Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
Abstract: Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Abstract: This paper presents a novel CMOS four-transistor
SRAM cell for very high density and low power embedded SRAM
applications as well as for stand-alone SRAM applications. This cell
retains its data with leakage current and positive feedback without
refresh cycle. The new cell size is 20% smaller than a conventional
six-transistor cell using same design rules. Also proposed cell uses
two word-lines and one pair bit-line. Read operation perform from
one side of cell, and write operation perform from another side of
cell, and swing voltage reduced on word-lines thus dynamic power
during read/write operation reduced. The fabrication process is fully
compatible with high-performance CMOS logic technologies,
because there is no need to integrate a poly-Si resistor or a TFT load.
HSPICE simulation in standard 0.25μm CMOS technology confirms
all results obtained from this paper.
Abstract: Explosive forming is one of the unconventional
techniques in which, most commonly, the water is used as the
pressure transmission medium. One of the newest methods in
explosive forming is gas detonation forming which uses a normal
shock wave derived of gas detonation, to form sheet metals. For this
purpose a detonation is developed from the reaction of H2+O2
mixture in a long cylindrical detonation tube. The detonation wave
goes through the detonation tube and acts as a blast load on the steel
blank and forms it. Experimental results are compared with a finite
element model; and the comparison of the experimental and
numerical results obtained from strain, thickness variation and
deformed geometry is carried out. Numerical and experimental
results showed approximately 75 – 90 % similarity in formability of
desired shape. Also optimum percent of gas mixture obtained when
we mix 68% H2 with 32% O2.
Abstract: Improvement in CAE methods has an important role for shortening of the vehicle product development time. It is provided that validation of the design and improvements in terms of durability can be done without hardware prototype production. In recent years, several different methods have been developed in order to investigate fatigue damage of the vehicle. The intended goal among these methods is prediction of fatigue damage in a short time with reduced costs. This study developed a new fatigue damage prediction method in the automotive sector using power spectrum densities of accelerations. This study also confirmed that the weak region in vehicle can be easily detected with the method developed in this study which results were compared with conventional method.
Abstract: This paper describes the speed sensorless vector control method of the parallel connected induction motor drive fed by a single inverter. Speed and rotor fluxes of the induction motor are estimated by natural observer with load torque adaptation and adaptive rotor flux observer. The performance parameters speed and rotor fluxes are estimated from the measured terminal voltages and currents. Fourth order induction motor model is used and speed is considered as a parameter. The performance of the natural observer is similar to the conventional observer. The speed of an induction motor is estimated by MATLAB simulation under different speed and load conditions. Estimated values along with other measured states are used for closed loop control. The simulation results show that the natural observer is also effective for parallel connected induction motor drive.
Abstract: This paper proposes the use of Bayesian belief
networks (BBN) as a higher level of health risk assessment for a
dumping site of lead battery smelter factory. On the basis of the
epidemiological studies, the actual hospital attendance records and
expert experiences, the BBN is capable of capturing the probabilistic
relationships between the hazardous substances and their adverse
health effects, and accordingly inferring the morbidity of the adverse
health effects. The provision of the morbidity rates of the related
diseases is more informative and can alleviate the drawbacks of
conventional methods.
Abstract: Image enhancement is the most important challenging preprocessing for almost all applications of Image Processing. By now, various methods such as Median filter, α-trimmed mean filter, etc. have been suggested. It was proved that the α-trimmed mean filter is the modification of median and mean filters. On the other hand, ε-filters have shown excellent performance in suppressing noise. In spite of their simplicity, they achieve good results. However, conventional ε-filter is based on moving average. In this paper, we suggested a new ε-filter which utilizes α-trimmed mean. We argue that this new method gives better outcomes compared to previous ones and the experimental results confirmed this claim.
Abstract: For higher order multiplications, a huge number of
adders or compressors are to be used to perform the partial product
addition. We have reduced the number of adders by introducing
special kind of adders that are capable to add five/six/seven bits per
decade. These adders are called compressors. Binary counter
property has been merged with the compressor property to develop
high order compressors. Uses of these compressors permit the
reduction of the vertical critical paths. A 16×16 bit multiplier has
been developed using these compressors. These compressors make
the multipliers faster as compared to the conventional design that
have been used 4-2 compressors and 3-2 compressors.
Abstract: A hardware efficient, multi mode, re-configurable
architecture of interleaver/de-interleaver for multiple standards,
like DVB, WiMAX and WLAN is presented. The interleavers
consume a large part of silicon area when implemented by using
conventional methods as they use memories to store permutation
patterns. In addition, different types of interleavers in different
standards cannot share the hardware due to different construction
methodologies. The novelty of the work presented in this paper is
threefold: 1) Mapping of vital types of interleavers including
convolutional interleaver onto a single architecture with flexibility
to change interleaver size; 2) Hardware complexity for channel
interleaving in WiMAX is reduced by using 2-D realization of the
interleaver functions; and 3) Silicon cost overheads reduced by
avoiding the use of small memories. The proposed architecture
consumes 0.18mm2 silicon area for 0.12μm process and can
operate at a frequency of 140 MHz. The reduced complexity helps
in minimizing the memory utilization, and at the same time
provides strong support to on-the-fly computation of permutation
patterns.
Abstract: In this paper, we present the design and experimental
evaluation of complementary energy path adiabatic logic (CEPAL)
based 1 bit full adder circuit. A simulative investigation on the
proposed full adder has been done using VIRTUOSO SPECTRE
simulator of cadence in 0.18μm UMC technology and its
performance has been compared with the conventional CMOS full
adder circuit. The CEPAL based full adder circuit exhibits the energy
saving of 70% to the conventional CMOS full adder circuit, at 100
MHz frequency and 1.8V operating voltage.
Abstract: The Pulsed Compression Reactor promises to be a
compact, economical and energy efficient alternative to conventional
chemical reactors.
In this article, the production of synthesis gas using the Pulsed
Compression Reactor is investigated. This is done experimentally as
well as with simulations. The experiments are done by means of a
single shot reactor, which replicates a representative, single
reciprocation of the Pulsed Compression Reactor with great control
over the reactant composition, reactor temperature and pressure and
temperature history. Simulations are done with a relatively simple
method, which uses different models for the chemistry and
thermodynamic properties of the species in the reactor. Simulation
results show very good agreement with the experimental data, and
give great insight into the reaction processes that occur within the
cycle.
Abstract: In this paper a technique for increasing the
convergence rate of fractionally spaced channel equalizer is
proposed. Instead of symbol-spaced updating of the equalizer filter, a
mechanism has been devised to update the filter at a higher rate. This
ensures convergence of the equalizer filter at a higher rate and
therefore less time-consuming. The proposed technique has been
simulated and tested for two-ray modeled channels with various
delay spreads. These channels include minimum-phase and nonminimum-
phase channels. Simulation results suggest that that
proposed technique outperforms the conventional technique of
symbol-spaced updating of equalizer filter.
Abstract: Recently electric vehicles are becoming popular as an
alternative of conventional fossil fuel vehicles. Conventional Internal
Combustion Engine (ICE) vehicle uses fossil fuel which contributing
a major part of overall carbon emission in the environment. Carbon
and other green house gas emission are responsible for global
warming and resulting climate change. It becomes vital to evaluate
performance of vehicle based on emission. In this paper an effort has
been made to depict the picture of emission caused by vehicle and
scenario of Australia has taken into account. Effort has been made to
compare the fossil based vehicle with electric vehicle in phases. The
study also evaluates advancement in electric vehicle technology,
required infrastructure for sustainability and future scope of
developments. This paper also includes the evaluation of electric
vehicle concept for pollution control and sustainable transport
systems in future. This study can be a benchmark for development of
electric vehicle as low carbon emission alternative for the cities of
tomorrow.
Abstract: In this paper, a new K-means clustering based
approach for identification of voltage control areas is developed.
Voltage control areas are important for efficient reactive power
management in power systems operating under deregulated
environment. Although, voltage control areas are formed using
conventional hierarchical clustering based method, but the present
paper investigate the capability of K-means clustering for the
purpose of forming voltage control areas. The proposed method is
tested and compared for IEEE 14 bus and IEEE 30 bus systems. The
results show that this K-means based method is competing with
conventional hierarchical approach
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: The permanent magnet synchronous motor (PMSM) is
very useful in many applications. Vector control of PMSM is popular
kind of its control. In this paper, at first an optimal vector control for
PMSM is designed and then results are compared with conventional
vector control. Then, it is assumed that the measurements are noisy
and linear quadratic Gaussian (LQG) methodology is used to filter
the noises. The results of noisy optimal vector control and filtered
optimal vector control are compared to each other. Nonlinearity of
PMSM and existence of inverter in its control circuit caused that the
system is nonlinear and time-variant. With deriving average model,
the system is changed to nonlinear time-invariant and then the
nonlinear system is converted to linear system by linearization of
model around average values. This model is used to optimize vector
control then two optimal vector controls are compared to each other.
Simulation results show that the performance and robustness to noise
of the control system has been highly improved.
Abstract: In this research, the diffusion of innovation regarding
smartphone usage is analysed through a consumer behaviour theory.
This research aims to determine whether a pattern surrounding the
diffusion of innovation exists. As a methodology, an empirical study
of the switch from a conventional cell phone to a smartphone was
performed. Specifically, a questionnaire survey was completed by
general consumers, and the situational and behavioural characteristics
of switching from a cell phone to a smartphone were analysed. In
conclusion, we found that the speed of the diffusion of innovation, the
consumer behaviour characteristics, and the utilities of the product
vary according to the stage of the product life cycle.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.