Abstract: In this paper, the issue of pth moment exponential stability of stochastic recurrent neural network with distributed time delays is investigated. By using the method of variation parameters, inequality techniques, and stochastic analysis, some sufficient conditions ensuring pth moment exponential stability are obtained. The method used in this paper does not resort to any Lyapunov function, and the results derived in this paper generalize some earlier criteria reported in the literature. One numerical example is given to illustrate the main results.
Abstract: Many environment specific methods and systems for Robot Navigation exist. However vast strides in the evolution of navigation technologies and system techniques create the need for a general unified framework that is scalable, modular and dynamic. In this paper a Unified Framework for a Robust Conflict-free Robot Navigation System that can be used for either a structured or unstructured and indoor or outdoor environments has been proposed. The fundamental design aspects and implementation issues encountered during the development of the module are discussed. The results of the deployment of three major peripheral modules of the framework namely the GSM based communication module, GIS Module and GPS module are reported in this paper.
Abstract: In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.
Abstract: In this work, we are interested in developing a speech denoising tool by using a discrete wavelet packet transform (DWPT). This speech denoising tool will be employed for applications of recognition, coding and synthesis. For noise reduction, instead of applying the classical thresholding technique, some wavelet packet nodes are set to zero and the others are thresholded. To estimate the non stationary noise level, we employ the spectral entropy. A comparison of our proposed technique to classical denoising methods based on thresholding and spectral subtraction is made in order to evaluate our approach. The experimental implementation uses speech signals corrupted by two sorts of noise, white and Volvo noises. The obtained results from listening tests show that our proposed technique is better than spectral subtraction. The obtained results from SNR computation show the superiority of our technique when compared to the classical thresholding method using the modified hard thresholding function based on u-law algorithm.
Abstract: It is important problems to increase the detection rates
and reduce false positive rates in Intrusion Detection System (IDS).
Although preventative techniques such as access control and
authentication attempt to prevent intruders, these can fail, and as a
second line of defence, intrusion detection has been introduced. Rare
events are events that occur very infrequently, detection of rare
events is a common problem in many domains. In this paper we
propose an intrusion detection method that combines Rough set and
Fuzzy Clustering. Rough set has to decrease the amount of data and
get rid of redundancy. Fuzzy c-means clustering allow objects to
belong to several clusters simultaneously, with different degrees of
membership. Our approach allows us to recognize not only known
attacks but also to detect suspicious activity that may be the result of
a new, unknown attack. The experimental results on Knowledge
Discovery and Data Mining-(KDDCup 1999) Dataset show that the
method is efficient and practical for intrusion detection systems.
Abstract: Modular multiplication is the basic operation
in most public key cryptosystems, such as RSA, DSA, ECC,
and DH key exchange. Unfortunately, very large operands
(in order of 1024 or 2048 bits) must be used to provide
sufficient security strength. The use of such big numbers
dramatically slows down the whole cipher system, especially
when running on embedded processors.
So far, customized hardware accelerators - developed on
FPGAs or ASICs - were the best choice for accelerating
modular multiplication in embedded environments. On the
other hand, many algorithms have been developed to speed
up such operations. Examples are the Montgomery modular
multiplication and the interleaved modular multiplication
algorithms. Combining both customized hardware with
an efficient algorithm is expected to provide a much faster
cipher system.
This paper introduces an enhanced architecture for computing
the modular multiplication of two large numbers X
and Y modulo a given modulus M. The proposed design is
compared with three previous architectures depending on
carry save adders and look up tables. Look up tables should
be loaded with a set of pre-computed values. Our proposed
architecture uses the same carry save addition, but replaces
both look up tables and pre-computations with an enhanced
version of sign detection techniques. The proposed architecture
supports higher frequencies than other architectures.
It also has a better overall absolute time for a single operation.
Abstract: The behavior of Radial Basis Function (RBF) Networks greatly depends on how the center points of the basis functions are selected. In this work we investigate the use of instance reduction techniques, originally developed to reduce the storage requirements of instance based learners, for this purpose. Five Instance-Based Reduction Techniques were used to determine the set of center points, and RBF networks were trained using these sets of centers. The performance of the RBF networks is studied in terms of classification accuracy and training time. The results obtained were compared with two Radial Basis Function Networks: RBF networks that use all instances of the training set as center points (RBF-ALL) and Probabilistic Neural Networks (PNN). The former achieves high classification accuracies and the latter requires smaller training time. Results showed that RBF networks trained using sets of centers located by noise-filtering techniques (ALLKNN and ENN) rather than pure reduction techniques produce the best results in terms of classification accuracy. The results show that these networks require smaller training time than that of RBF-ALL and higher classification accuracy than that of PNN. Thus, using ALLKNN and ENN to select center points gives better combination of classification accuracy and training time. Our experiments also show that using the reduced sets to train the networks is beneficial especially in the presence of noise in the original training sets.
Abstract: Herein, the organic semiconductor methyl orange
(MO), is investigated for the first time for its electronic applications.
For this purpose, Al/MO/n-Si heterojunction is fabricated through
economical cheap and simple “drop casting” technique. The currentvoltage
(I-V) measurements of the device are made at room
temperature under dark conditions. The I-V characteristics of
Al/MO/n-Si junction exhibits asymmetrical and rectifying behavior
that confirms the formation of diode. The diode parameters such as
rectification ratio (RR), turn on voltage (Vturn on), reverse saturation
current (I0), ideality factor (n), barrier height ( b
f ), series resistance
(Rs) and shunt resistance (Rsh) are determined from I-V curves using
Schottky equations. These values of these parameters are also
extracted and verified by applying Cheung’s functions. The
conduction mechanisms are explained from the forward bias I-V
characteristics using the power law.
Abstract: A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil might also be used as a foodstuff due to its significant nutrition content. The limitations for utilizing the oil as a foodstuff are mainly due to a toxicity of PE. Currently, a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence.
Ozone is considered as a strong oxidative agent. It reacts with PE by attacking the carbon-carbon double bond of PE. This modification of PE molecular structure yields a non toxic ester with high lipid content.
This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is an application for a new microscale plasma unit to ozone production and the technology permits ozone injection to the water-TPA mixture in form of microbubbles.
The efficacy of a heterogeneous process depends on the diffusion coefficient which can be controlled by contact time and interfacial area. The low velocity of rising microbubbles and high surface to volume ratio allow efficient mass transfer to be achieved during the process. Direct injection of ozone is the most efficient way to process with such highly reactive and short lived chemical.
Data on the plasma unit behavior are presented and the influence of gas oscillation technology on the microbubble production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.
Abstract: This paper compares the heuristic Global Search
Techniques; Genetic Algorithm, Particle Swarm Optimization,
Simulated Annealing, Generalized Pattern Search, genetic algorithm
hybridized with Nelder–Mead and Generalized pattern search
technique for tuning of fuzzy PID controller for Puma 560. Since the
actual control is in joint space ,inverse kinematics is used to generate
various joint angles correspoding to desired cartesian space
trajectory. Efficient dynamics and kinematics are modeled on Matlab
which takes very less simulation time. Performances of all the tuning
methods with and without disturbance are compared in terms of ITSE
in joint space and ISE in cartesian space for spiral trajectory tracking.
Genetic Algorithm hybridized with Generalized Pattern Search is
showing best performance.
Abstract: Business rules are widely used within the services
sector. They provide consistency and allow relatively unskilled staff
to process complex transactions correctly. But there are many
examples where the rules themselves have an impact on the costs and
profits of an organisation. Financial services, transport and human
services are areas where the rules themselves can impact the bottom
line in a predictable way. If this is the case, how can we find that set
of rules that maximise profit, performance or customer service, or
any other key performance indicators? The manufacturing, energy
and process industries have embraced mathematical optimisation
techniques to improve efficiency, increase production and so on. This
paper explores several real world (but simplified) problems in the
services sector and shows how business rules can be optimised. It
also examines the similarities and differences between the service
and other sectors, and how optimisation techniques could be used to
deliver similar benefits.
Abstract: The study will search the level of existence of the
sweethearting in Saudi Arabia's Supermarkets in Riyadh.
Sweethearting occurs when frontline workers give unauthorized free
or uncounted goods and services to customer-s conspirators. The
store managers and /or security managers were asked about the
sweethearting that occurs in the supermarkets. The characteristics of
sweethearting in Riyadh stores were investigated. Two independent
variables were related to the report of sweethearting. These
independent variables are: The effect of store environment on
sweethearting and the security techniques and loss prevention
electronics techniques used. This study expected to shed the light
about the level of sweethearting in Saudi Arabia and the factors
behind it. This study will serve as an exploratory study for such
phenomenon in Saudi Arabia as well as both descriptive for the
characteristics of sweethearting and explanatory study to link
between the environmental and security systems factors to
sweethearting.
Abstract: An optimal solution for a large number of constraint
satisfaction problems can be found using the technique of
substitution and elimination of variables analogous to the technique
that is used to solve systems of equations. A decision function
f(A)=max(A2) is used to determine which variables to eliminate. The
algorithm can be expressed in six lines and is remarkable in both its
simplicity and its ability to find an optimal solution. However it is
inefficient in that it needs to square the updated A matrix after each
variable elimination. To overcome this inefficiency the algorithm is
analyzed and it is shown that the A matrix only needs to be squared
once at the first step of the algorithm and then incrementally updated
for subsequent steps, resulting in significant improvement and an
algorithm complexity of O(n3).
Abstract: UWB is a very attractive technology for many
applications. It provides many advantages such as fine resolution and high power efficiency. Our interest in the current study is the use of
UWB radar technique in microwave medical imaging systems, especially for early breast cancer detection. The Federal Communications Commission FCC allowed frequency bandwidth of
3.1 to 10.6 GHz for this purpose. In this paper we suggest an UWB Bowtie slot antenna with enhanced bandwidth. Effects of varying the geometry of the antenna
on its performance and bandwidth are studied. The proposed antenna
is simulated in CST Microwave Studio. Details of antenna design and
simulation results such as return loss and radiation patterns are discussed in this paper. The final antenna structure exhibits good
UWB characteristics and has surpassed the bandwidth requirements.
Abstract: e-mail has become an important means of electronic
communication but the viability of its usage is marred by Unsolicited
Bulk e-mail (UBE) messages. UBE consists of many types
like pornographic, virus infected and 'cry-for-help' messages as well
as fake and fraudulent offers for jobs, winnings and medicines. UBE
poses technical and socio-economic challenges to usage of e-mails.
To meet this challenge and combat this menace, we need to
understand UBE. Towards this end, the current paper presents a
content-based textual analysis of nearly 3000 winnings-announcing
UBE. Technically, this is an application of Text Parsing and
Tokenization for an un-structured textual document and we approach
it using Bag Of Words (BOW) and Vector Space Document Model
techniques. We have attempted to identify the most frequently
occurring lexis in the winnings-announcing UBE documents. The
analysis of such top 100 lexis is also presented. We exhibit the
relationship between occurrence of a word from the identified lexisset
in the given UBE and the probability that the given UBE will be
the one announcing fake winnings. To the best of our knowledge and
survey of related literature, this is the first formal attempt for
identification of most frequently occurring lexis in winningsannouncing
UBE by its textual analysis. Finally, this is a sincere
attempt to bring about alertness against and mitigate the threat of
such luring but fake UBE.
Abstract: A time-domain numerical model within the
framework of transmission line modeling (TLM) is developed to
simulate electromagnetic pulse propagation inside multiple
microcavities forming photonic crystal (PhC) structures. The model
developed is quite general and is capable of simulating complex
electromagnetic problems accurately. The field quantities can be
mapped onto a passive electrical circuit equivalent what ensures that
TLM is provably stable and conservative at a local level.
Furthermore, the circuit representation allows a high level of
hybridization of TLM with other techniques and lumped circuit
models of components and devices. A photonic crystal structure
formed by rods (or blocks) of high-permittivity dieletric material
embedded in a low-dielectric background medium is simulated as an
example. The model developed gives vital spatio-temporal
information about the signal, and also gives spectral information over
a wide frequency range in a single run. The model has wide
applications in microwave communication systems, optical
waveguides and electromagnetic materials simulations.
Abstract: Estimation time and cost of work completion in a
project and follow up them during execution are contributors to
success or fail of a project, and is very important for project
management team. Delivering on time and within budgeted cost
needs to well managing and controlling the projects. To dealing with
complex task of controlling and modifying the baseline project
schedule during execution, earned value management systems have
been set up and widely used to measure and communicate the real
physical progress of a project. But it often fails to predict the total
duration of the project. In this paper data mining techniques is used
predicting the total project duration in term of Time Estimate At
Completion-EAC (t). For this purpose, we have used a project with
90 activities, it has updated day by day. Then, it is used regular
indexes in literature and applied Earned Duration Method to
calculate time estimate at completion and set these as input data for
prediction and specifying the major parameters among them using
Clem software. By using data mining, the effective parameters on
EAC and the relationship between them could be extracted and it is
very useful to manage a project with minimum delay risks. As we
state, this could be a simple, safe and applicable method in prediction
the completion time of a project during execution.
Abstract: In this paper, we study the oscillation of a class of second-order nonlinear neutral damped variable delay dynamic equations on time scales. By using a generalized Riccati transformation technique, we obtain some sufficient conditions for the oscillation of the equations. The results of this paper improve and extend some known results. We also illustrate our main results with some examples.
Abstract: This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.
Abstract: Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.