Abstract: The design of technological procedures for
manufacturing certain products demands the definition and
optimization of technological process parameters. Their
determination depends on the model of the process itself and its
complexity. Certain processes do not have an adequate mathematical
model, thus they are modeled using heuristic methods. First part of
this paper presents a state of the art of using soft computing
techniques in manufacturing processes from the perspective of
applicability in modern CAx systems. Methods of artificial
intelligence which can be used for this purpose are analyzed. The
second part of this paper shows some of the developed models of
certain processes, as well as their applicability in the actual
calculation of parameters of some technological processes within the
design system from the viewpoint of productivity.
Abstract: Raman spectroscopy are used to characterize the
chemical changes in normoxic polyhydroxyethylacrylate gel
dosimeter (PHEA) induced by radiation. Irradiations in the low dose
region are performed and the polymerizations of PHEA gels are
monitored by the observing the changes of Raman shift intensity of
the carbon covalent bond of PHEA originated from both monomer
and the cross-linker. The variation in peak intensities with absorbed
dose was observed. As the dose increase, the peak intensities of
covalent bond of carbon in the polymer gels decrease. This point out
that the amount of absorbed dose affect the polymerization of
polymer gels. As the absorbed dose increase, the polymerizations
also increase. Results verify that PHEA gel dosimeters are sensitive
even in lower dose region.
Abstract: The proposed multiplexer-based novel 1-bit full
adder cell is schematized by using DSCH2 and its layout is generated
by using microwind VLSI CAD tool. The adder cell layout
interconnect analysis is performed by using BSIM4 layout analyzer.
The adder circuit is compared with other six existing adder circuits
for parametric analysis. The proposed adder cell gives better
performance than the other existing six adder circuits in terms of
power, propagation delay and PDP. The proposed adder circuit is
further analyzed for interconnect analysis, which gives better
performance than other adder circuits in terms of layout thickness,
width and height.
Abstract: In this paper, an efficient local appearance feature
extraction method based the multi-resolution Curvelet transform is
proposed in order to further enhance the performance of the well
known Linear Discriminant Analysis(LDA) method when applied
to face recognition. Each face is described by a subset of band
filtered images containing block-based Curvelet coefficients. These
coefficients characterize the face texture and a set of simple statistical
measures allows us to form compact and meaningful feature vectors.
The proposed method is compared with some related feature extraction
methods such as Principal component analysis (PCA), as well
as Linear Discriminant Analysis LDA, and independent component
Analysis (ICA). Two different muti-resolution transforms, Wavelet
(DWT) and Contourlet, were also compared against the Block Based
Curvelet-LDA algorithm. Experimental results on ORL, YALE and
FERET face databases convince us that the proposed method provides
a better representation of the class information and obtains much
higher recognition accuracies.
Abstract: In synchronized games players make their moves simultaneously
rather than alternately. Synchronized Triomineering
and Synchronized Tridomineering are respectively the synchronized
versions of Triomineering and Tridomineering, two variants of a
classic two-player combinatorial game called Domineering. Experimental
results for small m × n boards (with m + n ≤ 12 for
Synchronized Triomineering and m + n ≤ 10 for Synchronized
Tridomineering) and some theoretical results for general k×n boards
(with k = 3, 4, 5 for Synchronized Triomineering and k = 3
for Synchronized Tridomineering) are presented. Future research is
indicated.
Abstract: Abstract–The objectives of the current study are to determine the
prevalence, etiological agents, drug susceptibility pattern and plasmid
profile of Acinetobacter baumannii isolates from Hospital-Acquired
Infections (HAI) at Community Hospital, Al Jouf Province, Saudi
Arabia. A total of 1890 patients had developed infection during
hospital admission and were included in the study. Among those who
developed nosocomial infections, 15(9.4), 10(2.7) and 118 (12.7) had
respiratory tract infection (RTI), blood stream infections (BSI) and
urinary tract (UTI) respectively. A total of 268 bacterial isolates were
isolated from nosocomial infection. S. aureus was reported in 23.5%
for of the total isolates followed by Klebsiella pneumoniae (17.5%), E.
coli (17.2%), P. aeruginosa (11.9%), coagulase negative
staphylococcus (9%), A. baumannii (7.1%), Enterobacter spp.
(3.4%), Citrobacter freundii (3%), Proteus mirabilis (2.6%), and
Proteus vulgaris and Enterococcous faecalis (0.7%). Isolated
organisms are multi-drug resistant, predominantly Gram-positive
pathogens with a high incidence of methicillin-resistant S. aureus,
extended spectrum beta lactamase and vancomycin resistant
enterococci organisms. The RFLP (Fragment Length Polymorphisms)
patterns of plasmid preparations from isolated A. baumannii isolates
had altered RFLP patterns, possibly due to the presence of plasmid(s).
Five A. baumannii isolates harbored plasmids all of which were not
less than 2.71kbp in molecular weight. Hence, it showed that the gene
coding for the isolates were located on the plasmid DNA while the
remaining isolates which have no plasmid might showed gene coding
for antibiotic resistance being located on chromosomal DNA.
Nosocomial infections represent a current problem in Community
Hospital, Al Jouf Province, Saudi Arabia. Problems associated with
SSI include infection with multidrug resistant pathogens which are
difficult to treat and are associated with increased mortality.
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: We consider a network of two M/M/1 parallel queues having the same poisonnian arrival stream with rate λ. Upon his arrival to the system a customer heads to the shortest queue and stays until being served. If the two queues have the same length, an arriving customer chooses one of the two queues with the same probability. Each duration of service in the two queues is an exponential random variable with rate μ and no jockeying is permitted between the two queues. A new numerical method, based on linear programming and convex optimization, is performed for the computation of the steady state solution of the system.
Abstract: In this paper, we present an approach for soccer video
edition using a multimodal annotation. We propose to associate with
each video sequence of a soccer match a textual document to be used
for further exploitation like search, browsing and abstract edition.
The textual document contains video meta data, match meta data, and
match data. This document, generated automatically while the video
is analyzed, segmented and classified, can be enriched semi
automatically according to the user type and/or a specialized
recommendation system.
Abstract: Since primary school trips usually start from home,
attention by many scholars have been focused on the home end for
data gathering. Thereafter category analysis has often been relied
upon when predicting school travel demands. In this paper, school
end was relied on for data gathering and multivariate regression for
future travel demand prediction. 9859 pupils were surveyed by way
of questionnaires at 21 primary schools. The town was divided into 5
zones. The study was carried out in Skudai Town, Malaysia. Based
on the hypothesis that the number of primary school trip ends are
expected to be the same because school trips are fixed, the choice of
trip end would have inconsequential effect on the outcome. The
study compared empirical data for home and school trip end
productions and attractions. Variance from both data results was
insignificant, although some claims from home based family survey
were found to be grossly exaggerated. Data from the school trip ends
was relied on for travel demand prediction because of its
completeness. Accessibility, trip attraction and trip production were
then related to school trip rates under daylight and dry weather
conditions. The paper concluded that, accessibility is an important
parameter when predicting demand for future school trip rates.
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: This work aims to investigate a potential of
microalgae for utilizing industrial wastewater as a cheap nutrient for
their growth and oil accumulation. Wastewater was collected from
the effluent ponds of agro-industrial factories (cassava and ethanol
production plants). Only 2 microalgal strains were isolated and
identified as Scenedesmus quadricauda and Chlorella sp.. However,
only S. quadricauda was selected to cultivate in various wastewater
concentrations (10%, 20%, 40%, 60%, 80% and 100%). The highest
biomass obtained at 6.6×106 and 6.27×106 cells/ml when 60%
wastewater was used in flask and photo-bioreactor. The cultures gave
the highest lipid content at 18.58 % and 42.86% in cases of S.
quadricauda and S. obliquus. In addition, under salt stress (1.0 M
NaCl), S. obliquus demonstrated the highest lipid content at 50%
which was much more than the case of no NaCl adding. However, the
concentration of NaCl does not affect on lipid accumulation in case
of S. quadricauda.
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.
Abstract: Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.
Abstract: The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.
Abstract: This paper describes a three-dimensional thermal
model of the current path included in the low voltage power circuit
breakers. The model can be used to analyse the thermal behaviour of
the current path during both steady-state and transient conditions.
The current path lengthwise temperature distribution and timecurrent
characteristic of the terminal connections of the power circuit
breaker have been obtained. The influence of the electric current and
voltage drop on main electric contact of the circuit breaker has been
investigated. To validate the three-dimensional thermal model, some
experimental tests have been done. There is a good correlation
between experimental and simulation results.
Abstract: This paper addresses functional projective lag synchronization of Lorenz system with four unknown parameters, where the output of the master system lags behind the output of the slave system proportionally. For this purpose, an adaptive control law is proposed to make the states of two identical Lorenz systems asymptotically synchronize up. Based on Lyapunov stability theory, a novel criterion is given for asymptotical stability of the null solution of an error dynamics. Finally, some numerical examples are provided to show the effectiveness of our results.
Abstract: In this study, a nickel film with nano-crystalline grains,
high hardness and smooth surface was electrodeposited using a post
supercritical carbon dioxide (CO2) mixed Watts electrolyte. Although
the hardness was not as high as its Sc-CO2 counterpart, the thin coating
contained significantly less number of nano-sized pinholes. By
measuring the escape concentration of the dissolved CO2 in post
Sc-CO2 mixed electrolyte with the elapsed time, it was believed that
the residue of dissolved CO2 bubbles should closely relate to the
improvement in hardness and surface roughness over its conventional
plating counterpart. Therefore, shortening the duration of
electroplating with the raise of current density up to 0.5 A/cm2 could
effectively retain more post Sc-CO2 mixing effect. This study not only
confirms the roles of dissolved CO2 bubbles in electrolyte but also
provides a potential process to overcome most issues associated with
the cost in building high-pressure chamber for large size products and
continuous plating using supercritical method.
Abstract: In this Letter, a class of impulsive switched cellular neural networks with time-varying delays is investigated. At the same time, parametric uncertainties assumed to be norm bounded are considered. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions guaranteeing exponential stability for all admissible parametric uncertainties are derived via constructing appropriate Lyapunov functional. One numerical example is provided to illustrate the validity of the main results obtained in this paper.
Abstract: In the traditional architecture, buildings were designed
to achieve human comfort by using locally available building materials and construction technology which were more responsive to
their climatic and geographic condition. This paper will try to bring out the wisdom of the local masons and builders, often the inhabitants
themselves, about their way of living, and shaping their built environment, indoor and outdoor spaces, as a response to the local
climatic conditions, from the findings of a field
settlement.