Abstract: The flow field within the combustor of scramjet
engine is very complex and poses a considerable challenge in the
design and development of a supersonic combustor with an optimized
geometry. In this paper comprehensive numerical studies on flow
field characteristics of different cavity based scramjet combustors
with transverse injection of hydrogen have been carried out for both
non-reacting and reacting flows. The numerical studies have been
carried out using a validated 2D unsteady, density based 1st-order
implicit k-omega turbulence model with multi-component finite rate
reacting species. The results show a wide variety of flow features
resulting from the interactions between the injector flows, shock
waves, boundary layers, and cavity flows. We conjectured that an
optimized cavity is a good choice to stabilize the flame in the
hypersonic flow, and it generates a recirculation zone in the scramjet
combustor. We comprehended that the cavity based scramjet
combustors having a bearing on the source of disturbance for the
transverse jet oscillation, fuel/air mixing enhancement, and flameholding
improvement. We concluded that cavity shape with
backward facing step and 45o forward ramp is a good choice to get
higher temperatures at the exit compared to other four models of
scramjet combustors considered in this study.
Abstract: An approach is offered for more precise definition of base lines- borders in handwritten cursive text and general problems of handwritten text segmentation have also been analyzed. An offered method tries to solve problems arose in handwritten recognition with specific slant or in other words, where the letters of the words are not on the same vertical line. As an informative features, some recognition systems use ascending and descending parts of the letters, found after the word-s baseline detection. In such recognition systems, problems in baseline detection, impacts the quality of the recognition and decreases the rate of the recognition. Despite other methods, here borders are found by small pieces containing segmentation elements and defined as a set of linear functions. In this method, separate borders for top and bottom border lines are found. At the end of the paper, as a result, azerbaijani cursive handwritten texts written in Latin alphabet by different authors has been analyzed.
Abstract: In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.
Abstract: A novel low-cost flight simulator with the development
goals cost effectiveness and high performance has been realized for
meeting the huge pilot training needs of airlines. The simulator
consists of an aircraft dynamics model, a sophisticated designed
low-profile electrical driven motion system with a subsided cabin, a
mixed reality based semi-virtual cockpit system, a control loading
system and some other subsystems. It shows its advantages over
traditional flight simulator by its features achieved with open
architecture, software solutions and low-cost hardware.
Abstract: Naive Bayes Nearest Neighbor (NBNN) and its variants, i,e., local NBNN and the NBNN kernels, are local feature-based classifiers that have achieved impressive performance in image classification. By exploiting instance-to-class (I2C) distances (instance means image/video in image/video classification), they avoid quantization errors of local image descriptors in the bag of words (BoW) model. However, the performances of NBNN, local NBNN and the NBNN kernels have not been validated on video analysis. In this paper, we introduce these three classifiers into human action recognition and conduct comprehensive experiments on the benchmark KTH and the realistic HMDB datasets. The results shows that those I2C based classifiers consistently outperform the SVM classifier with the BoW model.
Abstract: Heavy metals have bad effects on environment and
soils and it can uptake by natural HAP .natural Hap is an inexpensive
material that uptake large amounts of various heavy metals like Zn
(II) .Natural HAP (N-HAP), extracted from bovine cortical bone ash,
is a good choice for substitution of commercial HAP. Several
experiments were done to investigate the sorption capacity of Zn (II)
to N-HAP in various particles sizes, temperatures, initial
concentrations, pH and reaction times. In this study, the sorption of
Zinc ions from a Zn solution onto HAP particles with sizes of 1537.6
nm and 47.6 nm at three initial pH values of 4.50, 6.00 and 7.50 was
studied. The results showed that better performance was obtained
through a 47.6 nm particle size and higher pH values. The
experimental data were analyzed using Langmuir, Freundlich, and
Arrhenius equations for equilibrium, kinetic and thermodynamic
studies. The analysis showed a maximum adsorption capacity of NHAP
as being 1.562 mmol/g at a pH of 7.5 and small particle size.
Kinetically, the prepared N-HAP is a feasible sorbent that retains Zn
(II) ions through a favorable and spontaneous sorption process.
Abstract: Human pose estimation can be executed using Active Shape Models. The existing techniques for applying to human-body research using Active Shape Models, such as human detection, primarily take the form of silhouette of human body. This technique is not able to estimate accurately for human pose to concern two arms and legs, as the silhouette of human body represents the shape as out of round. To solve this problem, we applied the human body model as stick-figure, “skeleton". The skeleton model of human body can give consideration to various shapes of human pose. To obtain effective estimation result, we applied background subtraction and deformed matching algorithm of primary Active Shape Models in the fitting process. The images which were used to make the model were 600 human bodies, and the model has 17 landmark points which indicate body junction and key features of human pose. The maximum iteration for the fitting process was 30 times and the execution time was less than .03 sec.
Abstract: In this paper, we present the 2006 survey study origin destination and price that we carried out during 2006 fall in the area in the Moroccan region of Rabat-Salé-Zemmour-Zaer. The survey concerns the people-s characteristics, their displacements behavior and the price that they will be able to pay for a tramway ticket. The main objective is to study a set of relative features to the households and to their displacement's habits and to their choices among public and privet transport modes. A comparison between this survey results and that of the 1996's is made. A pricing scheme is also given according to the tram capacity. (The Rabat-Salé tramway is under construction right now and it will be operational beginning 2010).
Abstract: A kind of behavior model for discrete sampling and hold amplifier with charge transmission is analyzed. The transfer function and behavior features are based on the main AC responses of operation amplifier. The result used in pipelined and sigma-delta ADC shows the exact of model of sampling and hold amplifier, and the non-ideal factors are taken into account.
Abstract: This text studies glass bottle intelligent inspector
based machine vision instead of manual inspection. The system
structure is illustrated in detail in this paper. The text presents the
method based on watershed transform methods to segment the
possible defective regions and extract features of bottle wall by rules.
Then wavelet transform are used to exact features of bottle finish
from images. After extracting features, the fuzzy support vector
machine ensemble is putted forward as classifier. For ensuring that
the fuzzy support vector machines have good classification ability,
the GA based ensemble method is used to combining the several
fuzzy support vector machines. The experiments demonstrate that
using this inspector to inspect glass bottles, the accuracy rate may
reach above 97.5%.
Abstract: In this paper, the problem of finding the optimal
topological configuration of a deregulated distribution network is
considered. The new features of this paper are proposing a multiobjective
function and its application on deregulated distribution
networks for finding the optimal configuration. The multi-objective
function will be defined for minimizing total Energy Supply Costs
(ESC) and energy losses subject to load flow constraints. The
optimal configuration will be obtained by using Binary Genetic
Algorithm (BGA).The proposed method has been tested to analyze a
sample and a practical distribution networks.
Abstract: The use of contour strips of perennial vegetation with
bio-fuel potential can improve surface water quality by reducing
NO3-N and sediment outflow from cropland to surface water-bodies.
It also has economic benefits of producing ethanol. In this study,
The Soil and Water Assessment Tool (SWAT) model was applied to
a watershed in Iowa, USA to examine the effectiveness of contour
strips of switch grass in reducing the NO3-N outflows from crop
fields to rivers or lakes. Numerical experiments were conducted to
identify potential subbasins in the watershed that have high water
quality impact, and to examine the effects of strip size on NO3-N
reduction under various meteorological conditions, i.e. dry, average
and wet years. Useful information was obtained for the evaluation of
economic feasibility of growing switch grass for bio-fuel in contour
strips. The results can assist in cost-benefit analysis and decisionmaking
in best management practices for environmental protection.
Abstract: This paper focuses on the integration of hybrid renewable energy resources available in remote isolated islands of Sundarban-24 Parganas-South of Eastern part of India to National Grid of conventional power supply to give a Smart-Grid scenario. Before grid-integration, feasibility of optimization of hybrid renewable energy system is monitored through an Intelligent Controller proposed to be installed at Moushuni Island of Sundarban. The objective is to ensure the reliability and efficiency of the system to optimize the utilization of the hybrid renewable energy sources and also a proposition of how theses isolated Hybrid Renewable Energy Systems at remote islands can be grid-connected is analyzed towards vision of green smart-grid.
Abstract: Asynchronous Transfer Mode (ATM) is widely used
in telecommunications systems to send data, video and voice at a
very high speed. In ATM network optimizing the bandwidth through
dynamic routing is an important consideration. Previous research
work shows that traditional optimization heuristics result in suboptimal
solution. In this paper we have explored non-traditional
optimization technique. We propose comparison of two such
algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on
non-traditional Optimization approach, for solving the dynamic
routing problem in ATM networks which in return will optimize the
bandwidth. The optimized bandwidth could mean that some
attractive business applications would become feasible such as high
speed LAN interconnection, teleconferencing etc. We have also
performed a comparative study of the selection mechanisms in GA
and listed the best selection mechanism and a new initialization
technique which improves the efficiency of the GA.
Abstract: Recently many research has been conducted to
retrieve pertinent parameters and adequate models for automatic
music genre classification. In this paper, two measures based upon
information theory concepts are investigated for mapping the features
space to decision space. A Gaussian Mixture Model (GMM) is used
as a baseline and reference system. Various strategies are proposed
for training and testing sessions with matched or mismatched
conditions, long training and long testing, long training and short
testing. For all experiments, the file sections used for testing are
never been used during training. With matched conditions all
examined measures yield the best and similar scores (almost 100%).
With mismatched conditions, the proposed measures yield better
scores than the GMM baseline system, especially for the short testing
case. It is also observed that the average discrimination information
measure is most appropriate for music category classifications and on
the other hand the divergence measure is more suitable for music
subcategory classifications.
Abstract: The scroll pump belongs to the category of positive
displacement pump can be used for continuous pumping of gases at
low pressure apart from general vacuum application. The shape of
volume occupied by the gas moves and deforms continuously as the
spiral orbits. To capture flow features in such domain where mesh
deformation varies with time in a complicated manner, mesh less
solver was found to be very useful. Least Squares Kinetic Upwind
Method (LSKUM) is a kinetic theory based mesh free Euler solver
working on arbitrary distribution of points. Here upwind is enforced
in molecular level based on kinetic flux vector splitting scheme
(KFVS). In the present study we extended the LSKUM to moving
node viscous flow application. This new code LSKUM-NS-MN for
moving node viscous flow is validated for standard airfoil pitching
test case. Simulation performed for flow through scroll pump using
LSKUM-NS-MN code agrees well with the experimental pumping
speed data.
Abstract: For today-s and future wireless communications applications,
more and more data traffic has to be transmitted with
growing speed and quality demands. The analog front-end of any
mobile device has to cope with very hard specifications regardless
which transmission standard has to be supported. State-of-the-art
analog front-end implementations are reaching the limit of technical
feasibility. For that reason, alternative front-end architectures could
support a continuing development of mobile communications e.g.,
six-port-based front-ends [1], [2].
In this article we propose an analog front-end with high intermediate
frequency and which utilizes additive mixing instead
of multiplicative mixing. The system architecture is presented and
several spurious effects as well as their influence on the system
dimensioning are discussed. Furthermore, several issues concerning
the technical feasibility are provided and some simulation results
are discussed which show the principle functionality of the proposed
superposition heterodyne receiver.
Abstract: The use of Quantum dots is a promising emerging
Technology for implementing digital system at the nano level. It is
effecient for attractive features such as faster speed , smaller size and
low power consumption than transistor technology. In this paper,
various Combinational and sequential logical structures - HALF
ADDER, SR Latch and Flip-Flop, D Flip-Flop preceding NAND,
NOR, XOR,XNOR are discussed based on QCA design, with
comparatively less number of cells and area. By applying these
layouts, the hardware requirements for a QCA design can be reduced.
These structures are designed and simulated using QCA Designer
Tool. By taking full advantage of the unique features of this
technology, we are able to create complete circuits on a single layer
of QCA. Such Devices are expected to function with ultra low
power Consumption and very high speeds.
Abstract: An effective visual error concealment method has been presented by employing a robust rotation, scale, and translation (RST) invariant partial patch matching model (RSTI-PPMM) and
exemplar-based inpainting. While the proposed robust and inherently
feature-enhanced texture synthesis approach ensures the generation
of excellent and perceptually plausible visual error concealment results, the outlier pruning property guarantees the significant quality improvements, both quantitatively and qualitatively. No intermediate
user-interaction is required for the pre-segmented media and the
presented method follows a bootstrapping approach for an automatic
visual loss recovery and the image and video error concealment.
Abstract: The increasing importance of FlexRay systems in
automotive domain inspires unceasingly relative researches. One
primary issue among researches is to verify the reliability of FlexRay
systems either from protocol aspect or from system design aspect.
However, research rarely discusses the effect of network topology on
the system reliability. In this paper, we will illustrate how to model
the reliability of FlexRay systems with various network topologies by
a well-known probabilistic reasoning technology, Bayesian Network.
In this illustration, we especially investigate the effectiveness of error
containment built in star topology and fault-tolerant midpoint
synchronization algorithm adopted in FlexRay communication
protocol. Through a FlexRay steer-by-wire case study, the influence
of different topologies on the failure probability of the FlexRay steerby-
wire system is demonstrated. The notable value of this research is
to show that the Bayesian Network inference is a powerful and
feasible method for the reliability assessment of FlexRay systems.