Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: Theobjective of this study was to evaluate the optimal
treatment condition of Fenton oxidation process to removal
contaminant in soil slurry contaminated by petroleum hydrocarbons.
This research studied somefactors that affect the removal efficiency
of petroleum hydrocarbons in soil slurry including molar ratio of
hydrogen peroxide (H2O2) to ferrous ion(Fe2+), pH condition and
reaction time.The resultsdemonstrated that the optimum condition
was that the molar ratio of H2O2:Fe3+ was 200:1,the pHwas 4.0and
the rate of reaction was increasing rapidly from starting point to 7th
hour and destruction kinetic rate (k) was 0.24 h-1. Approximately
96% of petroleum hydrocarbon was observed(initialtotal petroleum
hydrocarbon (TPH) concentration = 70±7gkg-1)
Abstract: A study of electromagnetic flow meter is presented in the paper. Comparison has been made between the analytical and the numerical results by the use of FEM numerical analysis (Quick Field 5.6) for determining polarization voltage through the circle cross section of the polarization transducer. Exciting and geometrical parameters increasing its effectiveness has been examined. The aim is to obtain maximal output signal. The investigations include different variants of the magnetic flux density distribution around the tube: homogeneous field of magnitude Bm, linear distribution with maximal value Bm and trapezium distribution conserving the same exciting magnetic energy as the homogeneous field.
Abstract: This paper presents the utilizing of ferroelectric
material on antenna application. There are two different ferroelectric
had been used on the proposed antennas which include of Barium
Strontium Titanate (BST) and Bismuth Titanate (BiT), suitable for
Access Points operating in the WLAN IEEE 802.11 b/g and WiMAX
IEEE 802.16 within the range of 2.3 GHz to 2.5 GHz application.
BST, which had been tested to own a dielectric constant of εr = 15
while BiT has a dielectric constant that higher than BST which is εr =
21 and both materials are in rectangular shaped. The influence of
various parameters on antenna characteristics were investigated
extensively using commercial electromagnetic simulations software
by Communication Simulation Technology (CST). From theoretical
analysis and simulation results, it was demonstrated that ferroelectric
material used have not only improved the directive emission but also
enhanced the radiation efficiency.
Abstract: Model Predictive Control has been previously applied
to supply chain problems with promising results; however hitherto
proposed systems possessed no information on future demand. A
forecasting methodology will surely promote the efficiency of
control actions by providing insight on the future. A complete supply
chain management framework that is based on Model Predictive
Control (MPC) and Time Series Forecasting will be presented in this
paper. The proposed framework will be tested on industrial data in
order to assess the efficiency of the method and the impact of
forecast accuracy on overall control performance of the supply chain.
To this end, forecasting methodologies with different characteristics
will be implemented on test data to generate forecasts that will serve
as input to the Model Predictive Control module.
Abstract: In designing river intakes and diversion structures, it is paramount that the sediments entering the intake are minimized or, if possible, completely separated. Due to high water velocity, sediments can significantly damage hydraulic structures especially when mechanical equipment like pumps and turbines are used. This subsequently results in wasting water, electricity and further costs. Therefore, it is prudent to investigate and analyze the performance of lateral intakes affected by sediment control structures. Laboratory experiments, despite their vast potential and benefits, can face certain limitations and challenges. Some of these include: limitations in equipment and facilities, space constraints, equipment errors including lack of adequate precision or mal-operation, and finally, human error. Research has shown that in order to achieve the ultimate goal of intake structure design – which is to design longlasting and proficient structures – the best combination of sediment control structures (such as sill and submerged vanes) along with parameters that increase their performance (such as diversion angle and location) should be determined. Cost, difficulty of execution and environmental impacts should also be included in evaluating the optimal design. This solution can then be applied to similar problems in the future. Subsequently, the model used to arrive at the optimal design requires high level of accuracy and precision in order to avoid improper design and execution of projects. Process of creating and executing the design should be as comprehensive and applicable as possible. Therefore, it is important that influential parameters and vital criteria is fully understood and applied at all stages of choosing the optimal design. In this article, influential parameters on optimal performance of the intake, advantages and disadvantages, and efficiency of a given design are studied. Then, a multi-criterion decision matrix is utilized to choose the optimal model that can be used to determine the proper parameters in constructing the intake.
Abstract: Today-s economy is in a permanent change, causing
merger and acquisitions and co operations between enterprises. As a
consequence, process adaptations and realignments result in systems
integration and software development projects. Processes and
procedures to execute such projects are still reliant on craftsman-ship
of highly skilled workers. A generally accepted, industrialized
production, characterized by high efficiency and quality, seems
inevitable.
In spite of this, current concepts of software industrialization are
aimed at traditional software engineering and do not consider the
characteristics of systems integration. The present work points out
these particularities and discusses the applicability of existing
industrial concepts in the systems integration domain. Consequently
it defines further areas of research necessary to bring the field of
systems integration closer to an industrialized production, allowing a
higher efficiency, quality and return on investment.
Abstract: This paper proposes a novel feature extraction method,
based on Discrete Wavelet Transform (DWT) and K-L Seperability
(KLS), for the classification of Functional Data (FD). This method
combines the decorrelation and reduction property of DWT and the
additive independence property of KLS, which is helpful to extraction
classification features of FD. It is an advanced approach of the
popular wavelet based shrinkage method for functional data reduction
and classification. A theory analysis is given in the paper to prove the
consistent convergence property, and a simulation study is also done
to compare the proposed method with the former shrinkage ones. The
experiment results show that this method has advantages in improving
classification efficiency, precision and robustness.
Abstract: This paper presents the results of an experimental study on the performance of a triboelectric separator of plastic mixtures used for recycling. The separator consists of four cylindrical electrodes. The principle behind the separation technique is based on the difference in the Coulomb force acting on the plastic particles after triboelectric charging. The separation of mixtures of acrylonitrile butadiene styrene (ABS) and polystyrene (PS) using this method was studied. The effects of the triboelectric charging time and applied voltage on the separation efficiency were investigated. The experimental results confirm that it is possible to obtain a high purity and recovery rate for the initial compositions considered in this study.
Abstract: Accurate and comprehensive thermodynamic properties of pure and mixture of refrigerants are in demand by both producers and users of these materials. Information about thermodynamic properties is important initially to qualify potential candidates for working fluids in refrigeration machinery. From practical point of view, Refrigerants and refrigerant mixtures are widely used as working fluids in many industrial applications, such as refrigerators, heat pumps, and power plants The present work is devoted to evaluating seven cubic equations of state (EOS) in predicting gas and liquid phase volumetric properties of nine ozone-safe refrigerants both in super and sub-critical regions. The evaluations, in sub-critical region, show that TWU and PR EOS are capable of predicting PVT properties of refrigerants R32 within 2%, R22, R134a, R152a and R143a within 1% and R123, R124, R125, TWU and PR EOS's, from literature data are 0.5% for R22, R32, R152a, R143a, and R125, 1% for R123, R134a, and R141b, and 2% for R124. Moreover, SRK EOS predicts PVT properties of R22, R125, and R123 to within aforementioned errors. The remaining EOS's predicts volumetric properties of this class of fluids with higher errors than those above mentioned which are at most 8%.In general, the results are in favor of the preference of TWU and PR EOS over other remaining EOS's in predicting densities of all mentioned refrigerants in both super and sub critical regions. Typically, this refrigerant is known to offer advantages such as ozone depleting potential equal to zero, Global warming potential equal to 140, and no toxic.
Abstract: In historical science and social science, the influence
of natural disaster upon society is a matter of great interest. In
recent years, some archives are made through many hands for natural
disasters, however it is inefficiency and waste. So, we suppose a
computer system to create a historical natural disaster archive. As
the target of this analysis, we consider newspaper articles. The news
articles are considered to be typical examples that prescribe the
temporal relations of affairs for natural disaster. In order to do this
analysis, we identify the occurrences in newspaper articles by some
index entries, considering the affairs which are specific to natural
disasters, and show the temporal relation between natural disasters.
We designed and implemented the automatic system of “extraction
of the occurrences of natural disaster" and “temporal relation table
for natural disaster."
Abstract: In this paper, the problem of estimating the optimal
radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple-
output (MIMO) system operating in a Rayleigh fading environment
is examined. The optimisation between the radio capacity
and the theoretically achievable average channel capacity (in the
sense of information theory) per user of a MIMO single-cell SS system
operating in a Rayleigh fading environment is presented. Then,
the spectral efficiency is estimated in terms of the achievable average
channel capacity per user, during the operation over a broadcast
time-varying link, and leads to a simple novel-closed form expression
for the optimal radio capacity value based on the maximization
of the achieved spectral efficiency. Numerical results are presented to
illustrate the proposed analysis.
Abstract: This paper presents an approach which is based on the
use of supervised feed forward neural network, namely multilayer
perceptron (MLP) neural network and finite element method (FEM)
to solve the inverse problem of parameters identification. The
approach is used to identify unknown parameters of ferromagnetic
materials. The methodology used in this study consists in the
simulation of a large number of parameters in a material under test,
using the finite element method (FEM). Both variations in relative
magnetic permeability and electrical conductivity of the material
under test are considered. Then, the obtained results are used to
generate a set of vectors for the training of MLP neural network.
Finally, the obtained neural network is used to evaluate a group of
new materials, simulated by the FEM, but not belonging to the
original dataset. Noisy data, added to the probe measurements is used
to enhance the robustness of the method. The reached results
demonstrate the efficiency of the proposed approach, and encourage
future works on this subject.
Abstract: In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.
Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: The purpose of the present study is the investigation
of the relationship between knowledge management and enabling
managers based on achieving proper function. This research is
descriptive and investigative. The sample includes all male and
female high school managers of first and second regions of Urmia
including 98 school and accordingly 98 managers. The instrument
applied was a questionnaire. To sum up, there is a statistically
significant relationship between knowledge management and
empowering managers. In the end, several suggestions are provided.
Abstract: In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.
Abstract: We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Abstract: In this paper the direct kinematic model of a multiple
applications three degrees of freedom industrial manipulator, was
developed using the homogeneous transformation matrices and the
Denavit - Hartenberg parameters, likewise the inverse kinematic
model was developed using the same method, verifying that in the
workload border the inverse kinematic presents considerable errors,
therefore a genetic algorithm was implemented to optimize the model
improving greatly the efficiency of the model.