Abstract: The Shortest Approximate Common Superstring
(SACS) problem is : Given a set of strings f={w1, w2, ... , wn},
where no wi is an approximate substring of wj, i ≠ j, find a shortest
string Sa, such that, every string of f is an approximate substring of
Sa. When the number of the strings n>2, the SACS problem becomes
NP-complete. In this paper, we present a greedy approximation
SACS algorithm. Our algorithm is a 1/2-approximation for the SACS
problem. It is of complexity O(n2*(l2+log(n))) in computing time,
where n is the number of the strings and l is the length of a string.
Our SACS algorithm is based on computation of the Length of the
Approximate Longest Overlap (LALO).
Abstract: Cooling with sound is a physical phenomenon allowed by Thermo-Acoustics in which acoustic energy is transformed into a negative heat transfer, in other words: into cooling! Without needing any harmful gas, the transformation is environmentally friendly and can respond to many needs in terms of air conditioning, food refrigeration for domestic use, and cooling medical samples for example. To explore the possibilities of this cooling solution on a small scale, the TACS prototype has been designed, consisting of a low cost thermoacoustic refrigerant “pipe” able to lower the temperature by a few degrees. The obtained results are providing an interesting element for possible future of thermo-acoustic refrigeration.
Abstract: In this paper, the Fuzzy Autocatalytic Set (FACS) is
composed into Omega Algebra by embedding the membership value
of fuzzy edge connectivity using the property of transitive affinity.
Then, the Omega Algebra of FACS is a transformation semigroup
which is a special class of semigroup is shown.
Abstract: In this paper a novel, simple and reliable digital firing
scheme has been implemented for speed control of three-phase
induction motor using ac voltage controller. The system consists of
three-phase supply connected to the three-phase induction motor via
three triacs and its control circuit. The ac voltage controller has three
modes of operation depending on the shape of supply current. The
performance of the induction motor differs in each mode where the
speed is directly proportional with firing angle in two modes and
inversely in the third one. So, the control system has to detect the
current mode of operation to choose the correct firing angle of triacs.
Three sensors are used to feed the line currents to control system to
detect the mode of operation. The control strategy is implemented
using a low cost Xilinx Spartan-3E field programmable gate array
(FPGA) device. Three PI-controllers are designed on FPGA to
control the system in the three-modes. Simulation of the system is
carried out using PSIM computer program. The simulation results
show stable operation for different loading conditions especially in
mode 2/3. The simulation results have been compared with the
experimental results from laboratory prototype.
Abstract: Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.
Abstract: The presented work is motivated by a french law regarding nuclear waste management. In order to avoid the limitation coming with the usage of the existing scenario codes, as COSI, VISION or FAMILY, the Core Library for Advance Scenario Simulation (CLASS) is being develop. CLASS is an open source tool, which allows any user to simulate an electronuclear scenario. The main CLASS asset, is the possibility to include any type of reactor, even a complitely new concept, through the generation of its ACSII evolution database. In the present article, the CLASS working basis will be presented as well as a simple exemple in order to show his potentiel. In the considered exemple, the effect of the transmutation will be assessed on Minor Actinide Inventory produced by PWR reactors.
Abstract: The Minimum Vertex Cover (MVC) problem is a classic
graph optimization NP - complete problem. In this paper a competent
algorithm, called Vertex Support Algorithm (VSA), is designed to
find the smallest vertex cover of a graph. The VSA is tested on a
large number of random graphs and DIMACS benchmark graphs.
Comparative study of this algorithm with the other existing methods
has been carried out. Extensive simulation results show that the VSA
can yield better solutions than other existing algorithms found in the
literature for solving the minimum vertex cover problem.
Abstract: Content-Based Image Retrieval (CBIR) has been
one on the most vivid research areas in the field of computer vision
over the last 10 years. Many programs and tools have been
developed to formulate and execute queries based on the visual or
audio content and to help browsing large multimedia repositories.
Still, no general breakthrough has been achieved with respect to
large varied databases with documents of difering sorts and with
varying characteristics. Answers to many questions with respect to
speed, semantic descriptors or objective image interpretations are
still unanswered. In the medical field, images, and especially
digital images, are produced in ever increasing quantities and used
for diagnostics and therapy. In several articles, content based
access to medical images for supporting clinical decision making
has been proposed that would ease the management of clinical data
and scenarios for the integration of content-based access methods
into Picture Archiving and Communication Systems (PACS) have
been created. This paper gives an overview of soft computing
techniques. New research directions are being defined that can
prove to be useful. Still, there are very few systems that seem to be
used in clinical practice. It needs to be stated as well that the goal
is not, in general, to replace text based retrieval methods as they
exist at the moment.
Abstract: This work describes a CACSD tool for automatic design of robust controllers for hydraulic turbines. The tool calculates the optimal controller using the MATLAB hinfopt function and it
serves as a practical and effective solution for the laborious task of
designing a different controller for each type of turbine and generator, and different parameters and conditions of the plant. Results of the simulation of a generating unit subject to parameters
variation show the accuracy and efficiency of the obtained robust
controllers.
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.
Abstract: This paper presents how the real-time chatter
prevention can be realized by feedback of acoustic cutting signal, and
the efficacy of the proposed adaptive spindle speed tuning algorithm is
verified by intensive experimental simulations. A pair of
microphones, perpendicular to each other, is used to acquire the
acoustic cutting signal resulting from milling chatter. A real-time
feedback control loop is constructed for spindle speed compensation
so that the milling process can be ensured to be within the stability
zone of stability lobe diagram. Acoustic Chatter Signal Index (ACSI)
and Spindle Speed Compensation Strategy (SSCS) are proposed to
quantify the acoustic signal and actively tune the spindle speed
respectively. By converting the acoustic feedback signal into ACSI,
an appropriate Spindle Speed Compensation Rate (SSCR) can be
determined by SSCS based on real-time chatter level or ACSI.
Accordingly, the compensation command, referred to as Added-On
Voltage (AOV), is applied to increase/decrease the spindle motor
speed. By inspection on the precision and quality of the workpiece
surface after milling, the efficacy of the real-time chatter prevention
strategy via acoustic signal feedback is further assured.
Abstract: In this study, the effects of machining parameters on
specific energy during surface grinding of 6061Al-SiC35P
composites are investigated. Vol% of SiC, feed and depth of cut were
chosen as process variables. The power needed for the calculation of
the specific energy is measured from the two watt meter method.
Experiments are conducted using standard RSM design called Central
composite design (CCD). A second order response surface model was
developed for specific energy. The results identify the significant
influence factors to minimize the specific energy. The confirmation
results demonstrate the practicability and effectiveness of the
proposed approach.
Abstract: The sensitivity of UAVs to the atmospheric effects are
apparent. All the same the meteorological support for the UAVs
missions is often non-adequate or partly missing.
In our paper we show a new complex meteorological support
system for different types of UAVs pilots, specialists and decision
makers, too. The mentioned system has two important parts with
different forecasts approach such as the statistical and dynamical
ones.
The statistical prediction approach is based on a large
climatological data base and the special analog method which is able
to select similar weather situations from the mentioned data base to
apply them during the forecasting procedure.
The applied dynamic approach uses the specific WRF model runs
twice a day and produces 96 hours, high resolution weather forecast
for the UAV users over the Hungary. An easy to use web-based
system can give important weather information over the Carpathian
basin in Central-Europe. The mentioned products can be reached via
internet connection.
Abstract: The paper investigates the feasibility of constructing a software multi-agent based monitoring and classification system and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. The agents function autonomously to provide continuous and periodic monitoring of excels spreadsheet workbooks. Resulting in, the development of the MultiAgent classification System (MACS) that is in compliance with the specifications of the Foundation for Intelligent Physical Agents (FIPA). However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies that are Windows Communication Foundation (WCF) services, Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW that is in order to satisfy the monitoring and classification of the multiple developer aspect. ODM was used to automate the classification phase of MACS.
Abstract: Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.
Abstract: An optical fault monitoring in FTTH-PON using ACS
is demonstrated. This device can achieve real-time fault monitoring
for protection feeder fiber. In addition, the ACS can distinguish
optical fiber fault from the transmission services to other customers
in the FTTH-PON. It is essential to use a wavelength different from
the triple-play services operating wavelengths for failure detection.
ACS is using the operating wavelength 1625 nm for monitoring and
failure detection control. Our solution works on a standard local area
network (LAN) using a specially designed hardware interfaced with a
microcontroller integrated Ethernet.
Abstract: An edge based local search algorithm, called ELS, is proposed for the maximum clique problem (MCP), a well-known combinatorial optimization problem. ELS is a two phased local search method effectively £nds the near optimal solutions for the MCP. A parameter ’support’ of vertices de£ned in the ELS greatly reduces the more number of random selections among vertices and also the number of iterations and running times. Computational results on BHOSLIB and DIMACS benchmark graphs indicate that ELS is capable of achieving state-of-the-art-performance for the maximum clique with reasonable average running times.
Abstract: IEEE 802.11e is the enhanced version of the IEEE
802.11 MAC dedicated to provide Quality of Service of wireless
network. It supports QoS by the service differentiation and
prioritization mechanism. Data traffic receives different priority
based on QoS requirements. Fundamentally, applications are divided
into four Access Categories (AC). Each AC has its own buffer queue
and behaves as an independent backoff entity. Every frame with a
specific priority of data traffic is assigned to one of these access
categories. IEEE 802.11e EDCA (Enhanced Distributed Channel
Access) is designed to enhance the IEEE 802.11 DCF (Distributed
Coordination Function) mechanisms by providing a distributed
access method that can support service differentiation among
different classes of traffic. Performance of IEEE 802.11e MAC layer
with different ACs is evaluated to understand the actual benefits
deriving from the MAC enhancements.
Abstract: This paper study the segmented split capacitor
Digital-to-Analog Converter (DAC) implemented in a differentialtype
12-bit Successive Approximation Analog-to-Digital Converter
(SA-ADC). The series capacitance split array method employed as it
reduced the total area of the capacitors required for high resolution
DACs. A 12-bit regular binary array structure requires 2049 unit
capacitors (Cs) while the split array needs 127 unit Cs. These results
in the reduction of the total capacitance and power consumption of
the series split array architectures as to regular binary-weighted
structures. The paper will show the 12-bit DAC series split capacitor
with 4-bit thermometer coded DAC architectures as well as the
simulation and measured results.
Abstract: This paper aims to develop a model that assists the
international retailer in selecting the country that maximizes the
degree of fit between the retailer-s goals and the country
characteristics in his initial internationalization move. A two-stage
multi criteria decision model is designed integrating the Analytic
Hierarchy Process (AHP) and Goal Programming. Ethical, cultural,
geographic and economic proximity are identified as the relevant
constructs of the internationalization decision. The constructs are
further structured into sub-factors within analytic hierarchy. The
model helps the retailer to integrate, rank and weigh a number of
hard and soft factors and prioritize the countries accordingly. The
model has been implemented on a Turkish luxury goods retailer who
was planning to internationalize. Actual entry of the specific retailer
in the selected country is a support for the model. Implementation on
a single retailer limits the generalizability of the results; however, the
emphasis of the paper is on construct identification and model
development. The paper enriches the existing literature by proposing
a hybrid multi objective decision model which introduces new soft
dimensions i.e. perceived distance, ethical proximity, humane
orientation to the decision process and facilitates effective decision
making.