Abstract: In this paper presents a technique for developing the
computational efficiency in simulating double output induction
generators (DOIG) with two rotor circuits where stator transients are
to be included. Iterative decomposition is used to separate the flux–
Linkage equations into decoupled fast and slow subsystems, after
which the model order of the fast subsystems is reduced by
neglecting the heavily damped fast transients caused by the second
rotor circuit using integral manifolds theory. The two decoupled
subsystems along with the equation for the very slowly changing slip
constitute a three time-scale model for the machine which resulted in
increasing computational speed. Finally, the proposed method of
reduced order in this paper is compared with the other conventional
methods in linear and nonlinear modes and it is shown that this
method is better than the other methods regarding simulation
accuracy and speed.
Abstract: Signal processing applications which are iterative in
nature are best represented by data flow graphs (DFG). In these
applications, the maximum sampling frequency is dependent on the
topology of the DFG, the cyclic dependencies in particular. The
determination of the iteration bound, which is the reciprocal of the
maximum sampling frequency, is critical in the process of hardware
implementation of signal processing applications. In this paper, a
novel technique to compute the iteration bound is proposed. This
technique is different from all previously proposed techniques, in the
sense that it is based on the natural flow of tokens into the DFG
rather than the topology of the graph. The proposed algorithm has
lower run-time complexity than all known algorithms. The
performance of the proposed algorithm is illustrated through
analytical analysis of the time complexity, as well as through
simulation of some benchmark problems.
Abstract: Embedding and extraction of a secret information as
well as the restoration of the original un-watermarked image is
highly desirable in sensitive applications like military, medical, and
law enforcement imaging. This paper presents a novel reversible
data-hiding method for digital images using integer to integer
wavelet transform and companding technique which can embed and
recover the secret information as well as can restore the image to its
pristine state. The novel method takes advantage of block based
watermarking and iterative optimization of threshold for companding
which avoids histogram pre and post-processing. Consequently, it
reduces the associated overhead usually required in most of the
reversible watermarking techniques. As a result, it keeps the
distortion small between the marked and the original images.
Experimental results show that the proposed method outperforms the
existing reversible data hiding schemes reported in the literature.
Abstract: The purposes of this paper are to (1) promote
excellence in computer science by suggesting a cohesive innovative
approach to fill well documented deficiencies in current computer
science education, (2) justify (using the authors- and others anecdotal
evidence from both the classroom and the real world) why this
approach holds great potential to successfully eliminate the
deficiencies, (3) invite other professionals to join the authors in proof
of concept research. The authors- experiences, though anecdotal,
strongly suggest that a new approach involving visual modeling
technologies should allow computer science programs to retain a
greater percentage of prospective and declared majors as students
become more engaged learners, more successful problem-solvers,
and better prepared as programmers. In addition, the graduates of
such computer science programs will make greater contributions to
the profession as skilled problem-solvers. Instead of wearily
rememorizing code as they move to the next course, students will
have the problem-solving skills to think and work in more
sophisticated and creative ways.
Abstract: Surveillance system is widely used in the traffic
monitoring. The deployment of cameras is moving toward a
ubiquitous camera (UbiCam) environment. In our previous study, a
novel service, called GPS-VT, was firstly proposed by incorporating
global positioning system (GPS) and visual tracking techniques for
the UbiCam environment. The first prototype is called GODTA
(GPS-based Moving Object Detection and Tracking Approach). For a
moving person carried GPS-enabled mobile device, he can be
tracking when he enters the field-of-view (FOV) of a camera
according to his real-time GPS coordinate. In this paper, GPS-VT
service is applied to the tracking of vehicles. The moving speed of a
vehicle is much faster than a person. It means that the time passing
through the FOV is much shorter than that of a person. Besides, the
update interval of GPS coordinate is once per second, it is
asynchronous with the frame rate of the real-time image. The above
asynchronous is worsen by the network transmission delay. These
factors are the main challenging to fulfill GPS-VT service on a
vehicle.In order to overcome the influence of the above factors, a
back-propagation neural network (BPNN) is used to predict the
possible lane before the vehicle enters the FOV of a camera. Then, a
template matching technique is used for the visual tracking of a target
vehicle. The experimental result shows that the target vehicle can be
located and tracking successfully. The success location rate of the
implemented prototype is higher than that of the previous GODTA.
Abstract: The recent trend has been using hybrid approach rather than using a single intelligent technique to solve the problems. In this paper, we describe and discuss a framework to develop enterprise solutions that are backed by intelligent techniques. The framework not only uses intelligent techniques themselves but it is a complete environment that includes various interfaces and components to develop the intelligent solutions. The framework is completely Web-based and uses XML extensively. It can work like shared plat-form to be accessed by multiple developers, users and decision makers.
Abstract: The groundwater is one of the main sources for
sustainability in the United Arab Emirates (UAE). Intensive
developments in Al-Ain area lead to increase water demand, which
consequently reduced the overall groundwater quantity in major
aquifers. However, in certain residential areas within Al-Ain, it has
been noticed that the groundwater level is rising, for example in
Sha-ab Al Askher area. The reasons for the groundwater rising
phenomenon are yet to be investigated. In this work, twenty four
seismic refraction profiles have been carried out along the study
pilot area; as well as field measurement of the groundwater level in
a number of available water wells in the area. The processed
seismic data indicated the deepest and shallowest groundwater
levels are 15m and 2.3 meters respectively. This result is greatly
consistent with the proper field measurement of the groundwater
level. The minimum detected value may be referred to perched
subsurface water which may be associated to the infiltration from
the surrounding water bodies such as lakes, and elevated farms. The
maximum values indicate the accurate groundwater level within the
study area. The findings of this work may be considered as a
preliminary help to the decision makers.
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: It has been recognized that due to the autonomy and
heterogeneity, of Web services and the Web itself, new approaches
should be developed to describe and advertise Web services. The
most notable approaches rely on the description of Web services
using semantics. This new breed of Web services, termed semantic
Web services, will enable the automatic annotation, advertisement,
discovery, selection, composition, and execution of interorganization
business logic, making the Internet become a common
global platform where organizations and individuals communicate
with each other to carry out various commercial activities and to
provide value-added services. This paper deals with two of the
hottest R&D and technology areas currently associated with the Web
– Web services and the semantic Web. It describes how semantic
Web services extend Web services as the semantic Web improves the
current Web, and presents three different conceptual approaches to
deploying semantic Web services, namely, WSDL-S, OWL-S, and
WSMO.
Abstract: The development of biomimetic micro-aerial-vehicles
(MAVs) with flapping wings is the future trend in military/domestic
field. The successful flight of MAVs is strongly related to the
understanding of unsteady aerodynamic performance of low Reynolds
number airfoils under dynamic flapping motion. This study explored
the effects of flapping frequency, stroke amplitude, and the inclined
angle of stroke plane on lift force and thrust force of a bio-inspiration
corrugated airfoil with 33 full factorial design of experiment and
ANOVA analysis. Unsteady vorticity flows over a corrugated thin
airfoil executing flapping motion are computed with time-dependent
two-dimensional laminar incompressible Reynolds-averaged
Navier-Stokes equations with the conformal hybrid mesh. The tested
freestream Reynolds number based on the chord length of airfoil as
characteristic length is fixed of 103. The dynamic mesh technique is
applied to model the flapping motion of a corrugated airfoil. Instant
vorticity contours over a complete flapping cycle clearly reveals the
flow mechanisms for lift force generation are dynamic stall, rotational
circulation, and wake capture. The thrust force is produced as the
leading edge vortex shedding from the trailing edge of airfoil to form a
reverse von Karman vortex. Results also indicated that the inclined
angle is the most significant factor on both the lift force and thrust
force. There are strong interactions between tested factors which mean
an optimization study on parameters should be conducted in further
runs.
Abstract: This work presents the first results from the long-term experiment, which is focused on the impact of intensive rainfall and long period of drought on microbial activities in soil. Fifteen lysimeters were prepared in the area of our interest. This area is a protection zone of underground source of drinking water. These lysimeters were filed with topsoil and subsoil collected in this area and divided into two groups. These groups differ in fertilization and amount of water received during the growing season. Amount of microbial biomass and leaching of mineral nitrogen and phosphates were chosen as main indicators of microbial activities in soil. Content of mineral nitrogen and phosphates was measured in soil solution, which was collected from each lysimeters. Amount of microbial biomass was determined in soil samples that were taken from the lysimeters before and after the long period of drought and intensive rainfall.
Abstract: Beta-spline is built on G2 continuity which guarantees
smoothness of generated curves and surfaces using it. This curve is
preferred to be used in object design rather than reconstruction. This
study however, employs the Beta-spline in reconstructing a 3-
dimensional G2 image of the Stanford Rabbit. The original data
consists of multi-slice binary images of the rabbit. The result is then
compared with related works using other techniques.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: The aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.
Abstract: The increasing development of wireless networks and
the widespread popularity of handheld devices such as Personal
Digital Assistants (PDAs), mobile phones and wireless tablets
represents an incredible opportunity to enable mobile devices as a
universal payment method, involving daily financial transactions.
Unfortunately, some issues hampering the widespread acceptance of
mobile payment such as accountability properties, privacy protection,
limitation of wireless network and mobile device. Recently, many
public-key cryptography based mobile payment protocol have been
proposed. However, limited capabilities of mobile devices and
wireless networks make these protocols are unsuitable for mobile
network. Moreover, these protocols were designed to preserve
traditional flow of payment data, which is vulnerable to attack and
increase the user-s risk. In this paper, we propose a private mobile
payment protocol which based on client centric model and by
employing symmetric key operations. The proposed mobile payment
protocol not only minimizes the computational operations and
communication passes between the engaging parties, but also
achieves a completely privacy protection for the payer. The future
work will concentrate on improving the verification solution to
support mobile user authentication and authorization for mobile
payment transactions.
Abstract: This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.
Abstract: The daily increase of organic waste materials resulting
from different activities in the country is one of the main factors for
the pollution of environment. Today, with regard to the low level of
the output of using traditional methods, the high cost of disposal
waste materials and environmental pollutions, the use of modern
methods such as anaerobic digestion for the production of biogas has
been prevailing. The collected biogas from the process of anaerobic
digestion, as a renewable energy source similar to natural gas but
with a less methane and heating value is usable. Today, with the help
of technologies of filtration and proper preparation, access to biogas
with features fully similar to natural gas has become possible. At
present biogas is one of the main sources of supplying electrical and
thermal energy and also an appropriate option to be used in four
stroke engine, diesel engine, sterling engine, gas turbine, gas micro
turbine and fuel cell to produce electricity. The use of biogas for
different reasons which returns to socio-economic and environmental
advantages has been noticed in CHP for the production of energy in
the world. The production of biogas from the technology of anaerobic
digestion and its application in CHP power plants in Iran can not only
supply part of the energy demands in the country, but it can
materialize moving in line with the sustainable development. In this
article, the necessity of the development of CHP plants with biogas
fuels in the country will be dealt based on studies performed from the
economic, environmental and social aspects. Also to prove the
importance of the establishment of these kinds of power plants from
the economic point of view, necessary calculations has been done as
a case study for a CHP power plant with a biogas fuel.
Abstract: The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.
Abstract: This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.
Abstract: We report in this paper the procedure of a system of
automatic speech recognition based on techniques of the dynamic
programming. The technique of temporal retiming is a technique
used to synchronize between two forms to compare. We will see how
this technique is adapted to the field of the automatic speech
recognition. We will expose, in a first place, the theory of the
function of retiming which is used to compare and to adjust an
unknown form with a whole of forms of reference constituting the
vocabulary of the application. Then we will give, in the second place,
the various algorithms necessary to their implementation on machine.
The algorithms which we will present were tested on part of the
corpus of words in Arab language Arabdic-10 [4] and gave whole
satisfaction. These algorithms are effective insofar as we apply them
to the small ones or average vocabularies.