Abstract: Nowadays, biometrical characterizations of Artemia
cysts are used as one of the most important factors in the study of
Artemia populations and intraspecific particularity; meanwhile these
characters can be used as economical indices. For example, typically
high hatching efficiency is possible due to the small diameter of
cysts (high number per gram); therefore small diameter of cysts
show someway high quality of cysts. This study was performed
during a ten year period, including two different ecological
conditions: rainy and drought. It is important from two different
aspects because it covers alteration of A. urmiana during ten years
also its variation in the best and worst environmental situations in
which salinity increased from 173.8 ppt in 1994 to 280.8 ppt in
2003/4. In this study the biometrical raw data of Artemia urmiana
cysts at seven stations from the Urmia Lake in 1994 and their seven
identical locations at 26 studied stations in 2003/4 were reanalyzed
again and compared together. Biometrical comparison of untreated
and decapsulated cysts in each of the seven similar stations showed a
highly significant variation between 1994 and 2003/4. Based on this
study, in whole stations the untreated and decapsulated cysts from
1994 were larger than cysts of 2003/4 without any exception. But
there was no logical relationship between salinity and chorion
thickness in the Urmia Lake. With regard to PCA analyses the
stations of two different studied years certainly have been separated
with factor 1 from each other. In conclusion, the interaction between
genetic and environmental factors can determine and explain
variation in the range of cysts diameter in Artemia.
Abstract: This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.
Abstract: In this paper real money demand function is analyzed
within multivariate time-series framework. Cointegration approach is
used (Johansen procedure) assuming interdependence between
money demand determinants, which are nonstationary variables. This
will help us to understand the behavior of money demand in Croatia,
revealing the significant influence between endogenous variables in
vector autoregrression system (VAR), i.e. vector error correction
model (VECM). Exogeneity of the explanatory variables is tested.
Long-run money demand function is estimated indicating slow speed
of adjustment of removing the disequilibrium. Empirical results
provide the evidence that real industrial production and exchange
rate explains the most variations of money demand in the long-run,
while interest rate is significant only in short-run.
Abstract: In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.
Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: National Biodiversity Database System (NBIDS) has
been developed for collecting Thai biodiversity data. The goal of this
project is to provide advanced tools for querying, analyzing,
modeling, and visualizing patterns of species distribution for
researchers and scientists. NBIDS data record two types of datasets:
biodiversity data and environmental data. Biodiversity data are
specie presence data and species status. The attributes of biodiversity
data can be further classified into two groups: universal and projectspecific
attributes. Universal attributes are attributes that are common
to all of the records, e.g. X/Y coordinates, year, and collector name.
Project-specific attributes are attributes that are unique to one or a
few projects, e.g., flowering stage. Environmental data include
atmospheric data, hydrology data, soil data, and land cover data
collecting by using GLOBE protocols. We have developed webbased
tools for data entry. Google Earth KML and ArcGIS were used
as tools for map visualization. webMathematica was used for simple
data visualization and also for advanced data analysis and
visualization, e.g., spatial interpolation, and statistical analysis.
NBIDS will be used by park rangers at Khao Nan National Park, and
researchers.
Abstract: The System Identification problem looks for a
suitably parameterized model, representing a given process. The
parameters of the model are adjusted to optimize a performance
function based on error between the given process output and
identified process output. The linear system identification field is
well established with many classical approaches whereas most of
those methods cannot be applied for nonlinear systems. The problem
becomes tougher if the system is completely unknown with only the
output time series is available. It has been reported that the
capability of Artificial Neural Network to approximate all linear and
nonlinear input-output maps makes it predominantly suitable for the
identification of nonlinear systems, where only the output time series
is available. [1][2][4][5]. The work reported here is an attempt to
implement few of the well known algorithms in the context of
modeling of nonlinear systems, and to make a performance
comparison to establish the relative merits and demerits.
Abstract: In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.
Abstract: The polyfunctional and highly reactive bio-polymer,
the chitosan was first regioselectively converted into dialkylated
chitosan using dimsyl anionic solution(NaH in DMSO) and
bromodecane after protecting amino groups by phthalic anhydride.
The dibenzo-18-crown-6-ether, on the other hand, was converted into
its carbonyl derivatives via Duff reaction prior to incorporate into
chitosan by Schiff base formation. Thus formed diformylated
dibenzo-18-crown-6-ether was condensed with lipophilic chitosan to
prepare the novel solvent extraction reagent. The products were
characterized mainly by IR and 1H-NMR. Hence, the multidentate
crown ether-embedded polyfunctional bio-material was tested for
extraction of Pd(II) and Pt(IV) in aqueous solution.
Abstract: In Mauritius, much emphasis is put on measures to
combat the high prevalence of non-communicable diseases (NCDs).
Health promotion campaigns for the adoption of healthy behaviors
and screening programs are done regularly by local authorities and
NCD surveys are carried out at intervals. However, the health
behaviors of the poor have not been investigated so far. This study
aims to give an insight on the perceptions of health status and
lifestyle health behaviors of poor people in Mauritius. A crosssectional
study among 83 persons benefiting from social aid in a
selected urban district was carried out. Results showed that 51.8% of
respondents perceived that they had good health status. 57.8% had no
known NCD whilst 25.3% had hypertension, followed by diabetes
(16.9%), asthma (9.6%) and heart disease (7.2%).They had low
smoking (10.8%) and alcohol consumption (6.0%) as well as high
physical activity prevalence (54.2%). These results were significantly
different from the NCD survey carried out in the general population.
Consumption of vegetables in the study was high. Overweight and
obesity trends were however similar to the NCD survey report 2009.
These findings contrast with other international studies showing poor
people having poor perceptions of health status and unhealthy
behavioral choices. Whether these positive health behaviors of poor
people in Mauritius arise out of choice or whether it is because the
alternative behavior is too costly remains to be investigated further.
Abstract: In this paper, the process of obtaining Q and R
matrices for optimal pitch aircraft control system has been described.
Since the innovation of optimal control method, the determination of
Q and R matrices for such system has not been fully specified. The
value of Q and R for optimal pitch aircraft control application, have
been simulated and calculated. The suitable results for Q and R have
been observed through the performance index (PI). If the PI is small
“enough", we would say the Q & R values are suitable for that
certain type of optimal control system. Moreover, for the same value
of PI, we could have different Q and R sets. Due to the rule-free
determination of Q and R matrices, a specific method is brought to
find out the rough value of Q and R referring to rather small value of
PI.
Abstract: The machining performance is determined by the
frequency characteristics of the machine-tool structure and the
dynamics of the cutting process. Therefore, the prediction of dynamic
vibration behavior of spindle tool system is of great importance for the
design of a machine tool capable of high-precision and high-speed
machining. The aim of this study is to develop a finite element model
to predict the dynamic characteristics of milling machine tool and
hence evaluate the influence of the preload of the spindle bearings. To
this purpose, a three dimensional spindle bearing model of a high
speed engraving spindle tool was created. In this model, the rolling
interfaces with contact stiffness defined by Harris model were used to
simulate the spindle bearing components. Then a full finite element
model of a vertical milling machine was established by coupling the
spindle tool unit with the machine frame structure. Using this model,
the vibration mode that had a dominant influence on the dynamic
stiffness was determined. The results of the finite element simulations
reveal that spindle bearing with different preloads greatly affect the
dynamic behavior of the spindle tool unit and hence the dynamic
responses of the vertical column milling system. These results were
validated by performing vibration on the individual spindle tool unit
and the milling machine prototype, respectively. We conclude that
preload of the spindle bearings is an important component affecting
the dynamic characteristics and machining performance of the entire
vertical column structure of the milling machine.
Abstract: To support mobility in ATM networks, a number of
technical challenges need to be resolved. The impact of handoff
schemes in terms of service disruption, handoff latency, cost
implications and excess resources required during handoffs needs to
be addressed. In this paper, a one phase handoff and route
optimization solution using reserved PVCs between adjacent ATM
switches to reroute connections during inter-switch handoff is
studied. In the second phase, a distributed optimization process is
initiated to optimally reroute handoff connections. The main
objective is to find the optimal operating point at which to perform
optimization subject to cost constraint with the purpose of reducing
blocking probability of inter-switch handoff calls for delay tolerant
traffic. We examine the relation between the required bandwidth
resources and optimization rate. Also we calculate and study the
handoff blocking probability due to lack of bandwidth for resources
reserved to facilitate the rapid rerouting.
Abstract: This work involved the use of phytoremediation to
remediate an aged soil contaminated with polychlorinated biphenyls
(PCBs). At microcosm scale, tests were prepared using soil samples
that have been collected in an industrial area with a total PCBs
concentration of about 250 μg kg-1. Medicago sativa and Lolium
italicum were the species selected in this study that is used as
“feasibility test" for full scale remediation. The experiment was
carried out with the addition of a mixture of randomly methylatedbeta-
cyclodextrins (RAMEB). At the end of the experiment analysis
of soil samples showed that in general the presence of plants has led
to a higher degradation of most congeners with respect to not
vegetated soil. The two plant species efficiencies were comparable
and improved by RAMEB addition with a final reduction of total
PCBs near to 50%. With increasing the chlorination of the congeners
the removal percentage of PCBs progressively decreased.
Abstract: This article is devoted to the numerical solution of
large-scale quadratic eigenvalue problems. Such problems arise in
a wide variety of applications, such as the dynamic analysis of
structural mechanical systems, acoustic systems, fluid mechanics,
and signal processing. We first introduce a generalized second-order
Krylov subspace based on a pair of square matrices and two initial
vectors and present a generalized second-order Arnoldi process for
constructing an orthonormal basis of the generalized second-order
Krylov subspace. Then, by using the projection technique and the
refined projection technique, we propose a restarted generalized
second-order Arnoldi method and a restarted refined generalized
second-order Arnoldi method for computing some eigenpairs of largescale
quadratic eigenvalue problems. Some theoretical results are also
presented. Some numerical examples are presented to illustrate the
effectiveness of the proposed methods.
Abstract: Efforts to secure supervisory control and data acquisition
(SCADA) systems must be supported under the guidance of
sound security policies and mechanisms to enforce them. Critical
elements of the policy must be systematically translated into a format
that can be used by policy enforcement components. Ideally, the
goal is to ensure that the enforced policy is a close reflection of
the specified policy. However, security controls commonly used to
enforce policies in the IT environment were not designed to satisfy
the specific needs of the SCADA environment. This paper presents
a language, based on the well-known XACML framework, for the
expression of authorization policies for SCADA systems.
Abstract: This paper proposes a new performance characterization for the test strategy intended for second order filters denominated Transient Analysis Method (TRAM). We evaluate the ability of the addressed test strategy for detecting deviation faults under simultaneous statistical fluctuation of the non-faulty parameters. For this purpose, we use Monte Carlo simulations and a fault model that considers as faulty only one component of the filter under test while the others components adopt random values (within their tolerance band) obtained from their statistical distributions. The new data reported here show (for the filters under study) the presence of hard-to-test components and relatively low fault coverage values for small deviation faults. These results suggest that the fault coverage value obtained using only nominal values for the non-faulty components (the traditional evaluation of TRAM) seem to be a poor predictor of the test performance.
Abstract: By the application of an improved back-propagation
neural network (BPNN), a model of current densities for a solid oxide
fuel cell (SOFC) with 10 layers is established in this study. To build
the learning data of BPNN, Taguchi orthogonal array is applied to
arrange the conditions of operating parameters, which totally 7 factors
act as the inputs of BPNN. Also, the average current densities
achieved by numerical method acts as the outputs of BPNN.
Comparing with the direct solution, the learning errors for all learning
data are smaller than 0.117%, and the predicting errors for 27
forecasting cases are less than 0.231%. The results show that the
presented model effectively builds a mathematical algorithm to predict
performance of a SOFC stack immediately in real time.
Also, the calculating algorithms are applied to proceed with the
optimization of the average current density for a SOFC stack. The
operating performance window of a SOFC stack is found to be
between 41137.11 and 53907.89. Furthermore, an inverse predicting
model of operating parameters of a SOFC stack is developed here by
the calculating algorithms of the improved BPNN, which is proved to
effectively predict operating parameters to achieve a desired
performance output of a SOFC stack.
Abstract: The effect of time-periodic oscillations of the Rayleigh- Benard system on the heat transport in dielectric liquids is investigated by weakly nonlinear analysis. We focus on stationary convection using the slow time scale and arrive at the real Ginzburg- Landau equation. Classical fourth order Runge-kutta method is used to solve the Ginzburg-Landau equation which gives the amplitude of convection and this helps in quantifying the heat transfer in dielectric liquids in terms of the Nusselt number. The effect of electrical Rayleigh number and the amplitude of modulation on heat transport is studied.