Abstract: As more people from non-technical backgrounds
are becoming directly involved with large-scale ontology
development, the focal point of ontology research has shifted
from the more theoretical ontology issues to problems
associated with the actual use of ontologies in real-world,
large-scale collaborative applications. Recently the National
Science Foundation funded a large collaborative ontology
development project for which a new formal ontology model,
the Ontology Abstract Machine (OAM), was developed to
satisfy some unique functional and data representation
requirements. This paper introduces the OAM model and the
related algorithms that enable maintenance of an ontology that
supports node-based user access. The successful software
implementation of the OAM model and its subsequent
acceptance by a large research community proves its validity
and its real-world application value.
Abstract: Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.
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: In this paper an approaches for increasing the
effectiveness of error detection in computer network channels with
Pulse-Amplitude Modulation (PAM) has been proposed. Proposed
approaches are based on consideration of special feature of errors,
which are appearances in line with PAM. The first approach consists
of CRC modification specifically for line with PAM. The second
approach is base of weighted checksums using. The way for
checksum components coding has been developed. It has been shown
that proposed checksum modification ensure superior digital data
control transformation reliability for channels with PAM in compare
to CRC.
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: 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: 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: The design of an active leg orthosis for tumble
protection is proposed in this paper. The orthosis would be applied to
assist elders or invalids in rebalancing while they fall unexpectedly.
We observe the regain balance motion of healthy and youthful people,
and find the difference to elders or invalids. First, the physical model
of leg would be established, and we consider the leg motions are
achieve through four joints (phalanx stem, ankle, knee, and hip joint)
and five links (phalanges, talus, tibia, femur, and hip bone). To
formulate the dynamic equations, the coordinates which can clearly
describe the position in 3D space are first defined accordance with the
human movement of leg, and the kinematics and dynamics of the leg
movement can be formulated based on the robotics. For the purpose,
assisting elders and invalids in avoiding tumble, the posture variation
of unbalance and regaining balance motion are recorded by the
motion-capture image system, and the trajectory is taken as the desire
one. Then we calculate the force and moment of each joint based on
the leg motion model through programming MATLAB code. The
results would be primary information of the active leg orthosis design
for tumble protection.
Abstract: The indistinctness of the manufacturing processes makes that a parts cannot be realized in an absolutely exact way towards the specifications on the dimensions. It is thus necessary to assume that the effectively realized product has to belong in a very strict way to compatible intervals with a correct functioning of the parts. In this paper we present an approach based on mixing tow different characteristics theories, the fuzzy system and Petri net system. This tool has been proposed to model and control the quality in an assembly system. A robust command of a mechanical assembly process is presented as an application. This command will then have to maintain the specifications interval of parts in front of the variations. It also illustrates how the technique reacts when the product quality is high, medium, or low.
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: Taking into account the link between the efficiency of
a detector and the complexity of a stealth mechanism, we propose in
this paper a new formalism for stealth using graph theory.
Abstract: Kuwait-s electric power system is vertically integrated
organization owned and operated by the government. For more than
five decades, the government of Kuwait has provided relatively
reliable electric services to consumers with subsidized electric
service fees. Given the country-s rapid socio-economical
development and consequently the increase of electricity demand, a
question that inflicts itself: Is it necessary to reform the power system
to face the fast growing demand? This paper recommends that the
government should consider the private sector as a partner in
operating the power system. Therefore, power system restructuring is
needed to allow such partnership. There are challenges that prevent
such restructuring. Abstract recommendations toward resolving these
challenges are proposed.
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: To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
correlated.