Model Predictive Control of Turbocharged Diesel Engine with Exhaust Gas Recirculation
Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.
Evolution of Fuzzy Neural Networks Using an Evolution Strategy with Fuzzy Genotype Values
Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.
55 dB High Gain L-Band EDFA Utilizing Single Pump Source
In this paper, we experimentally investigate the performance of an efficient high gain triple-pass L-band Erbium-Doped Fiber (EDF) amplifier structure with a single pump source. The amplifier gain and noise figure variation with EDF pump power, input signal power and wavelengths have been investigated. The generated backward Amplified Spontaneous Emission (ASE) noise of the first amplifier stage is suppressed by using a tunable band-pass filter. The amplifier achieves a signal gain of 55 dB with low noise figure of 3.8 dB at -50 dBm input signal power. The amplifier gain shows significant improvement of 12.8 dB compared to amplifier structure without ASE suppression.
Real Time Acquisition and Analysis of Neural Response for Rehabilitative Control
Non-invasive Brain Computer Interface like Electroencephalography (EEG) which directly taps neurological signals, is being widely explored these days to connect paralytic patients/elderly with the external environment. However, in India the research is confined to laboratory settings and is not reaching the mass for rehabilitation purposes. An attempt has been made in this paper to analyze real time acquired EEG signal using cost effective and portable headset unit EMOTIV. Signal processing of real time acquired EEG is done using EEGLAB in MATLAB and EDF Browser application software platforms. Independent Component Analysis algorithm of EEGLAB is explored to identify deliberate eye blink in the attained neural signal. Time Frequency transforms and Data statistics obtained using EEGLAB along with component activation results of EDF browser clearly indicate voluntary eye blink in AF3 channel. The spectral analysis indicates dominant frequency component at 1.536000Hz representing the delta wave component of EEG during voluntary eye blink action. An algorithm is further designed to generate an active high signal based on thoughtful eye blink that can be used for plethora of control applications for rehabilitation.
Real Time Acquisition and Psychoacoustic Analysis of Brain Wave
Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analyzing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuro headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.
Performance Enhancement of DWDM Systems Using HTE Configuration HTE Configuration for 1479-1555nm Wavelength Range
In this paper, the gain spectrum of EDFA has been broadened by implementing HTE configuration for S and C band. On using this configuration an amplification bandwidth of 76nm ranging from 1479nm to 1555nm with a peak gain of 26dB has been obtained.
Design of EDFA Gain Controller based on Disturbance Observer Technique
Based on a theoretical erbium-doped fiber amplifier
(EDFA) model, we have proposed an application of disturbance
observer(DOB) with proportional/integral/differential(PID) controller
to EDFA for minimizing gain-transient time of wavelength
-division-multiplexing (WDM) multi channels in optical amplifier in
channel add/drop networks. We have dramatically reduced the
gain-transient time to less than 30μsec by applying DOB with PID
controller to the control of amplifier gain. The proposed DOB-based
gain control algorithm for EDFA was implemented as a digital control
system using TI's DSP(TMS320C28346) chip and experimental
results of the system verify the excellent performance of the proposed
gain control methodology.
Development of Neural Network Prediction Model of Energy Consumption
In the oil and gas industry, energy prediction can help
the distributor and customer to forecast the outgoing and incoming
gas through the pipeline. It will also help to eliminate any
uncertainties in gas metering for billing purposes. The objective of
this paper is to develop Neural Network Model for energy
consumption and analyze the performance model. This paper
provides a comprehensive review on published research on the
energy consumption prediction which focuses on structures and the
parameters used in developing Neural Network models. This paper is
then focused on the parameter selection of the neural network
prediction model development for energy consumption and analysis
on the result. The most reliable model that gives the most accurate
result is proposed for the prediction. The result shows that the
proposed neural network energy prediction model is able to
demonstrate an adequate performance with least Root Mean Square
On Asymptotic Laws and Transfer Processes Enhancement in Complex Turbulent Flows
The lecture represents significant advances in
understanding of the transfer processes mechanism in turbulent
separated flows. Based upon experimental data suggesting the
governing role of generated local pressure gradient that takes place in
the immediate vicinity of the wall in separated flow as a result of
intense instantaneous accelerations induced by large-scale vortex
flow structures similarity laws for mean velocity and temperature and
spectral characteristics and heat and mass transfer law for turbulent
separated flows have been developed. These laws are confirmed by
available experimental data. The results obtained were employed for
analysis of heat and mass transfer in some very complex processes
occurring in technological applications such as impinging jets, heat
transfer of cylinders in cross flow and in tube banks, packed beds
where processes manifest distinct properties which allow them to be
classified under turbulent separated flows. Many facts have got an
explanation for the first time.
Adaptive Fuzzy Control on EDF Scheduling
EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.
Recognition of Isolated Handwritten Latin Characters using One Continuous Route of Freeman Chain Code Representation and Feedforward Neural Network Classifier
In a handwriting recognition problem, characters can
be represented using chain codes. The main problem in representing
characters using chain code is optimizing the length of the chain
code. This paper proposes to use randomized algorithm to minimize
the length of Freeman Chain Codes (FCC) generated from isolated
handwritten characters. Feedforward neural network is used in the
classification stage to recognize the image characters. Our test results
show that by applying the proposed model, we reached a relatively
high accuracy for the problem of isolated handwritten when tested on
The Impact of Product Package Information on Consumer Behavior toward Genetically Modified Foods
Genetically modified (GM) technology in food
production continued to generate controversies. Consumers were
concerned with the GM foods about the healthy and environmental
risks. While consumers- acceptance was a critical factor affecting how
widely this technology be used. According to the research review,
consumers- lack of information was one of the reasons to explain
consumers- low acceptance toward GM foods. The objective for this
study wanted to find out would informative product package affect
consumers- behavior toward GM foods. An experiment was designed
to investigate consumer behavior toward different product package
information. The results indicated that the product package
information influenced consumer product trust toward GM foods.
Compared with the traceability production system information, the
information about the GM rice was approved by authorized
organizations could increase consumers product trust in GM foods.
Consumers in Taiwan saw the information provided by authorized
organizations more credible than other information.
The Characteristics of the Factors that Govern the Preferred Force in the Social Force Model of Pedestrian Movement
The social force model which belongs to the
microscopic pedestrian studies has been considered as the supremacy
by many researchers and due to the main feature of reproducing the
self-organized phenomena resulted from pedestrian dynamic. The
Preferred Force which is a measurement of pedestrian-s motivation to
adapt his actual velocity to his desired velocity is an essential term on
which the model was set up. This Force has gone through stages of
development: first of all, Helbing and Molnar (1995) have modeled
the original force for the normal situation. Second, Helbing and his
co-workers (2000) have incorporated the panic situation into this
force by incorporating the panic parameter to account for the panic
situations. Third, Lakoba and Kaup (2005) have provided the
pedestrians some kind of intelligence by incorporating aspects of the
decision-making capability. In this paper, the authors analyze the
most important incorporations into the model regarding the preferred
force. They make comparisons between the different factors of these
incorporations. Furthermore, to enhance the decision-making ability
of the pedestrians, they introduce additional features such as the
familiarity factor to the preferred force to let it appear more
representative of what actually happens in reality.
Statistical Analysis of Different Configurations of Hybrid Doped Fiber Amplifiers
Wavelength multiplexing (WDM) technology along
with optical amplifiers is used for optical communication systems in
S-band, C-band and L-band. To improve the overall system
performance Hybrid amplifiers consisting of cascaded TDFA and
EDFA with different gain bandwidths are preferred for long haul
wavelength multiplexed optical communication systems. This paper
deals with statistical analysis of different configuration of hybrid
amplifier i.e. analysis of TDFA-EDFA configuration and EDFA –
TDFA configuration. In this paper One-Way ANOVA method is used
for statistical analysis.
New Feed-Forward/Feedback Generalized Minimum Variance Self-tuning Pole-placement Controller
A new Feed-Forward/Feedback Generalized
Minimum Variance Pole-placement Controller to incorporate the
robustness of classical pole-placement into the flexibility of
generalized minimum variance self-tuning controller for Single-Input
Single-Output (SISO) has been proposed in this paper. The design,
which provides the user with an adaptive mechanism, which ensures
that the closed loop poles are, located at their pre-specified positions.
In addition, the controller design which has a feed-forward/feedback
structure overcomes the certain limitations existing in similar poleplacement
control designs whilst retaining the simplicity of
adaptation mechanisms used in other designs. It tracks set-point
changes with the desired speed of response, penalizes excessive
control action, and can be applied to non-minimum phase systems.
Besides, at steady state, the controller has the ability to regulate the
constant load disturbance to zero. Example simulation results using
both simulated and real plant models demonstrate the effectiveness of
the proposed controller.
Design Optimization for Efficient Erbium-Doped Fiber Amplifiers
The exact gain shape profile of erbium doped fiber
amplifiers (EDFA`s) are depends on fiber length and Er3 ion
densities. This paper optimized several of erbium doped fiber
parameters to obtain high performance characteristic at pump
wavelengths of λp= 980 nm and λs= 1550 nm for three different
pump powers. The maximum gain obtained for pump powers (10, 30
and 50mw) is nearly (19, 30 and 33 dB) at optimizations. The
required numerical aperture NA to obtain maximum gain becomes
less when pump power increased. The amplifier gain is increase
when Er+3doped near the center of the fiber core. The simulation has
been done by using optisystem 5.0 software (CAD for Photonics, a
license product of a Canadian based company) at 2.5 Gbps.
Identification of Flexographic-printed Newspapers with NIR Spectral Imaging
Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
Enhanced Character Based Algorithm for Small Parsimony
Phylogenetic tree is a graphical representation of the
evolutionary relationship among three or more genes or organisms.
These trees show relatedness of data sets, species or genes
divergence time and nature of their common ancestors. Quality of a
phylogenetic tree requires parsimony criterion. Various approaches
have been proposed for constructing most parsimonious trees. This
paper is concerned about calculating and optimizing the changes of
state that are needed called Small Parsimony Algorithms. This paper
has proposed enhanced small parsimony algorithm to give better
score based on number of evolutionary changes needed to produce
the observed sequence changes tree and also give the ancestor of the
Different Approaches for the Design of IFIR Compaction Filter
Optimization of filter banks based on the knowledge of input statistics has been of interest for a long time. Finite impulse response (FIR) Compaction filters are used in the design of optimal signal adapted orthonormal FIR filter banks. In this paper we discuss three different approaches for the design of interpolated finite impulse response (IFIR) compaction filters. In the first method, the magnitude squared response satisfies Nyquist constraint approximately. In the second and third methods Nyquist constraint is exactly satisfied. These methods yield FIR compaction filters whose response is comparable with that of the existing methods. At the same time, IFIR filters enjoy significant saving in the number of multipliers and can be implemented efficiently. Since eigenfilter approach is used here, the method is less complex. Design of IFIR filters in the least square sense is presented.
The Coverage of the Object-Oriented Framework Application Class-Based Test Cases
An application framework provides a reusable
design and implementation for a family of software systems.
Frameworks are introduced to reduce the cost of a product line
(i.e., family of products that share the common features). Software
testing is a time consuming and costly ongoing activity during the
application software development process. Generating reusable test
cases for the framework applications at the framework
development stage, and providing and using the test cases to test
part of the framework application whenever the framework is used
reduces the application development time and cost considerably.
Framework Interface Classes (FICs) are classes introduced by
the framework hooks to be implemented at the application
development stage. They can have reusable test cases generated at
the framework development stage and provided with the
framework to test the implementations of the FICs at the
application development stage. In this paper, we conduct a case
study using thirteen applications developed using three
frameworks; one domain oriented and two application oriented.
The results show that, in general, the percentage of the number of
FICs in the applications developed using domain frameworks is, on
average, greater than the percentage of the number of FICs in the
applications developed using application frameworks.
Consequently, the reduction of the application unit testing time
using the reusable test cases generated for domain frameworks is,
in general, greater than the reduction of the application unit testing
time using the reusable test cases generated for application
Online Control of Knitted Fabric Quality: Loop Length Control
Circular knitting machine makes the fabric with more than two knitting tools. Variation of yarn tension between different knitting tools causes different loop length of stitches duration knitting process. In this research, a new intelligent method is applied to control loop length of stitches in various tools based on ideal shape of stitches and real angle of stitches direction while different loop length of stitches causes stitches deformation and deviation those of angle. To measure deviation of stitch direction against variation of tensions, image processing technique was applied to pictures of different fabrics with constant front light. After that, the rate of deformation is translated to needed compensation of loop length cam degree to cure stitches deformation. A fuzzy control algorithm was applied to loop length modification in knitting tools. The presented method was experienced for different knitted fabrics of various structures and yarns. The results show that presented method is useable for control of loop length variation between different knitting tools based on stitch deformation for various knitted fabrics with different fabric structures, densities and yarn types.