Abstract: Plasma plume will be produced and arrive at spacecraft when the electric thruster operates on orbit. It-s important to characterize the thruster plasma parameters because the plume has significant effects or hazards on spacecraft sub-systems and parts. Through the ground test data of the desired parameters, the major characteristics of the thruster plume will be achieved. Also it is very important for optimizing design of Ion thruster. Retarding Potential Analyzer (RPA) is an effective instrument for plasma ion energy per unit charge distribution measurement. Special RPA should be designed according to certain plume plasma parameters range and feature. In this paper, major principles usable for good RPA design are discussed carefully. Conform to these principles, a four-grid planar electrostatic energy analyzer RPA was designed to avoid false data, and details were discussed including construction, materials, aperture diameter and so on. At the same time, it was designed more suitable for credible and long-duration measurements in the laboratory. In the end, RPA measurement results in the laboratory were given and discussed.
Abstract: Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images, may cause misalignments. To handle with this limitation, we propose to extract the salient edges and extracted control points (CP) of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT) that finds the best feature points. The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). The experimental results showed that the proposed method produces totally accurate performance for registration medical CT-MR images.
Abstract: With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.
Abstract: A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.
Abstract: Citizens are increasingly are provided with choice and
customization in public services and this has now also become a key
feature of higher education in terms of policy roll-outs on personal
development planning (PDP) and more generally as part of the
employability agenda. The goal here is to transform people, in this
case graduates, into active, responsible citizen-workers. A key part of
this rhetoric and logic is the inculcation of graduate attributes within
students. However, there has also been a concern with the issue of
student lack of engagement and perseverance with their studies. This
paper sets out to explore some of these conceptions that link graduate
attributes with citizenship as well as the notion of how identity is
forged through the higher education process. Examples are drawn
from a quality enhancement project that is being operated within the
context of the Scottish higher education system. This is further
framed within the wider context of competing and conflicting
demands on higher education, exacerbated by the current worldwide
economic climate. There are now pressures on students to develop
their employability skills as well as their capacity to engage with
global issues such as behavioural change in the light of
environmental concerns. It is argued that these pressures, in effect,
lead to a form of personalization that is concerned with how
graduates develop their sense of identity as something that is
engineered and re-engineered to meet these demands.
Abstract: The production and consumption of natural gas is on
the rise throughout the world as a result of its wide availability, ease
of transportation, use and clean-burning characteristics. The chief use
of ethane is in the chemical industry in the production of Ethene
(ethylene) by steam cracking. In this simulation, obtained ethane
recovery percent based on Gas sub-cooled process (GSP) is 99.9 by
mole that is included 32.1% by using de-methanizer column and
67.8% by de-ethanizer tower. The outstanding feature of this process
is the novel split-vapor concept that employs to generate reflux for
de-methanizer column. Remain amount of ethane in export gas cause
rise in gross heating value up to 36.66 MJ/Nm3 in order to use in
industrial and household consumptions.
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: 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: 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: 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.