Abstract: Timing driven physical design, synthesis, and
optimization tools need efficient closed-form delay models for
estimating the delay associated with each net in an integrated circuit
(IC) design. The total number of nets in a modern IC design has
increased dramatically and exceeded millions. Therefore efficient
modeling of interconnection is needed for high speed IC-s. This
paper presents closed–form expressions for RC and RLC
interconnection trees in current mode signaling, which can be
implemented in VLSI design tool. These analytical model
expressions can be used for accurate calculation of delay after the
design clock tree has been laid out and the design is fully routed.
Evaluation of these analytical models is several orders of magnitude
faster than simulation using SPICE.
Abstract: The strong international competition as the factor of rising economic development efficiency should not turn into destructive force for models of social orientation. What result Europe received from the accelerated integration without a long transition period of the accepted countries. Correlative relationship between the research and development expenditure and labor productivity, inflation and the rate economy's growth of the USA and the euro zone, employment and gross value added between Old and New Europe is analyzed in this article. The article estimates the differences in economic growth of Old and New Europe. Correlation rate between cycles of the euro area and the countries of Central and the Eastern Europe very much differs, though some of these countries have high correlation as members of the Economic and Monetary Union. Besides, the majority of the countries of Central and the Eastern Europe does not correspond to criteria of an optimum currency area.
Abstract: We demonstrate a 40Gbps downstream PON
transmission based on PM-QPSK modulation using commercial DFB
lasers without optical amplifier in the ODN, obtaining 40dB power
budget. We discuss this solution within NG-PON2 architectures.
Abstract: The crystallization kinetics and phase transformation
of SiO2.Al2O3.0,56P2O5.1,8CaO.0,56CaF2 glass have been
investigated using differential thermal analysis (DTA), x-ray
diffraction (XRD), and scanning electron microscopy (SEM). Glass
samples were obtained by melting the glass mixture at 14500С/120
min. in platinum crucibles. The mixture were prepared from
chemically pure reagents: SiO2, Al(OH)3, H3PO4, CaCO3 and CaF2.
The non-isothermal kinetics of crystallization was studied by
applying the DTA measurements carried out at various heating rates.
The activation energies of crystallization and viscous flow were
measured as 348,4 kJ.mol–1 and 479,7 kJ.mol–1 respectively. Value of
Avrami parameter n ≈ 3 correspond to a three dimensional of crystal
growth mechanism. The major crystalline phase determined by XRD
analysis was fluorapatite (Ca(PO4)3F) and as the minor phases –
fluormargarite (CaAl2(Al2SiO2)10F2) and vitlokite (Ca9P6O24). The
resulting glass-ceramic has a homogeneous microstructure, composed
of prismatic crystals, evenly distributed in glass phase.
Abstract: The uses of road map in daily activities are numerous
but it is a hassle to construct and update a road map whenever there
are changes. In Universiti Malaysia Sarawak, research on Automatic
Road Extraction (ARE) was explored to solve the difficulties in
updating road map. The research started with using Satellite Image
(SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space
Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm
was developed to extract roads automatically from satellite-taken
images. In order to extract the road network accurately, the satellite
image must be analyzed prior to the extraction process. The
characteristics of these elements are analyzed and consequently the
relationships among them are determined. In this study, the road
regions are extracted based on colour space elements and edge details
of roads. Besides, edge detection method is applied to further filter
out the non-road regions. The extracted road regions are validated by
using a segmentation method. These results are valuable for building
road map and detecting the changes of the existing road database.
The proposed Hybrid Simple Colour Space Segmentation and Edge
Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks
fully automatic, where the user only needs to input a high-resolution
satellite image and wait for the result. Moreover, this system can
work on complex road network and generate the extraction result in
seconds.
Abstract: A new, simple and highly sensitive kinetic
spectrophotometric method was developed for the determination of
trace amounts of Ru(III) in the range of 0.06-20 ng/ml .The method
is based on the inhibitory effect of ruthenium(III) on the oxidation of
Rhodamine B by bromate in acidic and micellar medium. The
reaction was monitored spectrophotometrically by measuring the
decreasing in absorbance of Rhodamine B at 554 nm with a fixedtime
method..The limit of detection is 0.04 ng/ml Ru(III).The relative
standard deviation of 5 and 10 ng/ml Ru(III) was 2.3 and 2.7 %,
respectively. The method was applied to the determination of
ruthenium in real water samples
Abstract: Mel Frequency Cepstral Coefficient (MFCC) features
are widely used as acoustic features for speech recognition as well
as speaker recognition. In MFCC feature representation, the Mel frequency
scale is used to get a high resolution in low frequency region,
and a low resolution in high frequency region. This kind of processing
is good for obtaining stable phonetic information, but not suitable
for speaker features that are located in high frequency regions. The
speaker individual information, which is non-uniformly distributed
in the high frequencies, is equally important for speaker recognition.
Based on this fact we proposed an admissible wavelet packet based
filter structure for speaker identification. Multiresolution capabilities
of wavelet packet transform are used to derive the new features.
The proposed scheme differs from previous wavelet based works,
mainly in designing the filter structure. Unlike others, the proposed
filter structure does not follow Mel scale. The closed-set speaker
identification experiments performed on the TIMIT database shows
improved identification performance compared to other commonly
used Mel scale based filter structures using wavelets.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: In order to implement flexibility as well as survivable
capacities over passive optical network (PON), a new automatic
random fault-recovery mechanism with array-waveguide-grating
based (AWG-based) optical switch (OSW) is presented. Firstly,
wavelength-division-multiplexing and optical code-division
multiple-access (WDM/OCDMA) scheme are configured to meet the
various geographical locations requirement between optical network
unit (ONU) and optical line terminal (OLT). The AWG-base optical
switch is designed and viewed as central star-mesh topology to
prohibit/decrease the duplicated redundant elements such as fiber and
transceiver as well. Hence, by simple monitoring and routing switch
algorithm, random fault-recovery capacity is achieved over
bi-directional (up/downstream) WDM/OCDMA scheme. When error
of distribution fiber (DF) takes place or bit-error-rate (BER) is higher
than 10-9 requirement, the primary/slave AWG-based OSW are
adjusted and controlled dynamically to restore the affected ONU
groups via the other working DFs immediately.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Networked schools have become a feature of
education systems in countries that seek to provide learning
opportunities in schools located beyond major centres of population.
The internet and e-learning have facilitated the development of
virtual educational structures that complement traditional schools,
encouraging collaborative teaching and learning to proceed. In rural
New Zealand and in the Atlantic Canadian province of
Newfoundland and Labrador, e-learning is able to provide new ways
of organizing teaching, learning and the management of educational
opportunities. However, the future of e-teaching and e-learning in
networked schools depends on the development of professional
education programs that prepare teachers for collaborative teaching
and learning environments in which both virtual and traditional face
to face instruction co-exist.
Abstract: this paper presented a survey analysis subjected on
network bandwidth management from published papers referred in
IEEE Explorer database in three years from 2009 to 2011. Network
Bandwidth Management is discussed in today-s issues for computer
engineering applications and systems. Detailed comparison is
presented between published papers to look further in the IP based
network critical research area for network bandwidth management.
Important information such as the network focus area, a few
modeling in the IP Based Network and filtering or scheduling used in
the network applications layer is presented. Many researches on
bandwidth management have been done in the broad network area
but fewer are done in IP Based network specifically at the
applications network layer. A few researches has contributed new
scheme or enhanced modeling but still the issue of bandwidth
management still arise at the applications network layer. This survey
is taken as a basic research towards implementations of network
bandwidth management technique, new framework model and
scheduling scheme or algorithm in an IP Based network which will
focus in a control bandwidth mechanism in prioritizing the network
traffic the applications layer.
Abstract: A common way to elude the signature-based Network Intrusion Detection System is based upon changing a recognizable attack to an unrecognizable one via the IDS. For example, in order to evade sign accommodation with intrusion detection system markers, a hacker spilt the payload packet into many small pieces or hides them within messages. In this paper we try to model the main fragmentation attack and create a new module in the intrusion detection architecture system which recognizes the main fragmentation attacks through verification of integrity checking of TCP packet in order to prevent elusion of the system and also to announce the necessary alert to the system administrator.
Abstract: To establish optical communication between any two
satellites, the transmitter satellite must track the beacon of the
receiver satellite and point the information optical beam in its
direction. Optical tracking and pointing systems for free space suffer
during tracking from high-amplitude vibration because of
background radiation from interstellar objects such as the Sun, Moon,
Earth, and stars in the tracking field of view or the mechanical
impact from satellite internal and external sources. The vibrations of
beam pointing increase the bit error rate and jam communication
between the two satellites. One way to overcome this problem is the
use of very small transmitter beam divergence angles of too narrow
divergence angle is that the transmitter beam may sometimes miss
the receiver satellite, due to pointing vibrations. In this paper we
propose the use of genetic algorithm to optimize the BER as function
of transmitter optics aperture.
Abstract: This paper addresses one of the most important issues
have been considered in hybrid MTS/MTO production environments. To cope with the problem, a mathematical programming model is
applied from a tactical point of view. The model is converted to a fuzzy goal programming model, because a degree of uncertainty is involved in hybrid MTS/MTO context. Finally, application of the
proposed model in an industrial center is reported and the results prove the validity of the model.
Abstract: Adaptive Genetic Algorithms extend the Standard Gas
to use dynamic procedures to apply evolutionary operators such as
crossover, mutation and selection. In this paper, we try to propose a
new adaptive genetic algorithm, which is based on the statistical
information of the population as a guideline to tune its crossover,
selection and mutation operators. This algorithms is called Statistical
Genetic Algorithm and is compared with traditional GA in some
benchmark problems.
Abstract: In this research work, investigations are carried out on
Continuous Wave (CW) Nd:YAG laser welding system after
preliminary experimentation to understand the influencing parameters
associated with laser welding of AISI 304. The experimental
procedure involves a series of laser welding trials on AISI 304
stainless steel sheets with various combinations of process parameters
like beam power, beam incident angle and beam incident angle. An
industrial 2 kW CW Nd:YAG laser system, available at Welding
Research Institute (WRI), BHEL Tiruchirappalli, is used for
conducting the welding trials for this research. After proper tuning of
laser beam, laser welding experiments are conducted on AISI 304
grade sheets to evaluate the influence of various input parameters on
weld bead geometry i.e. bead width (BW) and depth of penetration
(DOP). From the laser welding results, it is noticed that the beam
power and welding speed are the two influencing parameters on
depth and width of the bead. Three dimensional finite element
simulation of high density heat source have been performed for laser
welding technique using finite element code ANSYS for predicting
the temperature profile of laser beam heat source on AISI 304
stainless steel sheets. The temperature dependent material properties
for AISI 304 stainless steel are taken into account in the simulation,
which has a great influence in computing the temperature profiles.
The latent heat of fusion is considered by the thermal enthalpy of
material for calculation of phase transition problem. A Gaussian
distribution of heat flux using a moving heat source with a conical
shape is used for analyzing the temperature profiles. Experimental
and simulated values for weld bead profiles are analyzed for stainless
steel material for different beam power, welding speed and beam
incident angle. The results obtained from the simulation are
compared with those from the experimental data and it is observed
that the results of numerical analysis (FEM) are in good agreement
with experimental results, with an overall percentage of error
estimated to be within ±6%.
Abstract: In this paper the development of a heat exchanger as a
pilot plant for educational purpose is discussed and the use of neural
network for controlling the process is being presented. The aim of the
study is to highlight the need of a specific Pseudo Random Binary
Sequence (PRBS) to excite a process under control. As the neural
network is a data driven technique, the method for data generation
plays an important role. In light of this a careful experimentation
procedure for data generation was crucial task. Heat exchange is a
complex process, which has a capacity and a time lag as process
elements. The proposed system is a typical pipe-in- pipe type heat
exchanger. The complexity of the system demands careful selection,
proper installation and commissioning. The temperature, flow, and
pressure sensors play a vital role in the control performance. The
final control element used is a pneumatically operated control valve.
While carrying out the experimentation on heat exchanger a welldrafted
procedure is followed giving utmost attention towards safety
of the system. The results obtained are encouraging and revealing
the fact that if the process details are known completely as far as
process parameters are concerned and utilities are well stabilized then
feedback systems are suitable, whereas neural network control
paradigm is useful for the processes with nonlinearity and less
knowledge about process. The implementation of NN control
reinforces the concepts of process control and NN control paradigm.
The result also underlined the importance of excitation signal
typically for that process. Data acquisition, processing, and
presentation in a typical format are the most important parameters
while validating the results.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: This research is part of a broad program aimed at
advancing the science and technology involved in the rescue and
rehabilitation of oiled wildlife. One aspect of this research involves
the use of oil-sequestering magnetic particles for the removal of
contaminants from plumage – so-called “magnetic cleansing". This
treatment offers a number of advantages over conventional
detergent-based methods including portability - which offers the
possibility of providing a “quick clean" to the animal upon first
encounter in the field. This could be particularly advantageous
when the contaminant is toxic and/or corrosive and/or where there
is a delay in transporting the victim to a treatment centre. The
method could also be useful as part of a stabilization protocol when
large numbers of affected animals are awaiting treatment. This
presentation describes the design, development and testing of a
prototype field kit for providing a “quick clean" to contaminated
wildlife in the field.