Abstract: Numerical studies have been carried out using a two
dimensional code to examine the influence of pressure / thrust
transient of solid propellant rockets at liftoff. This code solves
unsteady Reynolds-averaged thin-layer Navier–Stokes equations by
an implicit LU-factorization time-integration method. The results
from the parametric study indicate that when the port is narrow there
is a possibility of increase in pressure / thrust-rise rate due to
relatively high flame spread rate. Parametric studies further reveal
that flame spread rate can be altered by altering the propellant
properties, igniter jet characteristics and nozzle closure burst pressure
without altering the grain configuration and/or the mission
demanding thrust transient. We observed that when the igniter
turbulent intensity is relatively low the vehicle could liftoff early due
to the early flow choking of the rocket nozzle. We concluded that the
high pressurization-rate has structural implications at liftoff in
addition to transient burning effect. Therefore prudent selection of the
port geometry and the igniter, for meeting the mission requirements,
within the given envelop are meaningful objectives for any designer
for the smooth liftoff of solid propellant rockets.
Abstract: Now a days, a significant part of commercial and governmental organisations like museums, cultural organizations, libraries, commercial enterprises, etc. invest intensively in new technologies for image digitization, digital libraries, image archiving and retrieval. Hence image authorization, authentication and security has become prime need. In this paper, we present a semi-fragile watermarking scheme for color images. The method converts the host image into YIQ color space followed by application of orthogonal dual domains of DCT and DWT transforms. The DCT helps to separate relevant from irrelevant image content to generate silent image features. DWT has excellent spatial localisation to help aid in spatial tamper characterisation. Thus image adaptive watermark is generated based of image features which allows the sharp detection of microscopic changes to locate modifications in the image. Further, the scheme utilises the multipurpose watermark consisting of soft authenticator watermark and chrominance watermark. Which has been proved fragile to some predefined processing like intentinal fabrication of the image or forgery and robust to other incidental attacks caused in the communication channel.
Abstract: the reliability analysis of the medical equipments can
help to increase the availability and the efficiency of the systems. In
this manuscript we present a simple method of decomposition that
could be easily applied on the complex medical systems. Using this
method we can easily calculate the effect of the subsystems or
components on the reliability of the overall system. Furthermore, to
investigate the effect of subsystems or components on system
performance, we perform a numerical study varying every time the
worst reliability of subsystem or component with another which has
higher reliability. It can also be useful to engineers and designers of
medical equipment, who wishes to optimize the complex systems.
Abstract: In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.
Abstract: The aim of this study was to establish the relationship between the principles of Educational Sport and the objectives of Physical Education in two brasilian laws: National Curriculum Guidelines (PCNs) for the Elementary and Middle School Levels and the Guidelines and Basis Legislation (LDB). The method used was the survey analysis in order to determine the practices present in, or the opinions of, a specific population. The instrument used in this research was a questionnaire. After a broad review of the bibliography and according to the methodological procedures, the aim was to set the relationships between the Principles of Educational Sport and the objectives of Physical Education, according to the Brazilian Law (LDB) and National Curriculum Guidelines (PCNs) in a table made under the analysis of a group of specialists. As the relation between the principles of Educational Sport and the objectives of School Physical Education have shown, we can state that School Physical Education has gained pedagogical security for the potential use of Educational Sport as part of its contents.
Abstract: The volume of XML data exchange is explosively
increasing, and the need for efficient mechanisms of XML data
management is vital. Many XML storage models have been proposed
for storing XML DTD-independent documents in relational database
systems. Benchmarking is the best way to highlight pros and cons of
different approaches. In this study, we use a common benchmarking
scheme, known as XMark to compare the most cited and newly
proposed DTD-independent methods in terms of logical reads,
physical I/O, CPU time and duration. We show the effect of Label
Path, extracting values and storing in another table and type of join
needed for each method-s query answering.
Abstract: Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.
Abstract: Noble metal participation in nanostructured
semiconductor catalysts has drawn much interest because of their
improved properties. Recently, it has been discussed by many
researchers that Ag participation in TiO2, CuO, ZnO semiconductors
showed improved photocatalytic and optical properties. In this
research, Ag/ZnO nanocomposite particles were prepared by
Ultrasonic Spray Pyrolysis(USP) Method. 0.1M silver and zinc
nitrate aqueous solutions were used as precursor solutions. The
Ag:Zn atomic ratio of the solution was selected 1:1. Experiments
were taken place under constant air flow of 400 mL/min at 800°C
furnace temperature. Particles were characterized by X-Ray
Diffraction (XRD), Scanning Electron Microscope (SEM) and
Energy Dispersive Spectroscopy (EDS). The crystallite sizes of Ag
and ZnO in composite particles are 24.6 nm, 19.7 nm respectively.
Although, spherical nanocomposite particles are in a range of 300-
800 nm, these particles are formed by the aggregation of primary
particles which are in a range of 20-60 nm.
Abstract: Several methods are available for weight and shape
optimization of structures, among which Evolutionary Structural
Optimization (ESO) is one of the most widely used methods. In ESO,
however, the optimization criterion is completely case-dependent.
Moreover, only the improving solutions are accepted during the
search. In this paper a Simulated Annealing (SA) algorithm is used
for structural optimization problem. This algorithm differs from other
random search methods by accepting non-improving solutions. The
implementation of SA algorithm is done through reducing the
number of finite element analyses (function evaluations).
Computational results show that SA can efficiently and effectively
solve such optimization problems within short search time.
Abstract: This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.
Abstract: In this paper challenges associated with a new
generation of Computer Science students are examined. The mode of
education in tertiary institutes has progressed slowly while the needs
of students have changed rapidly in an increasingly technological
world. The major learning paradigms and learning theories within
these paradigms are studied to find a suitable strategy for educating
modern students. These paradigms include Behaviourism,
Constructivism, Humanism and Cogntivism. Social Learning theory
and Elaboration theory are two theories that are further examined and
a survey is done to determine how these strategies will be received by
students. The results and findings are evaluated and indicate that
students are fairly receptive to a method that incorporates both Social
Learning theory and Elaboration theory, but that some aspects of all
paradigms need to be implemented to create a balanced and effective
strategy with technology as foundation.
Abstract: Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.
Abstract: The cumulative conformance count (CCC) charts are
widespread in process monitoring of high-yield manufacturing.
Recently, it is found the use of variable sampling interval (VSI)
scheme could further enhance the efficiency of the standard CCC
charts. The average time to signal (ATS) a shift in defect rate has
become traditional measure of efficiency of a chart with the VSI
scheme. Determining the ATS is frequently a difficult and tedious
task. A simple method based on a finite Markov Chain approach for
modeling the ATS is developed. In addition, numerical results are
given.
Abstract: Several numerical schemes utilizing central difference
approximations have been developed to solve the Goursat problem.
However, in a recent years compact discretization methods which
leads to high-order finite difference schemes have been used since it
is capable of achieving better accuracy as well as preserving certain
features of the equation e.g. linearity. The basic idea of the new
scheme is to find the compact approximations to the derivative terms
by differentiating centrally the governing equations. Our primary
interest is to study the performance of the new scheme when applied
to two Goursat partial differential equations against the traditional
finite difference scheme.
Abstract: Independent component analysis can estimate unknown
source signals from their mixtures under the assumption that the
source signals are statistically independent. However, in a real environment,
the separation performance is often deteriorated because
the number of the source signals is different from that of the sensors.
In this paper, we propose an estimation method for the number of
the sources based on the joint distribution of the observed signals
under two-sensor configuration. From several simulation results, it
is found that the number of the sources is coincident to that of
peaks in the histogram of the distribution. The proposed method can
estimate the number of the sources even if it is larger than that of
the observed signals. The proposed methods have been verified by
several experiments.
Abstract: Biomechanical properties of infantile aorta in vitro in
cases of different standard anastomoses: end-to-end (ETE), extended
anastomosis end-to-end (EETE) and subclavian flap aortoplasty
(SFA) used for surgical correction of coarctation were analyzed to
detect the influence of the method on the biomechanics of infantile
aorta and possible changes in haemodinamics. 10 specimens of native
aorta, 3 specimens with ETE, 4 EEET and 3 SFA were investigated.
The experiments showed a non-linear relationship between stress and
strain in the infantile aorta, the modulus of elasticity of the aortic wall
increased with the increase of inner pressure. In the case of
anastomosis end-to-end the modulus was almost constant, relevant to
the modulus of elasticity of the aorta with the inner pressure 100-120
mmHg. The anastomoses EETE and SFA showed elastic properties
closer to native aorta, the stiffness of ETE did not change with the
changes in inner pressure.
Abstract: A novel and versatile numerical technique to solve a self-stress equilibrium state is adopted herein as a form-finding procedure for an irregular tensegrity structure. The numerical form-finding scheme of a tensegrity structure uses only the connectivity matrix and prototype tension coefficient vector as the initial guess solution. Any information on the symmetrical geometry or other predefined initial structural conditions is not necessary to get the solution in the form-finding process. An eight-node initial condition example is presented to demonstrate the efficiency and robustness of the proposed method in the form-finding of an irregular tensegrity structure. Based on the conception from the form-finding of an eight-node irregular tensegrity structure, a monumental object is designed by considering the real world situation such as self-weight, wind and earthquake loadings.
Abstract: In this paper we use the property of co-occurrence
matrix in finding parallel lines in binary pictures for fingerprint
identification. In our proposed algorithm, we reduce the noise by
filtering the fingerprint images and then transfer the fingerprint
images to binary images using a proper threshold. Next, we divide
the binary images into some regions having parallel lines in the same
direction. The lines in each region have a specific angle that can be
used for comparison. This method is simple, performs the
comparison step quickly and has a good resistance in the presence of
the noise.
Abstract: The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expressed as integer number), the worst-case running time of the proposed algorithm is O (n x (B+1)), which makes the proposed method a very efficient tool
for solving the optimal risk reduction problem in the railway industry.
Abstract: Intrusion detection is a mechanism used to protect a
system and analyse and predict the behaviours of system users. An
ideal intrusion detection system is hard to achieve due to
nonlinearity, and irrelevant or redundant features. This study
introduces a new anomaly-based intrusion detection model. The
suggested model is based on particle swarm optimisation and
nonlinear, multi-class and multi-kernel support vector machines.
Particle swarm optimisation is used for feature selection by applying
a new formula to update the position and the velocity of a particle;
the support vector machine is used as a classifier. The proposed
model is tested and compared with the other methods using the KDD
CUP 1999 dataset. The results indicate that this new method achieves
better accuracy rates than previous methods.