theory and modulate this code into images by our method using spread-spectrum watermarking on frequency domain. The results show that the proposed method can efficiently handle large fingerprint code and trace colluders against averaging attacks.
Abstract: Repeated observation of a given area over time yields
potential for many forms of change detection analysis. These
repeated observations are confounded in terms of radiometric
consistency due to changes in sensor calibration over time,
differences in illumination, observation angles and variation in
atmospheric effects.
This paper demonstrates applicability of an empirical relative
radiometric normalization method to a set of multitemporal cloudy
images acquired by Resourcesat1 LISS III sensor. Objective of this
study is to detect and remove cloud cover and normalize an image
radiometrically. Cloud detection is achieved by using Average
Brightness Threshold (ABT) algorithm. The detected cloud is
removed and replaced with data from another images of the same
area. After cloud removal, the proposed normalization method is
applied to reduce the radiometric influence caused by non surface
factors. This process identifies landscape elements whose reflectance
values are nearly constant over time, i.e. the subset of non-changing
pixels are identified using frequency based correlation technique. The
quality of radiometric normalization is statistically assessed by R2
value and mean square error (MSE) between each pair of analogous
band.
Abstract: A new interface circuit for capacitive sensor is
presented. This paper presents the design and simulation of soil
moisture capacitive sensor interface circuit based on phase
differential technique. The circuit has been designed and fabricated
using MIMOS- 0.35"m CMOS technology. Simulation and test
results show linear characteristic from 36 – 52 degree phase
difference, representing 0 – 100% in soil moisture level. Test result
shows the circuit has sensitivity of 0.79mV/0.10 phase difference,
translating into resolution of 10% soil moisture level.
Abstract: Skyline extraction in mountainous images can be used
for navigation of vehicles or UAV(unmanned air vehicles), but it is
very hard to extract skyline shape because of clutters like clouds, sea
lines and field borders in images. We developed the edge-based
skyline extraction algorithm using a proposed multistage edge filtering
(MEF) technique. In this method, characteristics of clutters in the
image are first defined and then the lines classified as clutters are
eliminated by stages using the proposed MEF technique. After this
processing, we select the last line using skyline measures among the
remained lines. This proposed algorithm is robust under severe
environments with clutters and has even good performance for
infrared sensor images with a low resolution. We tested this proposed
algorithm for images obtained in the field by an infrared camera and
confirmed that the proposed algorithm produced a better performance
and faster processing time than conventional algorithms.
Abstract: Optical 1x12 fused-taper-twisted polymer optical fiber (POF) couplers has been fabricated by a perform technique. Characterization of the coupler which proposed to be used in passive night vision application to tracking a blind sport area was reported. During the development process of fused-taper-twisted POF couplers was carried out, red LED fully utilized to be injected into the couplers to test the quality of fabricated couplers. Some characterization parameters, such as optical output power, POFs attenuation characteristics and power losses on the network were observed. The maximum output power efficiency of the coupler is about 40%, but it can be improved gradually through experience and practice.
Abstract: This study reports the preparation of soft magnetic
ribbons of Fe-based amorphous alloys using the single-roller melt-spinning technique. Ribbon width varied from 142 mm to 213
mm and, with a thickness of approximately 22 μm ± 2 μm. The microstructure and magnetic properties of the ribbons were
characterized by differential scanning calorimeter (DSC), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and electrical resistivity measurements (ERM). The amorphous material
properties dependence of the cooling rate and nozzle pressure have uneven surface in ribbon thicknesses are investigated. Magnetic
measurement results indicate that some region of the ribbon exhibits good magnetic properties, higher saturation induction and lower coercivity. However, due to the uneven surface of 213 mm wide
ribbon, the magnetic responses are not uniformly distributed. To
understand the transformer magnetic performances, this study analyzes the measurements of a three-phase 2 MVA amorphous-cored transformer. Experimental results confirm that the transformer with a
ribbon width of 142 mm has better magnetic properties in terms of lower core loss, exciting power, and audible noise.
Abstract: This study presents an active vibration control
technique to reduce the earthquake responses of a retained structural
system. The proposed technique is a synthesis of the adaptive input
estimation method (AIEM) and linear quadratic Gaussian (LQG)
controller. The AIEM can estimate an unknown system input online.
The LQG controller offers optimal control forces to suppress
wall-structural system vibration. The numerical results show robust
performance in the active vibration control technique.
Abstract: The primary objective of this paper was to construct a
“kinematic parameter-independent modeling of three-axis machine
tools for geometric error measurement" technique. Improving the
accuracy of the geometric error for three-axis machine tools is one of
the machine tools- core techniques. This paper first applied the
traditional method of HTM to deduce the geometric error model for
three-axis machine tools. This geometric error model was related to the
three-axis kinematic parameters where the overall errors was relative
to the machine reference coordinate system. Given that the
measurement of the linear axis in this model should be on the ideal
motion axis, there were practical difficulties. Through a measurement
method consolidating translational errors and rotational errors in the
geometric error model, we simplified the three-axis geometric error
model to a kinematic parameter-independent model. Finally, based on
the new measurement method corresponding to this error model, we
established a truly practical and more accurate error measuring
technique for three-axis machine tools.
Abstract: Calibration estimation is a method of adjusting the
original design weights to improve the survey estimates by using
auxiliary information such as the known population total (or mean)
of the auxiliary variables. A calibration estimator uses calibrated
weights that are determined to minimize a given distance measure to
the original design weights while satisfying a set of constraints
related to the auxiliary information. In this paper, we propose a new
multivariate calibration estimator for the population mean in the
stratified sampling design, which incorporates information available
for more than one auxiliary variable. The problem of determining the
optimum calibrated weights is formulated as a Mathematical
Programming Problem (MPP) that is solved using the Lagrange
multiplier technique.
Abstract: The main aim is to perform mutational analysis of CTLA4 gene Exon 1 in SLE patients. A total of 61 SLE patients fulfilling “American College of Rheumatology (ACR) criteria" and 61 controls were enrolled in this study. The region of CTLA4 gene exon 1 was amplified by using Step-down PCR technique. Extracted DNA of band 354 bp was sequenced to analyze mutations in the exon-1 of CTLA-4 gene. Further, protein sequences were identified from nucleotide sequences of CTLA4 Exon 1 by using Expasy software and through Blast P software it was found that CTLA4 protein sequences of Pakistani SLE patients were similar to that of Chinese SLE population. No variations were found after patients sequences were compared with that of the control sequence. Furthermore it was found that CTLA4 protein sequences of Pakistani SLE patients were similar to that of Chinese SLE population. Thus CTLA4 gene may not be responsible for an autoimmune disease SLE.
Abstract: In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.
Abstract: Agriculture products are being more demanding in
market today. To increase its productivity, automation to produce
these products will be very helpful. The purpose of this work is to
measure and determine the ripeness and quality of watermelon. The
textures on watermelon skin will be captured using digital camera.
These images will be filtered using image processing technique. All
these information gathered will be trained using ANN to determine
the watermelon ripeness accuracy. Initial results showed that the best
model has produced percentage accuracy of 86.51%, when measured
at 32 hidden units with a balanced percentage rate of training dataset.
Abstract: In recent years, most of the regions in the world are
exposed to degradation and erosion caused by increasing
population and over use of land resources. The understanding of
the most important factors on soil erosion and sediment yield are
the main keys for decision making and planning. In this study, the
sediment yield and soil erosion were estimated and the priority of
different soil erosion factors used in the MPSIAC method of soil
erosion estimation is evaluated in AliAbad watershed in southwest
of Isfahan Province, Iran. Different information layers of the
parameters were created using a GIS technique. Then, a
multivariate procedure was applied to estimate sediment yield and
to find the most important factors of soil erosion in the model. The
results showed that land use, geology, land and soil cover are the
most important factors describing the soil erosion estimated by
MPSIAC model.
Abstract: The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of 'n' input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.
Abstract: Low frequency power oscillations may be triggered
by many events in the system. Most oscillations are damped by the
system, but undamped oscillations can lead to system collapse.
Oscillations develop as a result of rotor acceleration/deceleration
following a change in active power transfer from a generator. Like
the operations limits, the monitoring of power system oscillating
modes is a relevant aspect of power system operation and control.
Unprevented low-frequency power swings can be cause of cascading
outages that can rapidly extend effect on wide region. On this regard,
a Wide Area Monitoring, Protection and Control Systems
(WAMPCS) help in detecting such phenomena and assess power
system dynamics security. The monitoring of power system
electromechanical oscillations is very important in the frame of
modern power system management and control. In first part, this
paper compares the different technique for identification of power
system oscillations. Second part analyzes possible identification
some power system dynamics behaviors Using Wide Area
Monitoring Systems (WAMS) based on Phasor Measurement Units
(PMUs) and wavelet technique.
Abstract: A code has been developed in Mathematica using
Direct Simulation Monte Carlo (DSMC) technique. The code was
tested for 2-D air flow around a circular cylinder. Same geometry
and flow properties were used in FLUENT 6.2 for comparison. The
results obtained from Mathematica simulation indicated significant
agreement with FLUENT calculations, hence providing insight into
particle nature of fluid flows.