Abstract: The approach proposed here is oriented in the direction of fuzzy system for the analysis and the synthesis of intelligent climate controllers, the simulation of the internal climate of the greenhouse is achieved by a linear model whose coefficients are obtained by identification. The use of fuzzy logic controllers for the regulation of climate variables represents a powerful way to minimize the energy cost. Strategies of reduction and optimization are adopted to facilitate the tuning and to reduce the complexity of the controller.
Abstract: This paper presents a multi-objective order allocation
planning problem with the consideration of various real-world
production features. A novel hybrid intelligent optimization model,
integrating a multi-objective memetic optimization process, a Monte
Carlo simulation technique and a heuristic pruning technique, is
proposed to handle this problem. Experiments based on industrial data
are conducted to validate the proposed model. Results show that (1)
the proposed model can effectively solve the investigated problem by
providing effective production decision-making solutions, which
outperformsan NSGA-II-based optimization process and an industrial
method.
Abstract: This paper presented two new efficient algorithms
for contour approximation. The proposed algorithm is compared
with Ramer (good quality), Triangle (faster) and Trapezoid (fastest)
in this work; which are briefly described. Cartesian co-ordinates of
an input contour are processed in such a manner that finally
contours is presented by a set of selected vertices of the edge of the
contour. In the paper the main idea of the analyzed procedures for
contour compression is performed. For comparison, the mean
square error and signal-to-noise ratio criterions are used.
Computational time of analyzed methods is estimated depending on
a number of numerical operations. Experimental results are
obtained both in terms of image quality, compression ratios, and
speed. The main advantages of the analyzed algorithm is small
numbers of the arithmetic operations compared to the existing
algorithms.
Abstract: This paper proposes the method combining artificial
neural network (ANN) with particle swarm optimization (PSO) to
implement the maximum power point tracking (MPPT) by controlling
the rotor speed of the wind generator. First, the measurements of wind
speed, rotor speed of wind power generator and output power of wind
power generator are applied to train artificial neural network and to
estimate the wind speed. Second, the method mentioned above is
applied to estimate and control the optimal rotor speed of the wind
turbine so as to output the maximum power. Finally, the result reveals
that the control system discussed in this paper extracts the maximum
output power of wind generator within the short duration even in the
conditions of wind speed and load impedance variation.
Abstract: The aim of this study was to remove the two principal
noises which disturb the surface electromyography signal
(Diaphragm). These signals are the electrocardiogram ECG artefact
and the power line interference artefact. The algorithm proposed
focuses on a new Lean Mean Square (LMS) Widrow adaptive
structure. These structures require a reference signal that is correlated
with the noise contaminating the signal. The noise references are
then extracted : first with a noise reference mathematically
constructed using two different cosine functions; 50Hz (the
fundamental) function and 150Hz (the first harmonic) function for
the power line interference and second with a matching pursuit
technique combined to an LMS structure for the ECG artefact
estimation. The two removal procedures are attained without the use
of supplementary electrodes. These techniques of filtering are
validated on real records of surface diaphragm electromyography
signal. The performance of the proposed methods was compared with
already conducted research results.
Abstract: Information Technology (IT) projects are always
accompanied by various risks and because of high rate of failure in
such projects, managing risks in order to neutralize or at least
decrease their effects on the success of the project is strongly
essential. In this paper, fuzzy analytical hierarchy process (FAHP) is
exploited as a means of risk evaluation methodology to prioritize and
organize risk factors faced in IT projects. A real case of IT projects, a
project of design and implementation of an integrated information
system in a vehicle producing company in Iran is studied. Related
risk factors are identified and then expert qualitative judgments about
these factors are acquired. Translating these judgments to fuzzy
numbers and using them as an input to FAHP, risk factors are then
ranked and prioritized by FAHP in order to make project managers
aware of more important risks and enable them to adopt suitable
measures to deal with these highly devastative risks.
Abstract: This paper focuses on robust design and optimization
of industrial production wastes. Past literatures were reviewed to case
study Clamason Industries Limited (CIL) - a leading ladder-tops
manufacturer. A painstaking study of the firm-s practices at the shop
floor revealed that Over-production, Waiting time, Excess inventory,
and Defects are the major wastes that are impeding their progress and
profitability. Design expert8 software was used to apply Taguchi
robust design and response surface methodology in order to model,
analyse and optimise the wastes cost in CIL. Waiting time and overproduction
rank first and second in contributing to the costs of wastes
in CIL. For minimal wastes cost the control factors of overproduction,
waiting-time, defects and excess-inventory must be set at
0.30, 390.70, 4 and 55.70 respectively for CIL. The optimal value of
cost of wastes for the months studied was 22.3679. Finally, a
recommendation was made that for the company to enhance their
profitability and customer satisfaction, they must adopt the Shingeo
Shingo-s Single Minute Exchange of Dies (SMED), which will
immediately tackle the waste of waiting by drastically reducing their
setup time.
Abstract: This paper proposes a set of quasi-static mathematical
model of magnetic fields caused by high voltage conductors of
distribution transformer by using a set of second-order partial
differential equation. The modification for complex magnetic field
analysis and time-harmonic simulation are also utilized. In this
research, transformers were study in both balanced and unbalanced
loading conditions. Computer-based simulation utilizing the threedimensional
finite element method (3-D FEM) is exploited as a tool
for visualizing magnetic fields distribution volume a distribution
transformer. Finite Element Method (FEM) is one among popular
numerical methods that is able to handle problem complexity in
various forms. At present, the FEM has been widely applied in most
engineering fields. Even for problems of magnetic field distribution,
the FEM is able to estimate solutions of Maxwell-s equations
governing the power transmission systems. The computer simulation
based on the use of the FEM has been developed in MATLAB
programming environment.
Abstract: This paper describes a new measuring algorithm for
three-dimensional (3-D) braided composite material .Braided angle is
an important parameter of braided composites. The objective of this
paper is to present an automatic measuring system. In the paper, the
algorithm is performed by using vcµ6.0 language on PC. An
advanced filtered algorithm for image of 3-D braided composites
material performs has been developed. The procedure is completely
automatic and relies on the gray scale information content of the
images and their local wavelet transform modulus maxims.
Experimental results show that the proposed method is feasible.
The algorithm was tested on both carbon-fiber and glass-fiber
performs.
Abstract: Anaerobic treatment has many advantages over other
biological method particularly when used to treat complex
wastewater such as petroleum refinery wastewater. In this study two
Up-flow Anaerobic Sludge Blanket (UASB) reactors were operated
in parallel to treat six volumetric organic loads (0.58, 1.21, 0.89,
2.34, 1.47 and 4.14 kg COD/m3·d) to evaluate the chemical oxygen
demand (COD) removal efficiency. The reactors were continuously
adapting to the changing of operation condition with increase in the
removal efficiency or slight decrease until the last load which was
more than two times the load, at which the reactor stressed and the
removal efficiency decreased to 75% with effluent concentration of
1746 mg COD/L. Other parameters were also monitored such as pH,
alkalinity, volatile fatty acid and gas production rate. The UASB
reactor was suitable to treat petroleum refinery wastewater and the
highest COD removal rate was 83% at 1215 kg/m3·d with COD
concentration about 356 mg/L in the effluent.
Abstract: This paper proposes an innovative methodology for
Acceptance Sampling by Variables, which is a particular category of
Statistical Quality Control dealing with the assurance of products
quality. Our contribution lies in the exploitation of machine learning
techniques to address the complexity and remedy the drawbacks of
existing approaches. More specifically, the proposed methodology
exploits Artificial Neural Networks (ANNs) to aid decision making
about the acceptance or rejection of an inspected sample. For any
type of inspection, ANNs are trained by data from corresponding
tables of a standard-s sampling plan schemes. Once trained, ANNs
can give closed-form solutions for any acceptance quality level and
sample size, thus leading to an automation of the reading of the
sampling plan tables, without any need of compromise with the
values of the specific standard chosen each time. The proposed
methodology provides enough flexibility to quality control engineers
during the inspection of their samples, allowing the consideration of
specific needs, while it also reduces the time and the cost required for
these inspections. Its applicability and advantages are demonstrated
through two numerical examples.
Abstract: In this paper, a direct method based on variable step
size Block Backward Differentiation Formula which is referred as
BBDF2 for solving second order Ordinary Differential Equations
(ODEs) is developed. The advantages of the BBDF2 method over the
corresponding sequential variable step variable order Backward
Differentiation Formula (BDFVS) when used to solve the same
problem as a first order system are pointed out. Numerical results are
given to validate the method.
Abstract: Recently, the findings on the MEG iterative scheme has demonstrated to accelerate the convergence rate in solving any system of linear equations generated by using approximation equations of boundary value problems. Based on the same scheme, the aim of this paper is to investigate the capability of a family of four-point block iterative methods with a weighted parameter, ω such as the 4 Point-EGSOR, 4 Point-EDGSOR, and 4 Point-MEGSOR in solving two-dimensional elliptic partial differential equations by using the second-order finite difference approximation. In fact, the formulation and implementation of three four-point block iterative methods are also presented. Finally, the experimental results show that the Four Point MEGSOR iterative scheme is superior as compared with the existing four point block schemes.
Abstract: This paper investigates the optimization problem of
multi-product aggregate production planning (APP) with fuzzy data.
From a comprehensive viewpoint of conserving the fuzziness of input
information, this paper proposes a method that can completely
describe the membership function of the performance measure. The
idea is based on the well-known Zadeh-s extension principle which
plays an important role in fuzzy theory. In the proposed solution
procedure, a pair of mathematical programs parameterized by
possibility level a is formulated to calculate the bounds of the
optimal performance measure at a . Then the membership function of
the optimal performance measure is constructed by enumerating
different values of a . Solutions obtained from the proposed method
contain more information, and can offer more chance to achieve the
feasible disaggregate plan. This is helpful to the decision-maker in
practical applications.
Abstract: Studies on residential satisfaction have been actively
discussed under family house setting. However, limited studies have
been conducted on student residential satisfaction. This study is an
attempt to fill the research gap. It focuses on the influence of socioeconomic
on students- satisfaction with the universities- student
housing facilities. The students who stayed at the on-campus student
housing were the respondents. This study employed two-stage cluster
sampling method in classifying the respondents. Self-administered
questionnaires were distributed face-to-face to the students. In
general, it is confirmed that students- socio-economic backgrounds
have influence on the students- satisfaction with their housing
facilities. The main influential factors were the students- economic
status, sense of sharing, and ethnicity of their roommates.
Furthermore, this study could also provide a useful feedback for the
universities in order to improve their student housing facilities.
Abstract: This paper deals with the thermo-mechanical deformation behavior of shear deformable functionally graded ceramicmetal (FGM) plates. Theoretical formulations are based on higher order shear deformation theory with a considerable amendment in the transverse displacement using finite element method (FEM). The mechanical properties of the plate are assumed to be temperaturedependent and graded in the thickness direction according to a powerlaw distribution in terms of the volume fractions of the constituents. The temperature field is supposed to be a uniform distribution over the plate surface (XY plane) and varied in the thickness direction only. The fundamental equations for the FGM plates are obtained using variational approach by considering traction free boundary conditions on the top and bottom faces of the plate. A C0 continuous isoparametric Lagrangian finite element with thirteen degrees of freedom per node have been employed to accomplish the results. Convergence and comparison studies have been performed to demonstrate the efficiency of the present model. The numerical results are obtained for different thickness ratios, aspect ratios, volume fraction index and temperature rise with different loading and boundary conditions. Numerical results for the FGM plates are provided in dimensionless tabular and graphical forms. The results proclaim that the temperature field and the gradient in the material properties have significant role on the thermo-mechanical deformation behavior of the FGM plates.
Abstract: In the previous multi-solid models,¤ò approach is
used for the calculation of fugacity in the liquid phase. For the first
time, in the proposed multi-solid thermodynamic model,γ approach
has been used for calculation of fugacity in the liquid mixture.
Therefore, some activity coefficient models have been studied that
the results show that the predictive Wilson model is more appropriate
than others. The results demonstrate γ approach using the predictive
Wilson model is in more agreement with experimental data than the
previous multi-solid models. Also, by this method, generates a new
approach for presenting stability analysis in phase equilibrium
calculations. Meanwhile, the run time in γ approach is less than the
previous methods used ¤ò approach. The results of the new model
present 0.75 AAD % (Average Absolute Deviation) from the
experimental data which is less than the results error of the previous
multi-solid models obviously.
Abstract: Resource-constrained project scheduling is an NPhard
optimisation problem. There are many different heuristic
strategies how to shift activities in time when resource requirements
exceed their available amounts. These strategies are frequently based
on priorities of activities. In this paper, we assume that a suitable
heuristic has been chosen to decide which activities should be
performed immediately and which should be postponed and
investigate the resource-constrained project scheduling problem
(RCPSP) from the implementation point of view. We propose an
efficient routine that, instead of shifting the activities, extends their
duration. It makes it possible to break down their duration into active
and sleeping subintervals. Then we can apply the classical Critical
Path Method that needs only polynomial running time. This
algorithm can simply be adapted for multiproject scheduling with
limited resources.
Abstract: Biological reactions of individuals of a testing animal
to toxic substance are unique and can be used as an indication of the
existing of toxic substance. However, to distinguish such phenomenon
need a very complicate system and even more complicate to analyze
data in 3 dimensional. In this paper, a system to evaluate in vitro
biological activities to acute toxicity of stochastic self-affine
non-stationary signal of 3D goldfish swimming by using fractal
analysis is introduced. Regular digital camcorders are utilized by
proposed algorithm 3DCCPC to effectively capture and construct 3D
movements of the fish. A Critical Exponent Method (CEM) has been
adopted as a fractal estimator. The hypothesis was that the swimming
of goldfish to acute toxic would show the fractal property which
related to the toxic concentration. The experimental results supported
the hypothesis by showing that the swimming of goldfish under the
different toxic concentration has fractal properties. It also shows that
the fractal dimension of the swimming related to the pH value of FD Ôëê
0.26pH + 0.05. With the proposed system, the fish is allowed to swim
freely in all direction to react to the toxic. In addition, the trajectories
are precisely evaluated by fractal analysis with critical exponent
method and hence the results exhibit with much higher degree of
confidence.
Abstract: The use of magnetic and magnetic/gold core/shell
nanoparticles in biotechnology or medicine has shown good promise
due to their hybrid nature which possesses superior magnetic and
optical properties. Some of these potential applications include
hyperthermia treatment, bio-separations, diagnostics, drug delivery
and toxin removal. Synthesis refinement to control geometric and
magnetic/optical properties, and finding functional surfactants for
biomolecular attachment, are requirements to meet application
specifics.
Various high-temperature preparative methods were used for the
synthesis of iron oxide and gold-coated iron oxide nanoparticles.
Different surface functionalities, such as 11-aminoundecanoic and
11-mercaptoundecanoic acid, were introduced on the surface of the
particles to facilitate further attachment of biomolecular functionality
and drug-like molecules. Nanoparticle thermal stability, composition,
state of aggregation, size and morphology were investigated and the
results from techniques such as Fourier Transform-Infra Red
spectroscopy (FT-IR), Ultraviolet visible spectroscopy (UV-vis),
Transmission Electron Microscopy (TEM) and thermal analysis are
discussed.