Abstract: This study explores perceptions of English as a Foreign
Language (EFL) learners on using computer mediated communication
technology in their learner of English. The data consists of
observations of both synchronous and asynchronous communication
participants engaged in for over a period of 4 months, which included
online, and offline communication protocols, open-ended interviews
and reflection papers composed by participants.
Content analysis of interview data and the written documents listed
above, as well as, member check and triangulation techniques are the
major data analysis strategies. The findings suggest that participants
generally do not benefit from computer-mediated communication in
terms of its effect in learning a foreign language. Participants regarded
the nature of CMC as artificial, or pseudo communication that did not
aid their authentic communicational skills in English. The results of
this study sheds lights on insufficient and inconclusive findings, which
most quantitative CMC studies previously generated.
Abstract: Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.
Abstract: Rapid growth of distance learning resulted in
importance to conduct research on students- satisfaction with distance
learning because differences in students- satisfaction might influence
educational opportunities for learning in a relevant Web-based
environment. In line with this, this paper deals with satisfaction of
students with distance module at Faculty of organizational sciences
(FOS) in Serbia as well as some factors affecting differences in their
satisfaction . We have conducted a research on a population of 68
first-year students of distance learning studies at FOS. Using
statistical techniques, we have found out that there is no significant
difference in students- satisfaction with distance learning module
between men and women. In the same way, we also concluded that
there is a difference in satisfaction with distance learning module
regarding to student-s perception of opportunity to gain knowledge as
the classic students.
Abstract: Implicit equations play a crucial role in Engineering.
Based on this importance, several techniques have been applied to
solve this particular class of equations. When it comes to practical
applications, in general, iterative procedures are taken into account.
On the other hand, with the improvement of computers, other
numerical methods have been developed to provide a more
straightforward methodology of solution. Analytical exact approaches
seem to have been continuously neglected due to the difficulty
inherent in their application; notwithstanding, they are indispensable
to validate numerical routines. Lagrange-s Inversion Theorem is a
simple mathematical tool which has proved to be widely applicable to
engineering problems. In short, it provides the solution to implicit
equations by means of an infinite series. To show the validity of this
method, the tree-parameter infiltration equation is, for the first time,
analytically and exactly solved. After manipulating these series,
closed-form solutions are presented as H-functions.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.
Abstract: In this document, we have proposed a robust
conceptual strategy, in order to improve the robustness against the manufacturing defects and thus the reliability of logic CMOS circuits. However, in order to enable the use of future CMOS
technology nodes this strategy combines various types of design:
DFR (Design for Reliability), techniques of tolerance: hardware
redundancy TMR (Triple Modular Redundancy) for hard error
tolerance, the DFT (Design for Testability. The Results on largest ISCAS and ITC benchmark circuits show that our approach improves
considerably the reliability, by reducing the key factors, the area costs and fault tolerance probability.
Abstract: Computer aided design accounts with the support of
parametric software in the design of machine components as well as
of any other pieces of interest. The complexities of the element under
study sometimes offer certain difficulties to computer design, or ever
might generate mistakes in the final body conception. Reverse
engineering techniques are based on the transformation of already
conceived body images into a matrix of points which can be
visualized by the design software. The literature exhibits several
techniques to obtain machine components dimensional fields, as
contact instrument (MMC), calipers and optical methods as laser
scanner, holograms as well as moiré methods. The objective of this
research work was to analyze the moiré technique as instrument of
reverse engineering, applied to bodies of nom complex geometry as
simple solid figures, creating matrices of points. These matrices were
forwarded to a parametric software named SolidWorks to generate
the virtual object. Volume data obtained by mechanical means, i.e.,
by caliper, the volume obtained through the moiré method and the
volume generated by the SolidWorks software were compared and
found to be in close agreement. This research work suggests the
application of phase shifting moiré methods as instrument of reverse
engineering, serving also to support farm machinery element designs.
Abstract: On-board Error Detection and Correction (EDAC)
devices aim to secure data transmitted between the central
processing unit (CPU) of a satellite onboard computer and its local
memory. This paper presents a comparison of the performance of
four low complexity EDAC techniques for application in Random
Access Memories (RAMs) on-board small satellites. The
performance of a newly proposed EDAC architecture is measured
and compared with three different EDAC strategies, using the same
FPGA technology. A statistical analysis of single-event upset (SEU)
and multiple-bit upset (MBU) activity in commercial memories
onboard Alsat-1 is given for a period of 8 years
Abstract: This research intends to introduce a new usage of Artificial Intelligent (AI) approaches in Stepping Stone Detection (SSD) fields of research. By using Self-Organizing Map (SOM) approaches as the engine, through the experiment, it is shown that SOM has the capability to detect the number of connection chains that involved in a stepping stones. Realizing that by counting the number of connection chain is one of the important steps of stepping stone detection and it become the research focus currently, this research has chosen SOM as the AI techniques because of its capabilities. Through the experiment, it is shown that SOM can detect the number of involved connection chains in Network-based Stepping Stone Detection (NSSD).
Abstract: Numerical analysis naturally finds applications in all
fields of engineering and the physical sciences, but in the
21st century, the life sciences and even the arts have adopted
elements of scientific computations. The numerical data analysis
became key process in research and development of all the fields [6].
In this paper we have made an attempt to analyze the specified
numerical patterns with reference to the association rule mining
techniques with minimum confidence and minimum support mining
criteria. The extracted rules and analyzed results are graphically
demonstrated. Association rules are a simple but very useful form of
data mining that describe the probabilistic co-occurrence of certain
events within a database [7]. They were originally designed to
analyze market-basket data, in which the likelihood of items being
purchased together within the same transactions are analyzed.
Abstract: In the recent years, high dynamic range imaging has
gain popularity with the advancement in digital photography. In this
contribution we present a subjective evaluation of various tone
production and tone mapping techniques by a number of participants.
Firstly, standard HDR images were used and the participants were
asked to rate them based on a given rating scheme. After that, the
participant was asked to rate HDR image generated using linear and
nonlinear combination approach of multiple exposure images. The
experimental results showed that linearly generated HDR images
have better visualization than the nonlinear combined ones. In
addition, Reinhard et al. and the exponential tone mapping operators
have shown better results compared to logarithmic and the Garrett et
al. tone mapping operators.
Abstract: Thirty six samples from each (aerobic and anoxic)
activated sludge were collected from two wastewater treatment plants
with MBRs in Berlin, Germany. The samples were prepared for count
and definition of fungal isolates; these isolates were purified by
conventional techniques and identified by microscopic examination.
Sixty tow species belonging to 28 genera were isolated from
activated sludge samples under aerobic conditions (28 genera and 58
species) and anoxic conditions (26 genera and 52 species). The
obtained data show that, Aspergillus was found at 94.4% followed by
Penicillium 61.1 %, Fusarium (61.1 %), Trichoderma (44.4 %) and
Geotrichum candidum (41.6 %) species were the most prevalent in all
activated sludge samples. The study confirmed that fungi can thrive
in activated sludge and sporulation, but isolated in different numbers
depending on the effect of aeration system. Some fungal species in
our study are saprophytic, and other a pathogenic to plants and
animals.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.
Abstract: In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: This paper presents Simulated Annealing based
approach to estimate solar cell model parameters. Single diode solar
cell model is used in this study to validate the proposed approach
outcomes. The developed technique is used to estimate different
model parameters such as generated photocurrent, saturation current,
series resistance, shunt resistance, and ideality factor that govern the
current-voltage relationship of a solar cell. A practical case study is
used to test and verify the consistency of accurately estimating
various parameters of single diode solar cell model. Comparative
study among different parameter estimation techniques is presented
to show the effectiveness of the developed approach.
Abstract: When designing satellites, one of the major issues aside for designing its primary subsystems is to devise its thermal. The thermal management of satellites requires solving different sets of issues with regards to modelling. If the satellite is well conditioned all other parts of the satellite will have higher temperature no matter what. The main issue of thermal modelling for satellite design is really making sure that all the other points of the satellite will be within the temperature limits they are designed. The insertion of power electronics in aerospace technologies is becoming widespread and the modern electronic systems used in space must be reliable and efficient with thermal management unaffected by outer space constraints. Many advanced thermal management techniques have been developed in recent years that have application in high power electronic systems. This paper presents a Three-Dimensional Modal Transmission Line Matrix (3D-TLM) implementation of transient heat flow in space power electronics. In such kind of components heat dissipation and good thermal management are essential. Simulation provides the cheapest tool to investigate all aspects of power handling. The 3DTLM has been successful in modeling heat diffusion problems and has proven to be efficient in terms of stability and complex geometry. The results show a three-dimensional visualisation of self-heating phenomena in the device affected by outer space constraints, and will presents possible approaches for increasing the heat dissipation capability of the power modules.
Abstract: One of the approaches enabling people with amputated
limbs to establish some sort of interface with the real world includes
the utilization of the myoelectric signal (MES) from the remaining
muscles of those limbs. The MES can be used as a control input to a
multifunction prosthetic device. In this control scheme, known as the
myoelectric control, a pattern recognition approach is usually utilized
to discriminate between the MES signals that belong to different
classes of the forearm movements. Since the MES is recorded using
multiple channels, the feature vector size can become very large. In
order to reduce the computational cost and enhance the generalization
capability of the classifier, a dimensionality reduction method is
needed to identify an informative yet moderate size feature set. This
paper proposes a new fuzzy version of the well known Fisher-s
Linear Discriminant Analysis (LDA) feature projection technique.
Furthermore, based on the fact that certain muscles might contribute
more to the discrimination process, a novel feature weighting scheme
is also presented by employing Particle Swarm Optimization (PSO)
for estimating the weight of each feature. The new method, called
PSOFLDA, is tested on real MES datasets and compared with other
techniques to prove its superiority.
Abstract: In this paper, the position control of an electronic
throttle actuator is outlined. The dynamic behavior of the actuator is
described with the help of an uncertain plant model. This motivates
the controller design based on the ideas of higher-order slidingmodes.
As a consequence anti-chattering techniques can be omitted.
It is shown that the same concept is applicable to estimate unmeasureable
signals. The control law and the observer are implemented on
an electronic control unit. Results achieved by numerical simulations
and real world experiments are presented and discussed.
Abstract: In this paper, we present a novel, principled approach to resolve the remained problems of substitution technique of audio steganography. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.