Abstract: In this paper, delay-dependent stability analysis for
neutral type neural networks with uncertain paramters and
time-varying delay is studied. By constructing new
Lyapunov-Krasovskii functional and dividing the delay interval into
multiple segments, a novel sufficient condition is established to
guarantee the globally asymptotically stability of the considered
system. Finally, a numerical example is provided to illustrate the
usefulness of the proposed main results.
Abstract: Object Relational Databases (ORDB) are complex in
nature than traditional relational databases because they combine the
characteristics of both object oriented concepts and relational
features of conventional databases. Design of an ORDB demands
efficient and quality schema considering the structural, functional
and componential traits. This internal quality of the schema is
assured by metrics that measure the relevant attributes. This is
extended to substantiate the understandability, usability and
reliability of the schema, thus assuring external quality of the
schema. This work institutes a formalization of ORDB metrics;
metric definition, evaluation methodology and the calibration of the
metric. Three ORDB schemas were used to conduct the evaluation
and the formalization of the metrics. The metrics are calibrated using
content and criteria related validity based on the measurability,
consistency and reliability of the metrics. Nominal and summative
scales are derived based on the evaluated metric values and are
standardized. Future works pertaining to ORDB metrics forms the
concluding note.
Abstract: In the present paper, we obtain a sandwich-type theorem.
As applications of our main result, we discuss the univalence
and starlikeness of analytic functions in terms of certain differential
subordinations and differential inequalities.
Abstract: In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.
Abstract: In general the images used for compression are of
different types like dark image, high intensity image etc. When these
images are compressed using Counter Propagation Neural Network,
it takes longer time to converge. The reason for this is that the given
image may contain a number of distinct gray levels with narrow
difference with their neighborhood pixels. If the gray levels of the
pixels in an image and their neighbors are mapped in such a way that
the difference in the gray levels of the neighbor with the pixel is
minimum, then compression ratio as well as the convergence of the
network can be improved. To achieve this, a Cumulative Distribution
Function is estimated for the image and it is used to map the image
pixels. When the mapped image pixels are used the Counter
Propagation Neural Network yield high compression ratio as well as
it converges quickly.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: Decision making preferences to certain criteria
usually focus on positive degrees without considering the negative
degrees. However, in real life situation, evaluation becomes more
comprehensive if negative degrees are considered concurrently.
Preference is expected to be more effective when considering both
positive and negative degrees of preference to evaluate the best
selection. Therefore, the aim of this paper is to propose the
conflicting bifuzzy preference relations in group decision making by
utilization of a novel score function. The conflicting bifuzzy
preference relation is obtained by introducing some modifications on
intuitionistic fuzzy preference relations. Releasing the intuitionistic
condition by taking into account positive and negative degrees
simultaneously and utilizing the novel score function are the main
modifications to establish the proposed preference model. The
proposed model is tested with a numerical example and proved to be
simple and practical. The four-step decision model shows the
efficiency of obtaining preference in group decision making.
Abstract: In this paper, we present the recently implemented approach allowing dynamics systems to plan its actions, taking into account the environment perception changes, and to control their execution when uncertainty and incomplete knowledge are the major characteristics of the situated environment [1],[2],[3],[4]. The control distributed architecture has three modules and the approach is related to hierarchical planning: the plan produced by the planner is further refined at the control layer that in turn supervises its execution by a functional level. We propose a new intelligent distributed architecture constituted by: Multi-Agent subsystem of the sensor, of the interpretation and representation of environment [9], of the dynamic localization and of the action. We tested this distributed architecture with dynamic system in the known environment. The autonomous for Rotor Mini Rotorcraft task is described by the primitive actions. The distributed controlbased on multi-agent system is in charge of achieving each task in the best possible way taking into account the context and sensory feedback.
Abstract: European Rail Traffic Management System (ERTMS) is the European reference for interoperable and safer signaling systems to efficiently manage trains running. If implemented, it allows trains cross seamlessly intra-European national borders. ERTMS has defined a secure communication protocol, EURORADIO, based on open communication networks. Its RadioInfill function can improve the reaction of the signaling system to changes in line conditions, avoiding unnecessary braking: its advantages in terms of power saving and travel time has been analyzed. In this paper a software implementation of the EURORADIO protocol with RadioInfill for ERTMS Level 1 using GSM-R is illustrated as part of the SR-Secure Italian project. In this building-blocks architecture the EURORADIO layers communicates together through modular Application Programm Interfaces. Security coding rules and railway industry requirements specified by EN 50128 standard have been respected. The proposed implementation has successfully passed conformity tests and has been tested on a computer-based simulator.
Abstract: Recently, Genetic Algorithms (GA) and Differential
Evolution (DE) algorithm technique have attracted considerable
attention among various modern heuristic optimization techniques.
Since the two approaches are supposed to find a solution to a given
objective function but employ different strategies and computational
effort, it is appropriate to compare their performance. This paper
presents the application and performance comparison of DE and GA
optimization techniques, for flexible ac transmission system
(FACTS)-based controller design. The design objective is to enhance
the power system stability. The design problem of the FACTS-based
controller is formulated as an optimization problem and both the PSO
and GA optimization techniques are employed to search for optimal
controller parameters. The performance of both optimization
techniques has been compared. Further, the optimized controllers are
tested on a weekly connected power system subjected to different
disturbances, and their performance is compared with the
conventional power system stabilizer (CPSS). The eigenvalue
analysis and non-linear simulation results are presented and
compared to show the effectiveness of both the techniques in
designing a FACTS-based controller, to enhance power system
stability.
Abstract: As the development of digital technology is increasing,
Digital cinema is getting more spread.
However, content copy and attack against the digital cinema becomes
a serious problem. To solve the above security problem, we propose
“Additional Watermarking" for digital cinema delivery system. With
this proposed “Additional watermarking" method, we protect content
copyrights at encoder and user side information at decoder. It realizes
the traceability of the watermark embedded at encoder.
The watermark is embedded into the random-selected frames using
Hash function. Using it, the embedding position is distributed by Hash
Function so that third parties do not break off the watermarking
algorithm.
Finally, our experimental results show that proposed method is much
better than the convenient watermarking techniques in terms of
robustness, image quality and its simple but unbreakable algorithm.
Abstract: The H.264/AVC standard uses an intra prediction, 9
directional modes for 4x4 luma blocks and 8x8 luma blocks, 4
directional modes for 16x16 macroblock and 8x8 chroma blocks,
respectively. It means that, for a macroblock, it has to perform 736
different RDO calculation before a best RDO modes is determined.
With this Multiple intra-mode prediction, intra coding of H.264/AVC
offers a considerably higher improvement in coding efficiency
compared to other compression standards, but computational
complexity is increased significantly. This paper presents a fast intra
prediction algorithm for H.264/AVC intra prediction based a
characteristic of homogeneity information. In this study, the gradient
prediction method used to predict the homogeneous area and the
quadratic prediction function used to predict the nonhomogeneous
area. Based on the correlation between the homogeneity and block
size, the smaller block is predicted by gradient prediction and
quadratic prediction, so the bigger block is predicted by gradient
prediction. Experimental results are presented to show that the
proposed method reduce the complexity by up to 76.07%
maintaining the similar PSNR quality with about 1.94%bit rate
increase in average.
Abstract: The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.
Abstract: Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.
Abstract: F-actin fibrils are the cytoskeleton of osteocytes. They react in a dynamic manner to mechanical loading, and strength and
reposition their efforts to reinforce the cells structure. We hypothesize that f-actin is temporarly disrupted after loading and repolymerizes
in a new orientation to oppose the applied load. In vitro studies are conducted to determine f-actin disruption after varying mechanical stimulus parameters that are known to affect bone
formation. Results indicate that the f-actin cytoskeleton is disrupted in vitro as a function of applied mechanical stimulus parameters and
that the f-actin bundles reassemble after loading induced disruption
within 3 minutes after cessation of loading. The disruption of the factin
cytoskeleton depends on the magnitude of stretch, the numbers
of loading cycles, frequency, the insertion of rest between loading
cycles and extracellular calcium. In vivo studies also demonstrate
disruption of the f-actin cytoskeleton in cells embedded in the bone
matrix immediately after mechanical loading. These studies suggest
that adaptation of the f-actin fiber bundles of the cytoskeleton in
response to applied loads occurs by disruption and subsequent repolymerization.
Abstract: A self-evolution algorithm for optimizing neural networks using a combination of PSO and JPSO is proposed. The algorithm optimizes both the network topology and parameters simultaneously with the aim of achieving desired accuracy with less complicated networks. The performance of the proposed approach is compared with conventional back-propagation networks using several synthetic functions, with better results in the case of the former. The proposed algorithm is also implemented on slope stability problem to estimate the critical factor of safety. Based on the results obtained, the proposed self evolving network produced a better estimate of critical safety factor in comparison to conventional BPN network.
Abstract: In this paper, a two factor scheme is proposed to
generate cryptographic keys directly from biometric data, which
unlike passwords, are strongly bound to the user. Hash value of the
reference iris code is used as a cryptographic key and its length
depends only on the hash function, being independent of any other
parameter. The entropy of such keys is 94 bits, which is much higher
than any other comparable system. The most important and distinct
feature of this scheme is that it regenerates the reference iris code by
providing a genuine iris sample and the correct user password. Since
iris codes obtained from two images of the same eye are not exactly
the same, error correcting codes (Hadamard code and Reed-Solomon
code) are used to deal with the variability. The scheme proposed here
can be used to provide keys for a cryptographic system and/or for
user authentication. The performance of this system is evaluated on
two publicly available databases for iris biometrics namely CBS and
ICE databases. The operating point of the system (values of False
Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set
by properly selecting the error correction capacity (ts) of the Reed-
Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096%
and FRR is 0.76%.
Abstract: In this paper, we consider the design of pulse shaping
filter using orthogonal Hermite-Rodriguez basis functions. The pulse
shaping filter design problem has been formulated and solved as a
quadratic programming problem with linear inequality constraints.
Compared with the existing approaches reported in the literature, the
use of Hermite-Rodriguez functions offers an effective alternative to
solve the constrained filter synthesis problem. This is demonstrated
through a numerical example which is concerned with the design of
an equalization filter for a digital transmission channel.
Abstract: This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
Abstract: Optimization of extraction of phenolic compounds
from Avicennia marina using response surface methodology was
carried out during the present study. Five levels, three factors
rotatable design (CCRD) was utilized to examine the optimum
combination of extraction variables based on the TPC of Avicennia
marina leaves. The best combination of response function was 78.41
°C, drying temperature; 26.18°C; extraction temperature and 36.53
minutes of extraction time. However, the procedure can be promptly
extended to the study of several others pharmaceutical processes like
purification of bioactive substances, drying of extracts and
development of the pharmaceutical dosage forms for the benefit of
consumers.