Abstract: Asynchronous Transfer Mode (ATM) is widely used
in telecommunications systems to send data, video and voice at a
very high speed. In ATM network optimizing the bandwidth through
dynamic routing is an important consideration. Previous research
work shows that traditional optimization heuristics result in suboptimal
solution. In this paper we have explored non-traditional
optimization technique. We propose comparison of two such
algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on
non-traditional Optimization approach, for solving the dynamic
routing problem in ATM networks which in return will optimize the
bandwidth. The optimized bandwidth could mean that some
attractive business applications would become feasible such as high
speed LAN interconnection, teleconferencing etc. We have also
performed a comparative study of the selection mechanisms in GA
and listed the best selection mechanism and a new initialization
technique which improves the efficiency of the GA.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
Abstract: The increasing divorce and fertility rates outside of marriage, the changing values in the last decades have led to a high prevalence of single parent families. Currently, worldwide, singleparent families represent about a quarter of all families. Recent changes occurring in the structure of single-parent families and also the multitude of factors that influence the quality of life of these families require the development of new research tools in order to provide foundations for social policies addressed to this type of family. The purpose of this paper is to present an analysis concerning the quality of life for single parent families in Romania, based on data collected through a research methodology developed by the authors within a scientific research project funded by a national grant called Partnerships in priority areas.
Abstract: The scroll pump belongs to the category of positive
displacement pump can be used for continuous pumping of gases at
low pressure apart from general vacuum application. The shape of
volume occupied by the gas moves and deforms continuously as the
spiral orbits. To capture flow features in such domain where mesh
deformation varies with time in a complicated manner, mesh less
solver was found to be very useful. Least Squares Kinetic Upwind
Method (LSKUM) is a kinetic theory based mesh free Euler solver
working on arbitrary distribution of points. Here upwind is enforced
in molecular level based on kinetic flux vector splitting scheme
(KFVS). In the present study we extended the LSKUM to moving
node viscous flow application. This new code LSKUM-NS-MN for
moving node viscous flow is validated for standard airfoil pitching
test case. Simulation performed for flow through scroll pump using
LSKUM-NS-MN code agrees well with the experimental pumping
speed data.
Abstract: For today-s and future wireless communications applications,
more and more data traffic has to be transmitted with
growing speed and quality demands. The analog front-end of any
mobile device has to cope with very hard specifications regardless
which transmission standard has to be supported. State-of-the-art
analog front-end implementations are reaching the limit of technical
feasibility. For that reason, alternative front-end architectures could
support a continuing development of mobile communications e.g.,
six-port-based front-ends [1], [2].
In this article we propose an analog front-end with high intermediate
frequency and which utilizes additive mixing instead
of multiplicative mixing. The system architecture is presented and
several spurious effects as well as their influence on the system
dimensioning are discussed. Furthermore, several issues concerning
the technical feasibility are provided and some simulation results
are discussed which show the principle functionality of the proposed
superposition heterodyne receiver.
Abstract: In this paper, we propose disease diagnosis hardware
architecture by using Hypernetworks technique. It can be used to
diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate
cancer). Generally, the disparate diseases require specified diagnosis
hardware model for each disease. Using similarities of three diseases
diagnosis processor, we design diagnosis processor that can diagnose
three different diseases. Our proposed architecture that is combining
three processors to one processor can reduce hardware size without
decrease of the accuracy.
Abstract: This survey highlights a number of important issues
which relate to the needs to counseling for distance learners studying
at the School of Distance Education in University science Malaysia
(DEUSM) according to their gender. Data were obtained by selfreport
questionnaire that had been developed by the researchers in
counseling and educational psychology and interviews were take
place. 116 voluntary respondents complete the Questionnaire and
returned it back during new student-s registration week.64% of the
respondents were female and 52% were males that means
55%ofthem were females and 45% were males. The data was
analyzed to find out the frequencies of respondents agreements of the
items. The average of the female was 18 and the average of the male
was 19.6 by using t- test there is no significant values between the
genders. The findings show that respondents have needs for
counseling. (22) Significant needs for mails (DEUSM) the highest
was their families complain about the amount of time they spend at
work. (11) Significant needs for females the highest was they
convinced themselves that they only need 4 to 5 hours of sleep per
night.
Abstract: Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.
Abstract: Competing risks survival data that comprises of more
than one type of event has been used in many applications, and one
of these is in clinical study (e.g. in breast cancer study). The
decision tree method can be extended to competing risks survival
data by modifying the split function so as to accommodate two or
more risks which might be dependent on each other. Recently,
researchers have constructed some decision trees for recurrent
survival time data using frailty and marginal modelling. We further
extended the method for the case of competing risks. In this paper,
we developed the decision tree method for competing risks survival
time data based on proportional hazards for subdistribution of
competing risks. In particular, we grow a tree by using deviance
statistic. The application of breast cancer data is presented. Finally,
to investigate the performance of the proposed method, simulation
studies on identification of true group of observations were executed.
Abstract: The river flow forecasting represents a crucial point to employ for improving a management policy addressed to the right use of water resources as well as for conjugating prevention and defense actions against environmental degradation. The difficulties occurring during the field activities encourage the development and implementation of operative computation and measuring methods addressed to time reduction for data acquisition and processing maintaining a good level of accuracy. Therefore, the aim of the present work is to test a new entropy based expeditive methodology for the evaluation of the rating curves on three gauged sections with different geometric and morphological characteristics. The methodology requires the choice of only three verticals along the measure section and the sampling of only the maximum velocity. The results underline how in most conditions the rating curves drawn can replace those built with classic methodologies, simplifying thus the procedures of data monitoring and calculation.
Abstract: In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: The actual grow of the infrastructure in develop country require sophisticate ways manage the operation and control the quality served. This research wants to concentrate in the operation of this infrastructure beyond the construction. The infrastructure-s operation involves an uncertain environment, where unexpected variables are present every day and everywhere. Decision makers need to make right decisions with right information/data analyzed most in real time. To adequately support their decisions and decrease any negative impact and collateral effect, they need to use computational tools called decision support systems (DSS), but now the main source of information came from common users thought an extensive crowdsourcing
Abstract: In this paper a special kind of buffer management policy is studied where the packet are preempted even when sufficient space is available in the buffer for incoming packets. This is done to congestion for future incoming packets to improve QoS for certain type of packets. This type of study has been done in past for ATM type of scenario. We extend the same for heterogeneous traffic where data rate and size of the packets are very versatile in nature. Typical example of this scenario is the buffer management in Differentiated Service Router. There are two aspects that are of interest. First is the packet size: whether all packets have same or different sizes. Second aspect is the value or space priority of the packets, do all packets have the same space priority or different packets have different space priorities. We present two types of policies to achieve QoS goals for packets with different priorities: the push out scheme and the expelling scheme. For this work the scenario of packets of variable length is considered with two space priorities and main goal is to minimize the total weighted packet loss. Simulation and analytical studies show that, expelling policies can outperform the push out policies when it comes to offering variable QoS for packets of two different priorities and expelling policies also help improve the amount of admissible load. Some other comparisons of push out and expelling policies are also presented using simulations.
Abstract: Point quad tree is considered as one of the most
common data organizations to deal with spatial data & can be used to
increase the efficiency for searching the point features. As the
efficiency of the searching technique depends on the height of the
tree, arbitrary insertion of the point features may make the tree
unbalanced and lead to higher time of searching. This paper attempts
to design an algorithm to make a nearly balanced quad tree. Point
pattern analysis technique has been applied for this purpose which
shows a significant enhancement of the performance and the results
are also included in the paper for the sake of completeness.
Abstract: A lightpipe is an about 99 percent specular reflective
mirror pipe or duct that is used for the transmission of the daylight
from the outside into a building. The lightpipes are usually used in
the daylighting buildings, in the residential, industrial and
commercial sectors. This paper is about the performances of a
lightpipe installed in a laboratory (3 m x 2.6 m x 3 m) without
windows. The aim is to analyse the luminous intensity distribution
for several sky/sun conditions. The lightpipe was monitored during
the year 2006. The lightpipe is 1 m long and the diameter of the top
collector and of the internal diffuser device is 0.25 m. In the
laboratory there are seven illuminance sensors: one external is
located on the roof of the laboratory and six internal sensors are
connected to a data acquisition system. The internal sensors are
positioned under the internal diffusive device at an height of 0.85 m
from the floor to simulate a working plane. The numerical data are
obtained through a simulation software. This paper shows the
comparison between the experimental and numerical results
concerning the behavior of the lightpipe.
Abstract: Fuzzy Cognitive Maps (FCMs) have successfully
been applied in numerous domains to show relations between
essential components. In some FCM, there are more nodes, which
related to each other and more nodes means more complex in system
behaviors and analysis. In this paper, a novel learning method used to
construct FCMs based on historical data and by using data mining
and DEMATEL method, a new method defined to reduce nodes
number. This method cluster nodes in FCM based on their cause and
effect behaviors.
Abstract: This paper presents unified theory for local (Savitzky-
Golay) and global polynomial smoothing. The algebraic framework
can represent any polynomial approximation and is seamless from
low degree local, to high degree global approximations. The representation
of the smoothing operator as a projection onto orthonormal
basis functions enables the computation of: the covariance matrix
for noise propagation through the filter; the noise gain and; the
frequency response of the polynomial filters. A virtually perfect Gram
polynomial basis is synthesized, whereby polynomials of degree
d = 1000 can be synthesized without significant errors. The perfect
basis ensures that the filters are strictly polynomial preserving. Given
n points and a support length ls = 2m + 1 then the smoothing
operator is strictly linear phase for the points xi, i = m+1. . . n-m.
The method is demonstrated on geometric surfaces data lying on an
invariant 2D lattice.
Abstract: Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.
Abstract: In this paper, FinFET devices are analyzed with
emphasis on sub-threshold leakage current control. This is achieved
through proper biasing of the back gate, and through the use of
asymmetric work functions for the four terminal FinFET devices. We
are also examining different configurations of multiplexers and XOR
gates using transistors of symmetric and asymmetric work functions.
Based on extensive characterization data for MUX circuits, our
proposed configuration using symmetric devices lead to leakage
current and delay improvements of 65% and 47% respectively
compared to results in the literature. For XOR gates, a 90%
improvement in the average leakage current is achieved by using
asymmetric devices. All simulations are based on a 25nm FinFET
technology using the University of Florida UFDG model.