Abstract: In this paper, the issue of pth moment stability of a class of stochastic neural networks with mixed delays is investigated. By establishing two integro-differential inequalities, some new sufficient conditions ensuring pth moment exponential stability are obtained. Compared with some previous publications, our results generalize some earlier works reported in the literature, and remove some strict constraints of time delays and kernel functions. Two numerical examples are presented to illustrate the validity of the main results.
Abstract: Modular fixtures (MFs) are very important tools in
manufacturing processes in terms of reduction the cost and the
production time. This paper introduces an automated approach for
assembling MFs elements by employing SolidWorks as a powerful
3D CAD software. Visual Basic (VB) programming language was
applied integrating with SolidWorks API (Application programming
interface) functions. This integration allowed creating plug-in file and
generating new menus in the SolidWorks environment. The menus
allow the user to select, insert, and assemble MFs elements.
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: In the context of computer numerical control (CNC) and computer aided manufacturing (CAM), the capabilities of programming languages such as symbolic and intuitive programming, program portability and geometrical portfolio have special importance. They allow to save time and to avoid errors during part programming and permit code re-usage. Our updated literature review indicates that the current state of art presents voids in parametric programming, program portability and programming flexibility. In response to this situation, this article presents a compiler implementation for EGCL (Extended G-code Language), a new, enriched CNC programming language which allows the use of descriptive variable names, geometrical functions and flow-control statements (if-then-else, while). Our compiler produces low-level generic, elementary ISO-compliant Gcode, thus allowing for flexibility in the choice of the executing CNC machine and in portability. Our results show that readable variable names and flow control statements allow a simplified and intuitive part programming and permit re-usage of the programs. Future work includes allowing the programmer to define own functions in terms of EGCL, in contrast to the current status of having them as library built-in functions.
Abstract: We show that Chebyshev Polynomials are a practical representation of computable functions on the computable reals. The paper presents error estimates for common operations and demonstrates that Chebyshev Polynomial methods would be more efficient than Taylor Series methods for evaluation of transcendental functions.
Abstract: In this paper, a neural network tuned fuzzy controller
is proposed for controlling Multi-Input Multi-Output (MIMO)
systems. For the convenience of analysis, the structure of MIMO
fuzzy controller is divided into single input single-output (SISO)
controllers for controlling each degree of freedom. Secondly,
according to the characteristics of the system-s dynamics coupling, an
appropriate coupling fuzzy controller is incorporated to improve the
performance. The simulation analysis on a two-level mass–spring
MIMO vibration system is carried out and results show the
effectiveness of the proposed fuzzy controller. The performance
though improved, the computational time and memory used is
comparatively higher, because it has four fuzzy reasoning blocks and
number may increase in case of other MIMO system. Then a fuzzy
neural network is designed from a set of input-output training data to
reduce the computing burden during implementation. This control
strategy can not only simplify the implementation problem of fuzzy
control, but also reduce computational time and consume less
memory.
Abstract: A stiffened laminated composite panel (1 m length ×
0.5m width) was optimized for minimum weight and deflection under
several constraints using genetic algorithm. Here, a significant study
on the performance of a penalty function with two kinds of static and
dynamic penalty factors was conducted. The results have shown that
linear dynamic penalty factors are more effective than the static ones.
Also, a specially combined linear-exponential function has shown to
perform more effective than the previously mentioned penalty
functions. This was then resulted in the less sensitivity of the GA to
the amount of penalty factor.
Abstract: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: In this paper, a new hybrid of genetic algorithm (GA)
and simulated annealing (SA), referred to as GSA, is presented. In
this algorithm, SA is incorporated into GA to escape from local
optima. The concept of hierarchical parallel GA is employed to
parallelize GSA for the optimization of multimodal functions. In
addition, multi-niche crowding is used to maintain the diversity in
the population of the parallel GSA (PGSA). The performance of the
proposed algorithms is evaluated against a standard set of multimodal
benchmark functions. The multi-niche crowding PGSA and normal
PGSA show some remarkable improvement in comparison with the
conventional parallel genetic algorithm and the breeder genetic
algorithm (BGA).
Abstract: In this paper, the decomposition-aggregation method
is used to carry out connective stability criteria for general linear
composite system via aggregation. The large scale system is
decomposed into a number of subsystems. By associating directed
graphs with dynamic systems in an essential way, we define the
relation between system structure and stability in the sense of
Lyapunov. The stability criteria is then associated with the stability
and system matrices of subsystems as well as those interconnected
terms among subsystems using the concepts of vector differential
inequalities and vector Lyapunov functions. Then, we show that the
stability of each subsystem and stability of the aggregate model
imply connective stability of the overall system. An example is
reported, showing the efficiency of the proposed technique.
Abstract: The main objective of this paper is applying a
comparison between the Wolf Pack Search (WPS) as a newly
introduced intelligent algorithm with several other known algorithms
including Particle Swarm Optimization (PSO), Shuffled Frog
Leaping (SFL), Binary and Continues Genetic algorithms. All
algorithms are applied on two benchmark cost functions. The aim is
to identify the best algorithm in terms of more speed and accuracy in
finding the solution, where speed is measured in terms of function
evaluations. The simulation results show that the SFL algorithm with
less function evaluations becomes first if the simulation time is
important, while if accuracy is the significant issue, WPS and PSO
would have a better performance.
Abstract: Infrared communication in the wavelength band 780-
950 nm is very suitable for short-range point-to-point communications.
It is a good choice for vehicle-to-vehicle communication in several
intelligent-transportation-system (ITS) applications such as cooperative
driving, collision warning, and pileup-crash prevention. In this
paper, with the aid of a physical model established in our previous
works, we explore the communication area of an infrared intervehicle
communication system utilizing a typical low-cost cormmercial lightemitting
diodes (LEDs) as the emitter and planar p-i-n photodiodes
as the receiver. The radiation pattern of the emitter fabricated by
aforementioned LEDs and the receiving pattern of the receiver are
approximated by a linear combination of cosinen functions. This
approximation helps us analyze the system performance easily. Both
multilane straight-road conditions and curved-road conditions with
various radius of curvature are taken into account. The condition of
a small car communicating with a big truck, i.e., there is a vertical
mounting height difference between the emitter and the receiver, is
also considered. Our results show that the performance of the system
meets the requirement of aforementioned ITS applications in terms
of the communication area.
Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: Proteins levels produced by bacteria may be increased
in stressful surroundings, such as in the presence of antibiotics. It
appears that many antimicrobial agents or antibiotics, when used at
low concentrations, have in common the ability to activate or repress
gene transcription, which is distinct from their inhibitory effect.
There have been comparatively few studies on the potential of
antibiotics or natural compounds in nature as a specific chemical
signal that can trigger a variety of biological functions. Therefore,
this study was focusing on the effect of essential oils from
Cymbopogon flexuosus and C. nardus in regulating proteins
production by Bacillus subtilis ATCC 21332. The Minimum
Inhibition Concentrations (MICs) of both essential oils on B. subtilis
were determined by using microdilution assay, resulting 0.2% and
1.56% for each C. flexuosus and C. nardus subsequently. The
bacteria were further exposed to each essential oils at concentration
of 0.01XMIC for 2 days. The proteins were then isolated and
analyzed by sodium dodecyl sulfate polyacrylamide gel
electrophoresis (SDS-PAGE). Protein profile showed that a band
with approximate size of 250 kD was appeared for the treated
bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in
stressful condition with the presence of essential oils at low
concentration could induce the protein production.
Abstract: The Linear discriminant analysis (LDA) can be
generalized into a nonlinear form - kernel LDA (KLDA) expediently
by using the kernel functions. But KLDA is often referred to a general
eigenvalue problem in singular case. To avoid this complication, this
paper proposes an iterative algorithm for the two-class KLDA. The
proposed KLDA is used as a nonlinear discriminant classifier, and the
experiments show that it has a comparable performance with SVM.
Abstract: This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.
Abstract: In the normal operation conditions of a pico satellite,
conventional Unscented Kalman Filter (UKF) gives sufficiently good
estimation results. However, if the measurements are not reliable
because of any kind of malfunction in the estimation system, UKF
gives inaccurate results and diverges by time. This study, introduces
Robust Unscented Kalman Filter (RUKF) algorithms with the filter
gain correction for the case of measurement malfunctions. By the use
of defined variables named as measurement noise scale factor, the
faulty measurements are taken into the consideration with a small
weight and the estimations are corrected without affecting the
characteristic of the accurate ones. Two different RUKF algorithms,
one with single scale factor and one with multiple scale factors, are
proposed and applied for the attitude estimation process of a pico
satellite. The results of these algorithms are compared for different
types of measurement faults in different estimation scenarios and
recommendations about their applications are given.
Abstract: This paper presents nonlinear elastic dynamic analysis
of 3-D semi-rigid steel frames including geometric and connection
nonlinearities. The geometric nonlinearity is considered by using
stability functions and updating geometric stiffness matrix. The
nonlinear behavior of the steel beam-to-column connection is
considered by using a zero-length independent connection element
comprising of six translational and rotational springs. The nonlinear
dynamic equilibrium equations are solved by the Newmark numerical
integration method. The nonlinear time-history analysis results are
compared with those of previous studies and commercial SAP2000
software to verify the accuracy and efficiency of the proposed
procedure.
Abstract: With the advent of digital cinema and digital
broadcasting, copyright protection of video data has been one of the
most important issues.
We present a novel method of watermarking for video image data
based on the hardware and digital wavelet transform techniques and
name it as “traceable watermarking" because the watermarked data is
constructed before the transmission process and traced after it has been
received by an authorized user.
In our method, we embed the watermark to the lowest part of each
image frame in decoded video by using a hardware LSI.
Digital Cinema is an important application for traceable
watermarking since digital cinema system makes use of watermarking
technology during content encoding, encryption, transmission,
decoding and all the intermediate process to be done in digital cinema
systems. The watermark is embedded into the randomly selected
movie frames using hash functions.
Embedded watermark information can be extracted from the
decoded video data. For that, there is no need to access original movie
data. Our experimental results show that proposed traceable
watermarking method for digital cinema system is much better than the
convenient watermarking techniques in terms of robustness, image
quality, speed, simplicity and robust structure.
Abstract: The optimization problem using time scales is studied.
Time scale is a model of time. The language of time scales seems to
be an ideal tool to unify the continuous-time and the discrete-time
theories. In this work we present necessary conditions for a solution
of an optimization problem on time scales. To obtain that result we
use properties and results of the partial diamond-alpha derivatives for
continuous-multivariable functions. These results are also presented
here.