Abstract: Optimum communication and performance in
Wireless Sensor Networks, constitute multi-facet challenges due to
the specific networking characteristics as well as the scarce resource
availability. Furthermore, it is becoming increasingly apparent that
isolated layer based approaches often do not meet the demands posed
by WSNs applications due to omission of critical inter-layer
interactions and dependencies. As a counterpart, cross-layer is
receiving high interest aiming to exploit these interactions and
increase network performance. However, in order to clearly identify
existing dependencies, comprehensive performance studies are
required evaluating the effect of different critical network parameters
on system level performance and behavior.This paper-s main
objective is to address the need for multi-parametric performance
evaluations considering critical network parameters using a well
known network simulator, offering useful and practical conclusions
and guidelines. The results reveal strong dependencies among
considered parameters which can be utilized by and drive future
research efforts, towards designing and implementing highly efficient
protocols and architectures.
Abstract: Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.
Abstract: Ranking of fuzzy numbers play an important role in
decision making, optimization, forecasting etc. Fuzzy numbers must
be ranked before an action is taken by a decision maker. In this
paper, with the help of several counter examples it is proved that
ranking method proposed by Chen and Chen (Expert Systems with
Applications 36 (2009) 6833-6842) is incorrect. The main aim of this
paper is to propose a new approach for the ranking of generalized
trapezoidal fuzzy numbers. The main advantage of the proposed
approach is that the proposed approach provide the correct ordering
of generalized and normal trapezoidal fuzzy numbers and also the
proposed approach is very simple and easy to apply in the real life
problems. It is shown that proposed ranking function satisfies all
the reasonable properties of fuzzy quantities proposed by Wang and
Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).
Abstract: In this paper, solution of fuzzy differential equation
under general differentiability is obtained by simulink. The simulink
solution is equivalent or very close to the exact solution of the
problem. Accuracy of the simulink solution to this problem is
qualitatively better. An illustrative numerical example is presented
for the proposed method.
Abstract: This paper addresses the problem of asymptotic tracking
control of a linear parabolic partial differential equation with indomain
point actuation. As the considered model is a non-standard
partial differential equation, we firstly developed a map that allows
transforming this problem into a standard boundary control problem
to which existing infinite-dimensional system control methods can
be applied. Then, a combination of energy multiplier and differential
flatness methods is used to design an asymptotic tracking controller.
This control scheme consists of stabilizing state-feedback derived
from the energy multiplier method and feed-forward control based
on the flatness property of the system. This approach represents
a systematic procedure to design tracking control laws for a class
of partial differential equations with in-domain point actuation. The
applicability and system performance are assessed by simulation
studies.
Abstract: Using a set of confidence intervals, we develop a
common approach, to construct a fuzzy set as an estimator for
unknown parameters in statistical models. We investigate a method
to derive the explicit and unique membership function of such fuzzy
estimators. The proposed method has been used to derive the fuzzy
estimators of the parameters of a Normal distribution and some
functions of parameters of two Normal distributions, as well as the
parameters of the Exponential and Poisson distributions.
Abstract: In sport, human resources management gives special
attention to method of applying volunteers, their maintenance, and
participation of volunteers with each other and management
approaches for better operation of events celebrants. The recognition
of volunteers- characteristics and motives is important to notice,
because it makes the basis of their participation and commitment at
sport environment. The motivation and commitment of 281
volunteers were assessed using the organizational commitment scale,
motivation scale and personal characteristics questionnaire.The
descriptive results showed that; 64% of volunteers were women with
age average 21/24 years old. They were physical education student,
single (71/9%), without occupation (53%) and with average of 5
years sport experience. Their most important motivation was career
factor and the most important commitment factor was normative
factor. The results of examining the hypothesized showed that; age,
sport experience and education are effective in the amount of
volunteers- commitment. And the motive factors such as career,
material, purposive and protective factors also have the power to
predict the amount of sports volunteers- commitment value.
Therefore it is recommended to provide possible opportunities for
volunteers and carrying out appropriate instructional courses by
events executive managers.
Abstract: The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Abstract: Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.
Abstract: This paper introduces a new instantaneous frequency
computation approach -Counting Instantaneous Frequency for a
general class of signals called simple waves. The classsimple wave
contains a wide range of continuous signals for which the concept
instantaneous frequency has a perfect physical sense. The concept of
-Counting Instantaneous Frequency also applies to all the discrete data.
For all the simple wave signals and the discrete data, -Counting
instantaneous frequency can be computed directly without signal
decomposition process. The intrinsic mode functions obtained through
empirical mode decomposition belongs to simple wave. So
-Counting instantaneous frequency can be used together with
empirical mode decomposition.
Abstract: The indoor airflow with a mixed natural/forced convection
was numerically calculated using the laminar and turbulent
approach. The Boussinesq approximation was considered for a simplification
of the mathematical model and calculations. The results
obtained, such as mean velocity fields, were successfully compared
with experimental PIV flow visualizations. The effect of the distance
between the cooled wall and the heat exchanger on the temperature
and velocity distributions was calculated. In a room with a simple
shape, the computational code OpenFOAM demonstrated an ability to
numerically predict flow patterns. Furthermore, numerical techniques,
boundary type conditions and the computational grid quality were
examined. Calculations using the turbulence model k-omega had a
significant effect on the results influencing temperature and velocity
distributions.
Abstract: This paper presents a simple approach for load
flow analysis of a radial distribution network. The proposed
approach utilizes forward and backward sweep algorithm
based on Kirchoff-s current law (KCL) and Kirchoff-s voltage
law (KVL) for evaluating the node voltages iteratively. In this
approach, computation of branch current depends only on the
current injected at the neighbouring node and the current in
the adjacent branch. This approach starts from the end nodes
of sub lateral line, lateral line and main line and moves
towards the root node during branch current computation. The
node voltage evaluation begins from the root node and moves
towards the nodes located at the far end of the main, lateral
and sub lateral lines. The proposed approach has been tested
using four radial distribution systems of different size and
configuration and found to be computationally efficient.
Abstract: An effective approach for unbalanced three-phase
distribution power flow solutions is proposed in this paper. The
special topological characteristics of distribution networks have been
fully utilized to make the direct solution possible. Two matrices–the
bus-injection to branch-current matrix and the branch-current to busvoltage
matrix– and a simple matrix multiplication are used to
obtain power flow solutions. Due to the distinctive solution
techniques of the proposed method, the time-consuming LU
decomposition and forward/backward substitution of the Jacobian
matrix or admittance matrix required in the traditional power flow
methods are no longer necessary. Therefore, the proposed method is
robust and time-efficient. Test results demonstrate the validity of the
proposed method. The proposed method shows great potential to be
used in distribution automation applications.
Abstract: A feature weighting and selection method is proposed
which uses the structure of a weightless neuron and exploits the
principles that govern the operation of Genetic Algorithms and
Evolution. Features are coded onto chromosomes in a novel way
which allows weighting information regarding the features to be
directly inferred from the gene values. The proposed method is
significant in that it addresses several problems concerned with
algorithms for feature selection and weighting as well as providing
significant advantages such as speed, simplicity and suitability for
real-time systems.
Abstract: In the globalized e-learning environment, students coming from different cultures and countries have different characteristics and require different support designed for their approaches to study and learning styles. This paper explores the ways in which cultural background influences students- approaches to study and learning styles. Participants in the study consisted of 131 eastern students and 54 western students from an Australian university. The students were tested using the Study Process Questionnaire (SPQ) for assessing their approaches to study and the Index of Learning Styles Questionnaire (ILS) for assessing their learning styles. The results of the study led to a set of principles being proposed to guide personalization of e-learning system design on the basis of cultural differences.
Abstract: One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.
Abstract: Association rules are an important problem in data
mining. Massively increasing volume of data in real life databases
has motivated researchers to design novel and incremental algorithms
for association rules mining. In this paper, we propose an incremental
association rules mining algorithm that integrates shocking
interestingness criterion during the process of building the model. A
new interesting measure called shocking measure is introduced. One
of the main features of the proposed approach is to capture the user
background knowledge, which is monotonically augmented. The
incremental model that reflects the changing data and the user beliefs
is attractive in order to make the over all KDD process more
effective and efficient. We implemented the proposed approach and
experiment it with some public datasets and found the results quite
promising.
Abstract: Mitochondria are dynamic organelles, capable to
interact with each other. While the number of mitochondria in a cell
varies, their quality and functionality depends on the operation of
fusion, fission, motility and mitophagy. Nowadays, several
researches declare as an important factor in neurogenerative diseases
the disruptions in the regulation of mitochondrial dynamics. In this
paper a stochastic model in BioAmbients calculus is presented,
concerning mitochondrial fusion and its distribution in the renewal of
mitochondrial population in a cell. This model describes the
successive and dependent stages of protein synthesis, protein-s
activation and merging of two independent mitochondria.
Abstract: Vitamin A deficiency is a public health problem in
Zimbabwe. Addressing vitamin A deficiency has the potential of
enhancing resistance to disease and reducing mortality especially in
children less than 5 years. We implemented and adapted vitamin A
outreach supplementation strategy within the National Immunization
Days and Extended Programme of Immunization in a rural district in
Zimbabwe. Despite usual operational challenges faced this approach
enabled the district to increase delivery of supplementation coverage.
This paper describes the outreach strategy that was implemented in
the remote rural district. The strategy covered 63 outreach sites with
2 sites being covered per day and visited once per month for the
whole year. Coverage reached 71% in an area of previous coverage
rates of around less than 50%. We recommend further exploration of
this strategy by others working in similar circumstances. This
strategy can be a potential way for use by Scaling-Up-Nutrition
member states.
Abstract: This paper presents an evaluation for a wavelet-based
digital watermarking technique used in estimating the quality of
video sequences transmitted over Additive White Gaussian Noise
(AWGN) channel in terms of a classical objective metric, such as
Peak Signal-to-Noise Ratio (PSNR) without the need of the original
video. In this method, a watermark is embedded into the Discrete
Wavelet Transform (DWT) domain of the original video frames
using a quantization method. The degradation of the extracted
watermark can be used to estimate the video quality in terms of
PSNR with good accuracy. We calculated PSNR for video frames
contaminated with AWGN and compared the values with those
estimated using the Watermarking-DWT based approach. It is found
that the calculated and estimated quality measures of the video
frames are highly correlated, suggesting that this method can provide
a good quality measure for video frames transmitted over AWGN
channel without the need of the original video.