Abstract: The notions of I-vague normal groups with membership
and non-membership functions taking values in an involutary dually
residuated lattice ordered semigroup are introduced which generalize
the notions with truth values in a Boolean algebra as well as those
usual vague sets whose membership and non-membership functions
taking values in the unit interval [0, 1]. Various operations and
properties are established.
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: The modeling of sound radiation is of fundamental importance for understanding the propagation of acoustic waves and, consequently, develop mechanisms for reducing acoustic noise. The propagation of acoustic waves, are involved in various phenomena such as radiation, absorption, transmission and reflection. The radiation is studied through the linear equation of the acoustic wave that is obtained through the equation for the Conservation of Momentum, equation of State and Continuity. From these equations, is the Helmholtz differential equation that describes the problem of acoustic radiation. In this paper we obtained the solution of the Helmholtz differential equation for an infinite cylinder in a pulsating through free and homogeneous. The analytical solution is implemented and the results are compared with the literature. A numerical formulation for this problem is obtained using the Boundary Element Method (BEM). This method has great power for solving certain acoustical problems in open field, compared to differential methods. BEM reduces the size of the problem, thereby simplifying the input data to be worked and reducing the computational time used.
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: One of the purposes of the robust method of
estimation is to reduce the influence of outliers in the data, on the
estimates. The outliers arise from gross errors or contamination from
distributions with long tails. The trimmed mean is a robust estimate.
This means that it is not sensitive to violation of distributional
assumptions of the data. It is called an adaptive estimate when the
trimming proportion is determined from the data rather than being
fixed a “priori-.
The main objective of this study is to find out the robustness
properties of the adaptive trimmed means in terms of efficiency, high
breakdown point and influence function. Specifically, it seeks to find
out the magnitude of the trimming proportion of the adaptive
trimmed mean which will yield efficient and robust estimates of the
parameter for data which follow a modified Weibull distribution with
parameter λ = 1/2 , where the trimming proportion is determined by a
ratio of two trimmed means defined as the tail length. Secondly, the
asymptotic properties of the tail length and the trimmed means are
also investigated. Finally, a comparison is made on the efficiency of
the adaptive trimmed means in terms of the standard deviation for the
trimming proportions and when these were fixed a “priori".
The asymptotic tail lengths defined as the ratio of two trimmed
means and the asymptotic variances were computed by using the
formulas derived. While the values of the standard deviations for the
derived tail lengths for data of size 40 simulated from a Weibull
distribution were computed for 100 iterations using a computer
program written in Pascal language.
The findings of the study revealed that the tail lengths of the
Weibull distribution increase in magnitudes as the trimming
proportions increase, the measure of the tail length and the adaptive
trimmed mean are asymptotically independent as the number of
observations n becomes very large or approaching infinity, the tail
length is asymptotically distributed as the ratio of two independent
normal random variables, and the asymptotic variances decrease as
the trimming proportions increase. The simulation study revealed
empirically that the standard error of the adaptive trimmed mean
using the ratio of tail lengths is relatively smaller for different values
of trimming proportions than its counterpart when the trimming
proportions were fixed a 'priori'.
Abstract: Reliability assessment and risk analysis of rotating
machine rotors in various overload and malfunction situations
present challenge to engineers and operators. In this paper a new
analytical method for evaluation of rotor under large deformation is
addressed. Model is presented in general form to include also
composite rotors. Presented simulation procedure is based on
variational work method and has capability to account for geometric
nonlinearity, large displacement, nonlinear support effect and rotor
contacting other machine components. New shape functions are
presented which capable to predict accurate nonlinear profile of
rotor. The closed form solutions for various operating and
malfunction situations are expressed. Analytical simulation results
are discussed
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: An upwind difference approximation is used for a singularly perturbed problem in material science. Based on the discrete Green-s function theory, the error estimate in maximum norm is achieved, which is first-order uniformly convergent with respect to the perturbation parameter. The numerical experimental result is verified the valid of the theoretical analysis.
Abstract: Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.
Abstract: fibers of pure cellulose can be made from some bacteria such as acetobacter xylinum. Bacterial cellulose fibers are very pure, tens of nm across and about 0.5 micron long. The fibers are very stiff and, although nobody seems to have measured the strength of individual fibers. Their stiffness up to 70 GPa. Fundamental strengths should be at least greater than those of the best commercial polymers, but best bulk strength seems to about the same as that of steel. They can potentially be produced in industrial quantities at greatly lowered cost and water content, and with triple the yield, by a new process. This article presents a critical review of the available information on the bacterial cellulose as a biological nonwoven fabric with special emphasis on its fermentative production and applications. Characteristics of bacterial cellulose biofabric with respect to its structure and physicochemical properties are discussed. Current and potential applications of bacterial cellulose in textile, nonwoven cloth, paper, films synthetic fiber coating, food, pharmaceutical and other industries are also presented.
Abstract: Task of object localization is one of the major
challenges in creating intelligent transportation. Unfortunately, in
densely built-up urban areas, localization based on GPS only
produces a large error, or simply becomes impossible. New
opportunities arise for the localization due to the rapidly emerging
concept of a wireless ad-hoc network. Such network, allows
estimating potential distance between these objects measuring
received signal level and construct a graph of distances in which
nodes are the localization objects, and edges - estimates of the
distances between pairs of nodes. Due to the known coordinates of
individual nodes (anchors), it is possible to determine the location of
all (or part) of the remaining nodes of the graph. Moreover, road
map, available in digital format can provide localization routines
with valuable additional information to narrow node location search.
However, despite abundance of well-known algorithms for solving
the problem of localization and significant research efforts, there are
still many issues that currently are addressed only partially. In this
paper, we propose localization approach based on the graph mapped
distances on the digital road map data basis. In fact, problem is
reduced to distance graph embedding into the graph representing area
geo location data. It makes possible to localize objects, in some cases
even if only one reference point is available. We propose simple
embedding algorithm and sample implementation as spatial queries
over sensor network data stored in spatial database, allowing
employing effectively spatial indexing, optimized spatial search
routines and geometry functions.
Abstract: The drug discovery process starts with protein
identification because proteins are responsible for many functions
required for maintenance of life. Protein identification further needs
determination of protein function. Proposed method develops a
classifier for human protein function prediction. The model uses
decision tree for classification process. The protein function is
predicted on the basis of matched sequence derived features per each
protein function. The research work includes the development of a
tool which determines sequence derived features by analyzing
different parameters. The other sequence derived features are
determined using various web based tools.
Abstract: Despite the internet, which is one of the mass media
that has become quite common in recent years, the relationship of
Advertisement with Television and Cinema, which have always
drawn attention of researchers as basic media and where visual use is
in the foreground, have also become the subject of various studies.
Based on the assumption that the known fundamental effects of
advertisements on consumers are closely related to the creative
process of advertisements as well as the nature and characteristics of
the medium where they are used, these basic mass media (Television
and Cinema) and the consumer motivations of the advertisements
they broadcast have become a focus of study.
Given that the viewers of the mass media in question have shifted
from a passive position to a more active one especially in recent years
and approach contents of advertisements, as they do all contents, in a
more critical and “pitiless" manner, it is possible to say that
individuals make more use of advertisements than in the past and
combine their individual goals with the goals of the advertisements.
This study, which aims at finding out what the goals of these new
individual advertisement use are, how they are shaped by the distinct
characteristics of Television and Cinema, where visuality takes
precedence as basic mass media, and what kind of places they occupy
in the minds of consumers, has determined consumers- motivations
as: “Entertainment", “Escapism", “Play", “Monitoring/Discovery",
“Opposite Sex" and “Aspirations and Role Models".
This study intends to reveal the differences or similarities among
the needs and hence the gratifications of viewers who consume
advertisements on Television or at the Cinema, which are two basic
media where visuality is prioritized.
Abstract: The current methods of predictive controllers are
utilized for those processes in which the rate of output variations is
not high. For such processes, therefore, stability can be achieved by
implementing the constrained predictive controller or applying
infinite prediction horizon. When the rate of the output growth is
high (e.g. for unstable nonminimum phase process) the stabilization
seems to be problematic. In order to avoid this, it is suggested to
change the method in the way that: first, the prediction error growth
should be decreased at the early stage of the prediction horizon, and
second, the rate of the error variation should be penalized. The
growth of the error is decreased through adjusting its weighting
coefficients in the cost function. Reduction in the error variation is
possible by adding the first order derivate of the error into the cost
function. By studying different examples it is shown that using these
two remedies together, the closed-loop stability of unstable
nonminimum phase process can be achieved.
Abstract: We report the electronic structure and optical
properties of NdF3 compound. Our calculations are based on density
functional theory (DFT) using the full potential linearized augmented
plane wave (FPLAPW) method with the inclusion of spin orbit
coupling. We employed the local spin density approximation (LSDA)
and Coulomb-corrected local spin density approximation, known for
treating the highly correlated 4f electrons properly, is able to
reproduce the correct insulating ground state. We find that the
standard LSDA approach is incapable of correctly describing the
electronic properties of such materials since it positions the f-bands
incorrectly resulting in an incorrect metallic ground state. On the
other hand, LSDA + U approximation, known for treating the highly
correlated 4f electrons properly, is able to reproduce the correct
insulating ground state. Interestingly, however, we do not find any
significant differences in the optical properties calculated using
LSDA, and LSDA + U suggesting that the 4f electrons do not play a
decisive role in the optical properties of these compounds. The
reflectivity for NdF3 compound stays low till 7 eV which is
consistent with their large energy gaps. The calculated energy gaps
are in good agreement with experiments. Our calculated reflectivity
compares well with the experimental data and the results are analyzed
in the light of band to band transitions.
Abstract: This paper presents a speed fuzzy sliding mode
controller for a vector controlled induction machine (IM) fed by a
voltage source inverter (PWM).
The sliding mode based fuzzy control method is developed to
achieve fast response, a best disturbance rejection and to maintain a
good decoupling.
The problem with sliding mode control is that there is high
frequency switching around the sliding mode surface. The FSMC is
the combination of the robustness of Sliding Mode Control (SMC)
and the smoothness of Fuzzy Logic (FL). To reduce the torque
fluctuations (chattering), the sign function used in the conventional
SMC is substituted with a fuzzy logic algorithm.
The proposed algorithm was simulated by Matlab/Simulink
software and simulation results show that the performance of the
control scheme is robust and the chattering problem is solved.
Abstract: We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Abstract: Topology Optimization is a defined as the method of
determining optimal distribution of material for the assumed design
space with functionality, loads and boundary conditions [1].
Topology optimization can be used to optimize shape for the
purposes of weight reduction, minimizing material requirements or
selecting cost effective materials [2]. Topology optimization has been
implemented through the use of finite element methods for the
analysis, and optimization techniques based on the method of moving
asymptotes, genetic algorithms, optimality criteria method, level sets
and topological derivatives. Case study of Typical “Fuselage design"
is considered for this paper to explain the benefits of Topology
Optimization in the design cycle. A cylindrical shell is assumed as
the design space and aerospace standard pay loads were applied on
the fuselage with wing attachments as constraints. Then topological
optimization is done using Finite Element (FE) based software. This
optimization results in the structural concept design which satisfies
all the design constraints using minimum material.