Abstract: Available Bit Rate Service (ABR) is the lower priority
service and the better service for the transmission of data. On wireline
ATM networks ABR source is always getting the feedback from
switches about increase or decrease of bandwidth according to the
changing network conditions and minimum bandwidth is guaranteed.
In wireless networks guaranteeing the minimum bandwidth is really a
challenging task as the source is always in mobile and traveling from
one cell to another cell. Re establishment of virtual circuits from start
to end every time causes the delay in transmission. In our proposed
solution we proposed the mechanism to provide more available
bandwidth to the ABR source by re-usage of part of old Virtual
Channels and establishing the new ones. We want the ABR source to
transmit the data continuously (non-stop) inorderto avoid the delay.
In worst case scenario at least minimum bandwidth is to be allocated.
In order to keep the data flow continuously, priority is given to the
handoff ABR call against new ABR call.
Abstract: In this work, ionic liquids (ILs) for CO2 capturing in typical absorption/stripper process are considered. The use of ionic liquids is considered to be cost-effective because it requires less energy for solvent recovery compared to other conventional processes. A mathematical model is developed for the process based on Peng-Robinson (PR) equation of state (EoS) which is validated with experimental data for various solutions involving CO2. The model is utilized to study the sorbent and energy demand for three types of ILs at specific CO2 capturing rates. The energy demand is manifested by the vapor-liquid equilibrium temperature necessary to remove the captured CO2 from the used solvent in the regeneration step. It is found that higher recovery temperature is required for solvents with higher solubility coefficient. For all ILs, the temperature requirement is less than that required by the typical monoethanolamine (MEA) solvent. The effect of the CO2 loading in the sorbent stream on the process performance is also examined.
Abstract: In this work we adopt a combination of Laplace
transform and the decomposition method to find numerical solutions
of a system of multi-pantograph equations. The procedure leads to a
rapid convergence of the series to the exact solution after computing a
few terms. The effectiveness of the method is demonstrated in some
examples by obtaining the exact solution and in others by computing
the absolute error which decreases as the number of terms of the series
increases.
Abstract: The Wavelet-Galerkin finite element method for
solving the one-dimensional heat equation is presented in this work.
Two types of basis functions which are the Lagrange and multi-level
wavelet bases are employed to derive the full form of matrix system.
We consider both linear and quadratic bases in the Galerkin method.
Time derivative is approximated by polynomial time basis that
provides easily extend the order of approximation in time space. Our
numerical results show that the rate of convergences for the linear
Lagrange and the linear wavelet bases are the same and in order 2
while the rate of convergences for the quadratic Lagrange and the
quadratic wavelet bases are approximately in order 4. It also reveals
that the wavelet basis provides an easy treatment to improve
numerical resolutions that can be done by increasing just its desired
levels in the multilevel construction process.
Abstract: RFID (Radio Frequency IDentification) system has
been widely used in our life, such as transport systems, passports,
automotive, animal tracking, human implants, library, and so on.
However, the RFID authentication protocols between RF (Radio
Frequency) tags and the RF readers have been bring about various
privacy problems that anonymity of the tags, tracking, eavesdropping,
and so on. Many researchers have proposed the solution of the
problems. However, they still have the problem, such as location
privacy, mutual authentication. In this paper, we show the problems of
the previous protocols, and then we propose a more secure and
efficient RFID authentication protocol.
Abstract: Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).
Abstract: In this work, we apply the Modified Laplace
decomposition algorithm in finding a numerical solution of Blasius’
boundary layer equation for the flat plate in a uniform stream. The
series solution is found by first applying the Laplace transform to the
differential equation and then decomposing the nonlinear term by the
use of Adomian polynomials. The resulting series, which is exactly the
same as that obtained by Weyl 1942a, was expressed as a rational
function by the use of diagonal padé approximant.
Abstract: This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Abstract: In this paper variation of spot price and total profits of
the generating companies- through wholesale electricity trading are
discussed with and without Central Generating Stations (CGS) share
and seasonal variations are also considered. It demonstrates how
proper analysis of generators- efficiencies and capabilities, types of
generators owned, fuel costs, transmission losses and settling price
variation using the solutions of Optimal Power Flow (OPF), can
allow companies to maximize overall revenue. It illustrates how
solutions of OPF can be used to maximize companies- revenue under
different scenarios. And is also extended to computation of Available
Transfer Capability (ATC) is very important to the transmission
system security and market forecasting. From these results it is
observed that how crucial it is for companies to plan their daily
operations and is certainly useful in an online environment of
deregulated power system. In this paper above tasks are demonstrated
on 124 bus real-life Indian utility power system of Andhra Pradesh
State Grid and results have been presented and analyzed.
Abstract: Knowledge is attributed to human whose problemsolving
behavior is subjective and complex. In today-s knowledge
economy, the need to manage knowledge produced by a community
of actors cannot be overemphasized. This is due to the fact that
actors possess some level of tacit knowledge which is generally
difficult to articulate. Problem-solving requires searching and sharing
of knowledge among a group of actors in a particular context.
Knowledge expressed within the context of a problem resolution
must be capitalized for future reuse. In this paper, an approach that
permits dynamic capitalization of relevant and reliable actors-
knowledge in solving decision problem following Economic
Intelligence process is proposed. Knowledge annotation method and
temporal attributes are used for handling the complexity in the
communication among actors and in contextualizing expressed
knowledge. A prototype is built to demonstrate the functionalities of
a collaborative Knowledge Management system based on this
approach. It is tested with sample cases and the result showed that
dynamic capitalization leads to knowledge validation hence
increasing reliability of captured knowledge for reuse. The system
can be adapted to various domains.
Abstract: The struggle between modern and postmodern
understanding is also displayed in terms of the superiorities of
quantitative and qualitative methods to each other which are
evaluated within the scope of these understandings. By way of
assuming that the quantitative researches (modern) are able to
account for structure while the qualitative researches (postmodern)
explain the process, these methods are turned into a means for
worldviews specific to a period. In fact, process is not a functioning
independent of structure. In addition to this issue, the ability of
quantitative methods to provide scientific knowledge is also
controversial so long as they exclude the dialectical method. For this
reason, the critiques charged against modernism in terms of
quantitative methods are, in a sense, legitimate. Nevertheless, the
main issue is in which parameters postmodernist critique tries to
legitimize its critiques and whether these parameters represent a point
of view enabling democratic solutions.
In this respect, the scientific knowledge covered in Turkish media
as a means through which ordinary people have access to scientific
knowledge will be evaluated by means of content analysis within a
new objectivity conception.
Abstract: Recently, in some places, optical-fibre access
networks have been used with GPON technology belonging to
organizations (in most cases public bodies) that act as neutral
operators. These operators simultaneously provide network services
to various telecommunications operators that offer integrated voice,
data and television services. This situation creates new problems
related to quality of service, since the interests of the users are
intermingled with the interests of the operators. In this paper, we
analyse this problem and consider solutions that make it possible to
provide guaranteed quality of service for voice over IP, data services
and interactive digital television.
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: The symmetric solution set Σ sym is the set of all solutions to the linear systems Ax = b, where A is symmetric and lies between some given bounds A and A, and b lies between b and b. We present a contractor for Σ sym, which is an iterative method that starts with some initial enclosure of Σ sym (by means of a cartesian product of intervals) and sequentially makes the enclosure tighter. Our contractor is based on polyhedral approximation and solving a series of linear programs. Even though it does not converge to the optimal bounds in general, it may significantly reduce the overestimation. The efficiency is discussed by a number of numerical experiments.
Abstract: Crucial information barely visible to the human eye is
often embedded in a series of low resolution images taken of the
same scene. Super resolution reconstruction is the process of
combining several low resolution images into a single higher
resolution image. The ideal algorithm should be fast, and should add
sharpness and details, both at edges and in regions without adding
artifacts. In this paper we propose a super resolution blind
reconstruction technique for linearly degraded images. In our
proposed technique the algorithm is divided into three parts an image
registration, wavelets based fusion and an image restoration. In this
paper three low resolution images are considered which may sub
pixels shifted, rotated, blurred or noisy, the sub pixel shifted images
are registered using affine transformation model; A wavelet based
fusion is performed and the noise is removed using soft thresolding.
Our proposed technique reduces blocking artifacts and also
smoothens the edges and it is also able to restore high frequency
details in an image. Our technique is efficient and computationally
fast having clear perspective of real time implementation.
Abstract: In this paper we present a novel approach for human
Body configuration based on the Silhouette. We propose to address
this problem under the Bayesian framework. We use an effective
Model based MCMC (Markov Chain Monte Carlo) method to solve
the configuration problem, in which the best configuration could be
defined as MAP (maximize a posteriori probability) in Bayesian
model. This model based MCMC utilizes the human body model to
drive the MCMC sampling from the solution space. It converses the
original high dimension space into a restricted sub-space constructed
by the human model and uses a hybrid sampling algorithm. We
choose an explicit human model and carefully select the likelihood
functions to represent the best configuration solution. The
experiments show that this method could get an accurate
configuration and timesaving for different human from multi-views.
Abstract: The effect of extraction solvent upon properties
of carrageenan from Eucheuma cottonii was studied. The
distilled water and KOH solution (concentration 0.1- 0.5N) were
used as the solvent. Extraction process was carried out in water
bath equipped by stirrer with constant speed of 275 rpm with a
constant ratio of seaweed weight to solvent volume ( 1:50 g/mL)
at 86oC for 45 minutes. The extract was then precipitated in 3
volume of 90% ethanol, oven dried at 60oC. Based on
experimental data, alkali significantly influenced yield and
properties of extracted carrageenan. The extracted carrageenan
was found to have essentially identical FTIR spectra to the
reference samples of kappa-carrageenan. Increasing the KOH
concentration led to carrageenan containing less sulfate content
and intrinsic viscosity. The gel strength increased along with the
increasing of KOH concentration. The decreasing of intrinsic
viscosity value indicates that a polymer degradation occurs
during alkali extraction.
Abstract: This paper explores the effectiveness of machine
learning techniques in detecting firms that issue fraudulent financial
statements (FFS) and deals with the identification of factors
associated to FFS. To this end, a number of experiments have been
conducted using representative learning algorithms, which were
trained using a data set of 164 fraud and non-fraud Greek firms in the
recent period 2001-2002. The decision of which particular method to
choose is a complicated problem. A good alternative to choosing
only one method is to create a hybrid forecasting system
incorporating a number of possible solution methods as components
(an ensemble of classifiers). For this purpose, we have implemented
a hybrid decision support system that combines the representative
algorithms using a stacking variant methodology and achieves better
performance than any examined simple and ensemble method. To
sum up, this study indicates that the investigation of financial
information can be used in the identification of FFS and underline the
importance of financial ratios.
Abstract: The previous study of new metal gasket that contact
width and contact stress an important design parameter for optimizing
metal gasket performance. The optimum design based on an elastic
and plastic contact stress was founded. However, the influence of
flange surface roughness had not been investigated thoroughly. The
flange has many kinds of surface roughness. In this study, we
conducted a gasket model include a flange surface roughness effect. A
finite element method was employed to develop simulation solution. A
uniform quadratic mesh used for meshing the gasket material and a
gradually quadrilateral mesh used for meshing the flange. The gasket
model was simulated by using two simulation stages which is forming
and tightening simulation. A simulation result shows that a smoother
of surface roughness has higher slope for force per unit length. This
mean a squeezed against between flange and gasket will be strong. The
slope of force per unit length for gasket 400-MPa mode was higher
than the gasket 0-MPa mode.
Abstract: Using vision based solution in intelligent vehicle application often needs large memory to handle video stream and image process which increase complexity of hardware and software. In this paper, we present a FPGA implement of a vision based lane departure warning system. By taking frame of videos, the line gradient of line is estimated and the lane marks are found. By analysis the position of lane mark, departure of vehicle will be detected in time. This idea has been implemented in Xilinx Spartan6 FPGA. The lane departure warning system used 39% logic resources and no memory of the device. The average availability is 92.5%. The frame rate is more than 30 frames per second (fps).