Abstract: This paper presents a fuzzy logic controlled shunt
active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a
simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able
to operate in both balanced and unbalanced load conditions. A fuzzy
logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity
of the presented approach in harmonic mitigation is verified via
simulation results of the proposed test system under different loading
conditions.
Abstract: Brand loyalty is a strategic asset of the company. In
the era of competition to have loyal customers decides on the market
superiority of enterprises. Creating the loyalty of buyers, however, is
a lengthy process and requires the appropriate business strategy,
preceded by the proper market research. The purpose of the paper is
to present the concept of brand loyalty, the creation of loyalty of
customers, the benefits and determinants of loyalty on the example of
brewery market in Poland.
Abstract: Star graphs are Cayley graphs of symmetric groups of permutations, with transpositions as the generating sets. A star graph is a preferred interconnection network topology to a hypercube for its ability to connect a greater number of nodes with lower degree. However, an attractive property of the hypercube is that it has a Hamiltonian decomposition, i.e. its edges can be partitioned into disjoint Hamiltonian cycles, and therefore a simple routing can be found in the case of an edge failure. The existence of Hamiltonian cycles in Cayley graphs has been known for some time. So far, there are no published results on the much stronger condition of the existence of Hamiltonian decompositions. In this paper, we give a construction of a Hamiltonian decomposition of the star graph 5-star of degree 4, by defining an automorphism for 5-star and a Hamiltonian cycle which is edge-disjoint with its image under the automorphism.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: Land degradation is of concern in many countries. People more and more must address the problems associated with the degradation of soil properties due to man. Increasingly, organic soil amendments, such as compost are being examined for their potential use in soil restoration and for preventing soil erosion. In the Czech Republic, compost is the most used to improve soil structure and increase the content of soil organic matter. Land reclamation / restoration is one of the ways to evaluate industrially produced compost because Czech farmers are not willing to use compost as organic fertilizer. The most common use of reclamation substrates in the Czech Republic is for the rehabilitation of landfills and contaminated sites.
This paper deals with the influence of reclamation substrates (RS) with different proportions of compost and sand on selected soil properties–chemical characteristics, nitrogen bioavailability, leaching of mineral nitrogen, respiration activity and plant biomass production. Chemical properties vary proportionally with addition of compost and sand to the control variant (topsoil). The highest differences between the variants were recorded in leaching of mineral nitrogen (varies from 1.36mg dm-3 in C to 9.09mg dm-3). Addition of compost to soil improves conditions for plant growth in comparison with soil alone. However, too high addition of compost may have adverse effects on plant growth. In addition, high proportion of compost increases leaching of mineral N. Therefore, mixture of 70% of soil with 10% of compost and 20% of sand may be recommended as optimal composition of RS.
Abstract: This paper present the implementation of a new ordering strategy on Successive Overrelaxation scheme on two dimensional boundary value problems. The strategy involve two directions alternatingly; from top and bottom of the solution domain. The method shows to significantly reduce the iteration number to converge. Four numerical experiments were carried out to examine the performance of the new strategy.
Abstract: This study aims to identify the current situation and
problems of environmental statement for major four home appliances
(refrigerators, washing machines, air conditioners and television
receivers) sold at online stores in Japan, and then to suggest how to
improve the situation, through a questionnaire survey conducted
among businesses that operate online stores and online malls with
multiple online stores. Results of the study boil down to:
(1) It is found out that environmental statement for the home
appliances at online stores have four problems; (i) less information
on “three Rs" and “chemical substances" than the one on “energy
conservation", (ii) cost for providing environmental statement, (iii)
issues associated with a label and mark placement, and (iv) issues
associated with energy conservation statement.
(2) Improvements are suggested for each of the four problems listed
above, and shown are (i) the effectiveness of, and need to promote, a
label and mark placement, (ii) cost burden on buyers, and (iii) need
of active efforts made by businesses and of dissemination of legal
regulations to businesses.
Abstract: This paper presents an algebraic approach to optimize
queries in domain-specific database management system
for protein structure data. The approach involves the introduction of
several protein structure specific algebraic operators to query the
complex data stored in an object-oriented database system. The
Protein Algebra provides an extensible set of high-level Genomic
Data Types and Protein Data Types along with a comprehensive
collection of appropriate genomic and protein functions. The paper
also presents a query translator that converts high-level query
specifications in algebra into low-level query specifications in
Protein-QL, a query language designed to query protein structure
data. The query transformation process uses a Protein Ontology that
serves the purpose of a dictionary.
Abstract: Heat pipes are used to control the thermal problem for
electronic cooling. It is especially difficult to dissipate heat to a heat
sink in an environment in space compared to earth. For solving this
problem, in this study, the Poiseuille (Po) number, which is the main
measure of the performance of a heat pipe, is studied by CFD; then, the
heat pipe performance is verified with experimental results. A heat
pipe is then fabricated for a spatial environment, and an in-house code
is developed. Further, a heat pipe subsystem, which consists of a heat
pipe, MLI (Multi Layer Insulator), SSM (Second Surface Mirror), and
radiator, is tested and correlated with the TMM (Thermal
Mathematical Model) through a commercial code. The correlation
results satisfy the 3K requirement, and the generated thermal model is
verified for application to a spatial environment.
Abstract: The main aim of this work is to establish the
capabilities of new green buildings to ascertain off-grid electricity
generation based on the integration of wind turbines in the
conceptual model of a rotating tower [2] in Dubai. An in depth
performance analysis of the WinWind 3.0MW [3] wind turbine is
performed. Data based on the Dubai Meteorological Services is
collected and analyzed in conjunction with the performance analysis
of this wind turbine. The mathematical model is compared with
Computational Fluid Dynamics (CFD) results based on a conceptual
rotating tower design model. The comparison results are further
validated and verified for accuracy by conducting experiments on a
scaled prototype of the tower design. The study concluded that
integrating wind turbines inside a rotating tower can generate enough
electricity to meet the required power consumption of the building,
which equates to a wind farm containing 9 horizontal axis wind
turbines located at an approximate area of 3,237,485 m2 [14].
Abstract: This paper describes the design of a real-time audiorange
digital oscilloscope and its implementation in 90nm CMOS
FPGA platform. The design consists of sample and hold circuits,
A/D conversion, audio and video processing, on-chip RAM, clock
generation and control logic. The design of internal blocks and
modules in 90nm devices in an FPGA is elaborated. Also the key
features and their implementation algorithms are presented.
Finally, the timing waveforms and simulation results are put
forward.
Abstract: This paper presents a novel iris recognition system
using 1D log polar Gabor wavelet and Euler numbers. 1D log polar
Gabor wavelet is used to extract the textural features, and Euler
numbers are used to extract topological features of the iris. The
proposed decision strategy uses these features to authenticate an
individual-s identity while maintaining a low false rejection rate. The
algorithm was tested on CASIA iris image database and found to
perform better than existing approaches with an overall accuracy of
99.93%.
Abstract: The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: More and more governments around the world are
introducing e-government as a means of reducing costs, improving
services, saving time and increasing effectiveness and efficiency in
the public sector Therefore e-government has been identified as one
of the top priorities for Saudi government and all its agencies.
However, the adoption of e-government is facing many challenges
and barriers such as technological, cultural, organizational, and social
issues which must be considered and treated carefully by any
government contemplating its adoption. This paper reports on a pilot
study amongst online (e-ready) citizens to identify the challenges and
barriers that affect the adoption of e-government services especially
from their perspective in Saudi society. Based on the analysis of data
collected from an online survey the researcher was able to identify
some of the important barriers and challenges from the e-ready
citizen perspective. As a result, this study has generated a list of
possible strategies to move towards successful adoption of egovernment
services in Saudi Arabia.
Abstract: Cs-type nanocomposite zeolite membrane was successfully synthesized on an alumina ceramic hollow fibre with a mean outer diameter of 1.7 mm; cesium cationic exchange test was carried out inside test module with mean wall thickness of 230 μm and an average crossing pore size smaller than 0.2 μm. Separation factor of n-butane/H2 obtained indicate that a relatively high quality closed to 20. Maxwell-Stefan modeling provides an equivalent thickness lower than 1 µm. To compare the difference an application to CO2/N2 separation has been achieved, reaching separation factors close to (4,18) before and after cation exchange on H-zeolite membrane formed within the pores of a ceramic alumina substrate.
Abstract: In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.
Abstract: This paper presents the averaging model of a buck
converter derived from the generalized state-space averaging method.
The sliding mode control is used to regulate the output voltage of the
converter and taken into account in the model. The proposed model
requires the fast computational time compared with those of the full
topology model. The intensive time-domain simulations via the exact
topology model are used as the comparable model. The results show
that a good agreement between the proposed model and the switching
model is achieved in both transient and steady-state responses. The
reported model is suitable for the optimal controller design by using
the artificial intelligence techniques.
Abstract: Safety instrumented systems (SISs) are becoming
increasingly complex and the proportion of programmable electronic
parts is growing. The IEC 61508 global standard was established to
ensure the functional safety of SISs, but it was expressed in highly
macroscopic terms. This study introduces an evaluation process for
hardware safety integrity levels through failure modes, effects, and
diagnostic analysis (FMEDA).FMEDA is widely used to evaluate
safety levels, and it provides the information on failure rates and
failure mode distributions necessary to calculate a diagnostic coverage
factor for a given component. In our evaluation process, the
components of the SIS subsystem are first defined in terms of failure
modes and effects. Then, the failure rate and failure mechanism
distribution are assigned to each component. The safety mode and
detectability of each failure mode are determined for each component.
Finally, the hardware safety integrity level is evaluated based on the
calculated results.
Abstract: It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.