Abstract: Supersonic open and closed cavity flows are investigated experimentally and computationally. Free stream Mach number of two is set. Schlieren imaging is used to visualise the flow behaviour showing stark differences between open and closed. Computational Fluid Dynamics (CFD) is used to simulate open cavity of flow with aspect ratio of 4. A rear wall treatment is implemented in order to pursue a simple passive control approach. Good qualitative agreement is achieved between the experimental flow visualisation and the CFD in terms of the expansion-shock waves system. The cavity oscillations are shown to be dominated by the first and third Rossister modes combining to high fluctuations of non-linear nature above the cavity rear edge. A simple rear wall treatment in terms of a hole shows mixed effect on the flow oscillations, RMS contours, and time history density fluctuations are given and analysed.
Abstract: Well-developed strategic marketing planning is the essential
prerequisite for establishment of the right and unique competitive
advantage. Typical market, however, is a heterogeneous
and decentralized structure with natural involvement of individual
or group subjectivity and irrationality. These features cannot be
fully expressed with one-shot rigorous formal models based on,
e.g. mathematics, statistics or empirical formulas. We present an
innovative solution, extending the domain of agent based computational
economics towards the concept of hybrid modeling in service
provider and consumer market such as telecommunications. The
behavior of the market is described by two classes of agents -
consumer and service provider agents - whose internal dynamics
are fundamentally different. Customers are rather free multi-state
structures, adjusting behavior and preferences quickly in accordance
with time and changing environment. Producers, on the contrary,
are traditionally structured companies with comparable internal processes
and specific managerial policies. Their business momentum is
higher and immediate reaction possibilities limited. This limitation
underlines importance of proper strategic planning as the main
process advising managers in time whether to continue with more
or less the same business or whether to consider the need for future
structural changes that would ensure retention of existing customers
or acquisition of new ones.
Abstract: The problem of incompressible steady flow simulation around an airfoil is discussed. For some simplest airfoils (circular, elliptical, Zhukovsky airfoils) the exact solution is known from complex analysis. It allows to compute the intensity of vortex layer which simulates the airfoil. Some modifications of the vortex element method are proposed and test computations are carried out. It-s shown that the these approaches are much more effective in comparison with the classical numerical scheme.
Abstract: Com Poisson distribution is capable of modeling the count responses irrespective of their mean variance relation and the parameters of this distribution when fitted to a simple cross sectional data can be efficiently estimated using maximum likelihood (ML) method. In the regression setup, however, ML estimation of the parameters of the Com Poisson based generalized linear model is computationally intensive. In this paper, we propose to use quasilikelihood (QL) approach to estimate the effect of the covariates on the Com Poisson counts and investigate the performance of this method with respect to the ML method. QL estimates are consistent and almost as efficient as ML estimates. The simulation studies show that the efficiency loss in the estimation of all the parameters using QL approach as compared to ML approach is quite negligible, whereas QL approach is lesser involving than ML approach.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents in legacy e-learning environments. It introduces the design and development of a scalable
and interoperable integration platform supporting various assessment agents for e-learning environments. The agents are implemented in
order to provide intelligent assessment services to computational intelligent techniques such as Bayesian Networks and Genetic
Algorithms. The utilization of new and emerging technologies like web services allows integrating the provided services to any web
based legacy e-learning environment.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.
Abstract: The purpose of this paper is applied Taguchi method on the optimization for PEMFC performance, and a representative Computational Fluid Dynamics (CFD) model is selectively performed for statistical analysis. The studied factors in this paper are pressure of fuel cell, operating temperature, the relative humidity of anode and cathode, porosity of gas diffusion electrode (GDE) and conductivity of GDE. The optimal combination for maximum power density is gained by using a three-level statistical method. The results confirmed that the robustness of the optimum design parameters influencing the performance of fuel cell are founded by pressure of fuel cell, 3atm; operating temperature, 353K; the relative humidity of anode, 50%; conductivity of GDE, 1000 S/m, but the relative humidity of cathode and porosity of GDE are pooled as error due to a small sum of squares. The present simulation results give designers the ideas ratify the effectiveness of the proposed robust design methodology for the performance of fuel cell.
Abstract: Due to memory leaks, often-valuable system memory
gets wasted and denied for other processes thereby affecting the
computational performance. If an application-s memory usage
exceeds virtual memory size, it can leads to system crash. Current
memory leak detection techniques for clusters are reactive and
display the memory leak information after the execution of the
process (they detect memory leak only after it occur).
This paper presents a Dynamic Memory Monitoring Agent
(DMMA) technique. DMMA framework is a dynamic memory leak
detection, that detects the memory leak while application is in
execution phase, when memory leak in any process in the cluster is
identified by DMMA it gives information to the end users to enable
them to take corrective actions and also DMMA submit the affected
process to healthy node in the system. Thus provides reliable service
to the user. DMMA maintains information about memory
consumption of executing processes and based on this information
and critical states, DMMA can improve reliability and
efficaciousness of cluster computing.
Abstract: This paper examines the forced convection flow of
incompressible, electrically conducting viscous fluid past a sharp
wedge in the presence of heat generation or absorption with an
applied magnetic field. The system of partial differential equations
governing Falkner - Skan wedge flow and heat transfer is first
transformed into a system of ordinary differential equations using
similarity transformations which is later solved using an implicit
finite - difference scheme, along with quasilinearization technique.
Numerical computations are performed for air (Pr = 0.7) and
displayed graphically to illustrate the influence of pertinent physical
parameters on local skin friction and heat transfer coefficients and,
also on, velocity and temperature fields. It is observed that the
magnetic field increases both the coefficients of skin friction and heat
transfer. The effect of heat generation or absorption is found to be
very significant on heat transfer, but its effect on the skin friction is
negligible. Indeed, the occurrence of overshoot is noticed in the
temperature profiles during heat generation process, causing the
reversal in the direction of heat transfer.
Abstract: Evolvable hardware (EHW) is a developing field that
applies evolutionary algorithm (EA) to automatically design circuits,
antennas, robot controllers etc. A lot of research has been done in this
area and several different EAs have been introduced to tackle
numerous problems, as scalability, evolvability etc. However every
time a specific EA is chosen for solving a particular task, all its
components, such as population size, initialization, selection
mechanism, mutation rate, and genetic operators, should be selected
in order to achieve the best results. In the last three decade the
selection of the right parameters for the EA-s components for solving
different “test-problems" has been investigated. In this paper the
behaviour of mutation rate for designing logic circuits, which has not
been done before, has been deeply analyzed. The mutation rate for an
EHW system modifies the number of inputs of each logic gates, the
functionality (for example from AND to NOR) and the connectivity
between logic gates. The behaviour of the mutation has been
analyzed based on the number of generations, genotype redundancy
and number of logic gates for the evolved circuits. The experimental
results found provide the behaviour of the mutation rate during
evolution for the design and optimization of simple logic circuits.
The experimental results propose the best mutation rate to be used for
designing combinational logic circuits. The research presented is
particular important for those who would like to implement a
dynamic mutation rate inside the evolutionary algorithm for evolving
digital circuits. The researches on the mutation rate during the last 40
years are also summarized.
Abstract: An efficient transient flow simulation for gas
pipelines and networks is presented. The proposed transient flow
simulation is based on the transfer function models and MATLABSimulink.
The equivalent transfer functions of the nonlinear
governing equations are derived for different types of the boundary
conditions. Next, a MATLAB-Simulink library is developed and
proposed considering any boundary condition type. To verify the
accuracy and the computational efficiency of the proposed
simulation, the results obtained are compared with those of the
conventional finite difference schemes (such as TVD, method of
lines, and other finite difference implicit and explicit schemes). The
effects of the flow inertia and the pipeline inclination are
incorporated in this simulation. It is shown that the proposed
simulation has a sufficient accuracy and it is computationally more
efficient than the other methods.
Abstract: This paper addresses an efficient technique to embed and detect digital fingerprint code. Orthogonal modulation method is a straightforward and widely used approach for digital fingerprinting but shows several limitations in computational cost and signal efficiency. Coded modulation method can solve these limitations in theory. However it is difficult to perform well in practice if host signals are not available during tracing colluders, other kinds of attacks are applied, and the size of fingerprint code becomes large. In this paper, we propose a hybrid modulation method, in which the merits of or-thogonal modulation and coded modulation method are combined so that we can achieve low computational cost and high signal efficiency. To analyze the performance, we design a new fingerprint code based on GD-PBIBD theory and modulate this code into images by our method using spread-spectrum watermarking on frequency domain. The results show that the proposed method can efficiently handle large fingerprint code and trace colluders against averaging attacks.
Abstract: Since 1992, year where Hugo de Garis has published
the first paper on Evolvable Hardware (EHW), a period of intense
creativity has followed. It has been actively researched, developed
and applied to various problems. Different approaches have been
proposed that created three main classifications: extrinsic, mixtrinsic
and intrinsic EHW. Each of these solutions has a real interest.
Nevertheless, although the extrinsic evolution generates some
excellent results, the intrinsic systems are not so advanced. This
paper suggests 3 possible solutions to implement the run-time
configuration intrinsic EHW system: FPGA-based Run-Time
Configuration system, JBits-based Run-Time Configuration system
and Multi-board functional-level Run-Time Configuration system.
The main characteristic of the proposed architectures is that they are
implemented on Field Programmable Gate Array. A comparison of
proposed solutions demonstrates that multi-board functional-level
run-time configuration is superior in terms of scalability, flexibility
and the implementation easiness.
Abstract: Multiplication algorithms have considerable effect on
processors performance. A new high-speed, low-power
multiplication algorithm has been presented using modified Dadda
tree structure. Three important modifications have been implemented
in inner product generation step, inner product reduction step and
final addition step. Optimized algorithms have to be used into basic
computation components, such as multiplication algorithms. In this
paper, we proposed a new algorithm to reduce power, delay, and
transistor count of a multiplication algorithm implemented using low
power modified counter. This work presents a novel design for
Dadda multiplication algorithms. The proposed multiplication
algorithm includes structured parts, which have important effect on
inner product reduction tree. In this paper, a 1.3V, 64-bit carry hybrid
adder is presented for fast, low voltage applications. The new 64-bit
adder uses a new circuit to implement the proposed carry hybrid
adder. The new adder using 80 nm CMOS technology has been
implemented on 700 MHz clock frequency. The proposed
multiplication algorithm has achieved 14 percent improvement in
transistor count, 13 percent reduction in delay and 12 percent
modification in power consumption in compared with conventional
designs.
Abstract: Virtual engineering technology has undergone rapid progress in recent years and is being adopted increasingly by manufacturing companies of many engineering disciplines. There is an increasing demand from industry for qualified virtual engineers. The qualified virtual engineers should have the ability of applying engineering principles and mechanical design methods within the commercial software package environment. It is a challenge to the engineering education in universities which traditionally tends to lack the integration of knowledge and skills required for solving real world problems. In this paper, a case study shows some recent development of a MSc Mechanical Engineering course at Department of Engineering and Technology in MMU, and in particular, two units Simulation of Mechanical Systems(SMS) and Computer Aided Fatigue Analysis(CAFA) that emphasize virtual engineering education and promote integration of knowledge acquisition, skill training and industrial application.
Abstract: In a bid to improve turbine entry temperature for maximizing the thermal efficiency of the HP stage gas turbine blade, an attempt is made in this paper to compare the performance of helicoidal ducted blade cooling with turbulator of different geometric proportion. It is found from analysis that there is significant improvement in cooling characteristics for turbine blade with turbulator geometry having larger e/D ratio. Also it is found from analysis, performance is vastly improved for greater thickness of turbulator geometry.
Abstract: In order to give high expertise the computer aided
design of mechanical systems involves specific activities focused on
processing two type of information: knowledge and data. Expert rule
based knowledge is generally processing qualitative information and
involves searching for proper solutions and their combination into
synthetic variant. Data processing is based on computational models
and it is supposed to be inter-related with reasoning in the knowledge
processing. In this paper an Intelligent Integrated System is proposed,
for the objective of choosing the adequate material. The software is
developed in Prolog – Flex software and takes into account various
constraints that appear in the accurate operation of gears.
Abstract: Ant colony optimization (ACO) and its variants are
applied extensively to resolve various continuous optimization
problems. As per the various diversification and intensification
schemes of ACO for continuous function optimization, researchers
generally consider components of multidimensional state space to
generate the new search point(s). However, diversifying to a new
search space by updating only components of the multidimensional
vector may not ensure that the new point is at a significant distance
from the current solution. If a minimum distance is not ensured
during diversification, then there is always a possibility that the
search will end up with reaching only local optimum. Therefore, to
overcome such situations, a Mahalanobis distance-based
diversification with Nelder-Mead simplex-based search scheme for
each ant is proposed for the ACO strategy. A comparative
computational run results, based on nine nonlinear standard test
problems, confirms that the performance of ACO is improved
significantly with the integration of the proposed schemes in the
ACO.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents and evolutionary
computation techniques in legacy e-learning environments. It
introduces the design and development of a scalable and
interoperable integration platform supporting:
I) various assessment agents for e-learning environments,
II) a specific resource retrieval agent for the provision of
additional information from Internet sources matching the
needs and profile of the specific user and
III) a genetic algorithm designed to extract efficient information
(classifying rules) based on the students- answering input
data.
The agents are implemented in order to provide intelligent
assessment services based on computational intelligence techniques
such as Bayesian Networks and Genetic Algorithms.
The proposed Genetic Algorithm (GA) is used in order to extract
efficient information (classifying rules) based on the students-
answering input data. The idea of using a GA in order to fulfil this
difficult task came from the fact that GAs have been widely used in
applications including classification of unknown data.
The utilization of new and emerging technologies like web
services allows integrating the provided services to any web based
legacy e-learning environment.