Abstract: This work is focused on the steady boundary layer flow
near the forward stagnation point of plane and axisymmetric bodies
towards a stretching sheet. The no slip condition on the solid
boundary is replaced by the partial slip condition. The analytical
solutions for the velocity distributions are obtained for the various
values of the ratio of free stream velocity and stretching velocity, slip
parameter, the suction and injection velocity parameter, magnetic
parameter and dimensionality index parameter in the series forms with
the help of homotopy analysis method (HAM). Convergence of the
series is explicitly discussed. Results show that the flow and the skin
friction coefficient depend heavily on the velocity slip factor. In
addition, the effects of all the parameters mentioned above were more
pronounced for plane flows than for axisymmetric flows.
Abstract: The reliability of the tools developed to learn the
learning styles is essential to find out students- learning styles
trustworthily. For this purpose, the psychometric features of Grasha-
Riechman Student Learning Style Inventory developed by Grasha
was studied to contribute to this field. The study was carried out on
6th, 7th, and 8th graders of 10 primary education schools in Konya.
The inventory was applied twice with an interval of one month, and
according to the data of this application, the reliability coefficient
numbers of the 6 sub-dimensions pointed in the theory of the
inventory was found to be medium. Besides, it was found that the
inventory does not have a structure with 6 factors for both
Mathematics and English courses as represented in the theory.
Abstract: End milling process is one of the common metal
cutting operations used for machining parts in manufacturing
industry. It is usually performed at the final stage in manufacturing a
product and surface roughness of the produced job plays an
important role. In general, the surface roughness affects wear
resistance, ductility, tensile, fatigue strength, etc., for machined parts
and cannot be neglected in design. In the present work an
experimental investigation of end milling of aluminium alloy with
carbide tool is carried out and the effect of different cutting
parameters on the response are studied with three-dimensional
surface plots. An artificial neural network (ANN) is used to establish
the relationship between the surface roughness and the input cutting
parameters (i.e., spindle speed, feed, and depth of cut). The Matlab
ANN toolbox works on feed forward back propagation algorithm is
used for modeling purpose. 3-12-1 network structure having
minimum average prediction error found as best network architecture
for predicting surface roughness value. The network predicts surface
roughness for unseen data and found that the result/prediction is
better. For desired surface finish of the component to be produced
there are many different combination of cutting parameters are
available. The optimum cutting parameter for obtaining desired
surface finish, to maximize tool life is predicted. The methodology is
demonstrated, number of problems are solved and algorithm is coded
in Matlab®.
Abstract: There is no doubt that Internet technology is widely used by hotels and its demand is constantly booming. Hotels have largely adopted website information services through using different interactive tools, dimensions and attributes to achieve excellence in functionality and usability but these do not necessary equate with website effectiveness. One way to investigate the effectiveness of hotel website is from the perspective ofe-consumers. This exploratory research is to investigate the perceived importance of websites effectiveness of some selected independent small and medium-sized hotels (SMHs) located in Dubai, United Arab Emirates, from the perspective of Omanie-consumers by using non-random sampling method. From 400 questionnaire addressed to respondents in 27 organizations in Muscat the capital city of Oman, 173 are valid. Findings of this study assist SMHs management in Dubai with the reallocation of their resources and efforts in order to supportebusiness development and to sustain a competitive advantage.
Abstract: This paper presents an optimization of the hull
separation, i.e. transverse clearance. The main objective is to identify
the feasible speed ranges and find the optimum transverse clearance
considering the minimum wave-making resistance. The dimensions
and the weight of hardware systems installed in the catamaran
structured fuel cell powered USV (Unmanned Surface Vehicle) were
considered as constraints. As the CAE (Computer Aided Engineering)
platform FRIENDSHIP-Framework was used. The hull surface
modeling, DoE (Design of Experiment), Tangent search optimization,
tool integration and the process automation were performed by
FRIENDSHIP-Framework. The hydrodynamic result was evaluated
by XPAN the potential solver of SHIPFLOW.
Abstract: Network on Chip (NoC) has emerged as a promising
on chip communication infrastructure. Three Dimensional Integrate
Circuit (3D IC) provides small interconnection length between layers
and the interconnect scalability in the third dimension, which can
further improve the performance of NoC. Therefore, in this paper,
a hierarchical cluster-based interconnect architecture is merged with
the 3D IC. This interconnect architecture significantly reduces the
number of long wires. Since this architecture only has approximately
a quarter of routers in 3D mesh-based architecture, the average
number of hops is smaller, which leads to lower latency and higher
throughput. Moreover, smaller number of routers decreases the area
overhead. Meanwhile, some dual links are inserted into the bottlenecks
of communication to improve the performance of NoC.
Simulation results demonstrate our theoretical analysis and show the
advantages of our proposed architecture in latency, throughput and
area, when compared with 3D mesh-based architecture.
Abstract: In a complex project environment, project teams face
multi-dimensional communication problems that can ultimately lead
to project breakdown. Team Performance varies in Face-to-Face
(FTF) environment versus groups working remotely in a computermediated
communication (CMC) environment. A brief review of the
Input_Process_Output model suggested by James E. Driskell, Paul H.
Radtke and Eduardo Salas in “Virtual Teams: Effects of
Technological Mediation on Team Performance (2003)", has been
done to develop the basis of this research. This model theoretically
analyzes the effects of technological mediation on team processes,
such as, cohesiveness, status and authority relations, counternormative
behavior and communication. An empirical study
described in this paper has been undertaken to test the
“cohesiveness" of diverse project teams in a multi-national
organization. This study uses both quantitative and qualitative
techniques for data gathering and analysis. These techniques include
interviews, questionnaires for data collection and graphical data
representation for analyzing the collected data. Computer-mediated
technology may impact team performance because of difference in
cohesiveness among teams and this difference may be moderated by
factors, such as, the type of communication environment, the type of
task and the temporal context of the team. Based on the reviewed
model, sets of hypotheses are devised and tested. This research,
reports on a study that compared team cohesiveness among virtual
teams using CMC and non-CMC communication mediums. The
findings suggest that CMC can help virtual teams increase team
cohesiveness among their members, making CMC an effective
medium for increasing productivity and team performance.
Abstract: New design of a grid for preparation of high density
granules with enhanced mechanical strength by granulation of
dispersed materials is suggested.
A method for hydrodynamic dimensioning of the grid depending
on granulation conditions, hydrodynamic regime of the operation,
dispersity and physicochemical characteristics of the materials to be
granulated was suggested.
The aim of the grid design is to solve the problems arising by the
granulation of disperse materials.
Abstract: The present study is concerned with effect of exciting
boundary layer on increase in heat transfer from flat surfaces. As any
increase in heat transfer between a fluid inside a face and another one
outside of it can cause an increase in some equipment's efficiency, so
at this present we have tried to increase the wall's heat transfer
coefficient by exciting the fluid boundary layer. By a collision
between flow and the placed block at the fluid way, the flow pattern
and the boundary layer stability will change. The flow way inside the
channel is simulated as a 2&3-dimensional channel by Gambit
TM
software.
With studying the achieved results by this simulation for the flow
way inside the channel with a block coordinating with Fluent
TM
software, it's determined that the figure and dimensions of the exciter
are too important for exciting the boundary layer so that any increase
in block dimensions in vertical side against the flow and any
reduction in its dimensions at the flow side can increase the average
heat transfer coefficient from flat surface and increase the flow
pressure loss. Using 2&3-dimensional analysis on exciting the flow at
the flow way inside a channel by cylindrical block at the same time
with the external flow, we came to this conclusion that the heat flux
transferred from the surface, is increased considerably in terms of the
condition without excitation. Also, the k-e turbulence model is used.
Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: In a previous work, we presented the numerical
solution of the two dimensional second order telegraph partial
differential equation discretized by the centred and rotated five-point
finite difference discretizations, namely the explicit group (EG) and
explicit decoupled group (EDG) iterative methods, respectively. In
this paper, we utilize a domain decomposition algorithm on these
group schemes to divide the tasks involved in solving the same
equation. The objective of this study is to describe the development
of the parallel group iterative schemes under OpenMP programming
environment as a way to reduce the computational costs of the
solution processes using multicore technologies. A detailed
performance analysis of the parallel implementations of points and
group iterative schemes will be reported and discussed.
Abstract: This paper presents an approach based on the
adoption of a distributed cognition framework and a non parametric
multicriteria evaluation methodology (DEA) designed specifically to
compare e-commerce websites from the consumer/user viewpoint. In
particular, the framework considers a website relative efficiency as a
measure of its quality and usability. A website is modelled as a black
box capable to provide the consumer/user with a set of
functionalities. When the consumer/user interacts with the website to
perform a task, he/she is involved in a cognitive activity, sustaining a
cognitive cost to search, interpret and process information, and
experiencing a sense of satisfaction. The degree of ambiguity and
uncertainty he/she perceives and the needed search time determine
the effort size – and, henceforth, the cognitive cost amount – he/she
has to sustain to perform his/her task. On the contrary, task
performing and result achievement induce a sense of gratification,
satisfaction and usefulness. In total, 9 variables are measured,
classified in a set of 3 website macro-dimensions (user experience,
site navigability and structure). The framework is implemented to
compare 40 websites of businesses performing electronic commerce
in the information technology market. A questionnaire to collect
subjective judgements for the websites in the sample was purposely
designed and administered to 85 university students enrolled in
computer science and information systems engineering
undergraduate courses.
Abstract: This paper presents a hybrid approach for solving nqueen problem by combination of PSO and SA. PSO is a population based heuristic method that sometimes traps in local maximum. To solve this problem we can use SA. Although SA suffer from many iterations and long time convergence for solving some problems, By good adjusting initial parameters such as temperature and the length of temperature stages SA guarantees convergence. In this article we use discrete PSO (due to nature of n-queen problem) to achieve a good local maximum. Then we use SA to escape from local maximum. The experimental results show that our hybrid method in comparison of SA method converges to result faster, especially for high dimensions n-queen problems.
Abstract: Incompressible Navier-Stokes equations are reviewed
in this work. Three-dimensional Navier-Stokes equations are solved
analytically. The Mathematical derivation shows that the solutions
for the zero and constant pressure gradients are similar. Descriptions
of the proposed formulation and validation against two laminar
experiments and three different turbulent flow cases are reported in
this paper. Even though, the analytical solution is derived for nonreacting
flows, it could reproduce trends for cases including
combustion.
Abstract: In this paper we consider a one-dimensional random
geometric graph process with the inter-nodal gaps evolving according
to an exponential AR(1) process. The transition probability matrix
and stationary distribution are derived for the Markov chains concerning
connectivity and the number of components. We analyze the
algorithm for hitting time regarding disconnectivity. In addition to
dynamical properties, we also study topological properties for static
snapshots. We obtain the degree distributions as well as asymptotic
precise bounds and strong law of large numbers for connectivity
threshold distance and the largest nearest neighbor distance amongst
others. Both exact results and limit theorems are provided in this
paper.
Abstract: The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.
Abstract: This paper seeks to explore the actual classroom
setting, to examine its role for students- learning, and attitude in the
class. It presents a theoretical approach of the classroom as system to
be explored and examines the concrete reality of Greek secondary
education students, under the light of the above approach. Based on
the findings of a quantitative and qualitative research, authors
propose a rather ontological approach of the classroom and underline
what the key-elements for such approach should be. The paper
explores extensively the theoretical dimensions for the change of
paradigm required and addresses the new issues to be considered.
Abstract: In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression[6]. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory [7]. Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area[1].
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.