Abstract: In many ways, biomedical analysis is analogous to possibilistic reasoning. In spite of that, there are hardly any applications of possibility theory in biology or medicine. The aim of this work is to demonstrate the use of possibility theory in an epidemiological study. In the paper, we build the possibility distribution for the controlled bloodstream concentrations of any physiologically active substance through few approximate considerations. This possibility distribution is tested later against the empirical histograms obtained from the panel study of the eight different physiologically active substances in 417 individuals.
Abstract: An exact algorithm for a n-link manipulator movement amidst arbitrary unknown static obstacles is presented.
The algorithm guarantees the reaching of a target configuration of the manipulator in a finite number of steps. The algorithm is
reduced to a finite number of calls of a subroutine for planning a trajectory in the presence of known forbidden states. The polynomial approximation algorithm which is used as the subroutine is presented. The results of the exact algorithm
implementation for the control of a seven link (7 degrees of
freedom, 7DOF) manipulator are given.
Abstract: The purpose of the present work was to study the
production and process parameters optimization for the synthesis of
cellulase from Trichoderma viride in solid state fermentation (SSF)
using an agricultural wheat straw as substrates; as fungal conversion
of lignocellulosic biomass for cellulase production is one among the
major increasing demand for various biotechnological applications.
An optimization of process parameters is a necessary step to get
higher yield of product. Several kinetic parameters like pretreatment,
extraction solvent, substrate concentration, initial moisture content,
pH, incubation temperature and inoculum size were optimized for
enhanced production of third most demanded industrially important
cellulase. The maximum cellulase enzyme activity 398.10±2.43
μM/mL/min was achieved when proximally analyzed lignocellulosic
substrate wheat straw inocubated at 2% HCl as pretreatment tool
along with distilled water as extraction solvent, 3% substrate
concentration 40% moisture content with optimum pH 5.5 at 45°C
incubation temperature and 10% inoculum size.
Abstract: We propose a new approach on how to obtain the approximate solutions of Hamilton-Jacobi (HJ) equations. The process of the approximation consists of two steps. The first step is to transform the HJ equations into the virtual time based HJ equations (VT-HJ) by introducing a new idea of ‘virtual-time’. The second step is to construct the approximate solutions of the HJ equations through a computationally iterative procedure based on the VT-HJ equations. It should be noted that the approximate feedback solutions evolve by themselves as the virtual-time goes by. Finally, we demonstrate the effectiveness of our approximation approach by means of simulations with linear and nonlinear control problems.
Abstract: The Helmholtz equation often arises in the study of physical problems involving partial differential equation. Many researchers have proposed numerous methods to find the analytic or approximate solutions for the proposed problems. In this work, the exact analytical solutions of the Helmholtz equation in spherical polar coordinates are presented using the Nikiforov-Uvarov (NU) method. It is found that the solution of the angular eigenfunction can be expressed by the associated-Legendre polynomial and radial eigenfunctions are obtained in terms of the Laguerre polynomials. The special case for k=0, which corresponds to the Laplace equation is also presented.
Abstract: A novel method of learning complex fuzzy decision regions in the n-dimensional feature space is proposed. Through the fuzzy decision regions, a given pattern's class membership value of every class is determined instead of the conventional crisp class the pattern belongs to. The n-dimensional fuzzy decision region is approximated by union of hyperellipsoids. By explicitly parameterizing these hyperellipsoids, the decision regions are determined by estimating the parameters of each hyperellipsoid.Genetic Algorithm is applied to estimate the parameters of each region component. With the global optimization ability of GA, the learned decision region can be arbitrarily complex.
Abstract: The indoor airflow with a mixed natural/forced convection
was numerically calculated using the laminar and turbulent
approach. The Boussinesq approximation was considered for a simplification
of the mathematical model and calculations. The results
obtained, such as mean velocity fields, were successfully compared
with experimental PIV flow visualizations. The effect of the distance
between the cooled wall and the heat exchanger on the temperature
and velocity distributions was calculated. In a room with a simple
shape, the computational code OpenFOAM demonstrated an ability to
numerically predict flow patterns. Furthermore, numerical techniques,
boundary type conditions and the computational grid quality were
examined. Calculations using the turbulence model k-omega had a
significant effect on the results influencing temperature and velocity
distributions.
Abstract: Frequently a group of people jointly decide and authorize
a specific person as a representative in some business/poitical
occasions, e.g., the board of a company authorizes the chief executive
officer to close a multi-billion acquisition deal. In this paper, an
integrated proxy multi-signature scheme that allows anonymously
vetoable delegation is proposed. This protocol integrates mechanisms
of private veto, distributed proxy key generation, secure transmission
of proxy key, and existentially unforgeable proxy multi-signature
scheme. First, a provably secure Guillou-Quisquater proxy signature
scheme is presented, then the “zero-sharing" protocol is extended
over a composite modulus multiplicative group, and finally the above
two are combined to realize the GQ proxy multi-signature with
anonymously vetoable delegation. As a proxy signature scheme, this
protocol protects both the original signers and the proxy signer.
The modular design allows simplified implementation with less
communication overheads and better computation performance than
a general secure multi-party protocol.
Abstract: The aim of this study was to investigate the influence
of reaction temperature and wheat straw moisture content on the
pyrolysis product yields, in the temperature range of 475-575 °C.
Samples of straw with moisture contents from 1.5 wt % to 15.0 wt %
were fed to a bench scale Pyrolysis Centrifuge Reactor (PCR). The
experimental results show that the changes in straw moisture content
have no significant effect on the distribution of pyrolysis product
yields. The maximum bio-oil yields approximately 60 (wt %, on dry
ash free feedstock basis) was observed around 525 °C - 550 °C for all
straw moisture levels. The water content in the wet straw bio-oil was
the highest. The heating value of bio-oil and solid char were
measured and the percentages of its energy distribution were
calculated. The energy distributions of bio-oil, char and gas were 56-
69 % 24-33 %, and 2-19 %, respectively.
Abstract: In this paper, we show that C*-tensor product of an arbitrary C*-algebra A, (not unital necessary) and C*-algebra B without ground state, have no approximately inner strongly continuous one-parameter group of *-automorphisms.
Abstract: Polyphenolics and sugar are the components of many
fruit juices. In this work, the performance of ultra-filtration (UF) for
separating phenolic compounds from apple juice was studied by
performing batch experiments in a membrane module with an area of
0.1 m2 and fitted with a regenerated cellulose membrane of 1 kDa
MWCO. The effects of various operating conditions: transmembrane
pressure (3, 4, 5 bar), temperature (30, 35, 40 ºC), pH (2, 3, 4, 5),
feed concentration (3, 5, 7, 10, 15 ºBrix for apple juice) and feed flow
rate (1, 1.5, 1.8 L/min) on the performance were determined.
The optimum operating conditions were: transmembrane pressure
4 bar, temperature 30 ºC, feed flow rate 1 – 1.8 L/min, pH 3 and 10
Brix (apple juice). After performing ultrafiltration under these
conditions, the concentration of polyphenolics in retentate was
increased by a factor of up to 2.7 with up to 70% recovered in the
permeate and with approx. 20% of the sugar in that stream..
Application of diafiltration (addition of water to the concentrate) can
regain the flux by a factor of 1.5, which has been decreased due to
fouling. The material balance performed on the process has shown
the amount of deposits on the membrane and the extent of fouling in
the system. In conclusion, ultrafiltration has been demonstrated as a
potential technology to separate the polyphenolics and sugars from
their mixtures and can be applied to remove sugars from fruit juice.
Abstract: The ever increasing product diversity and competition on the market of goods and services has dictated the pace of growth in the number of advertisements. Despite their admittedly diminished effectiveness over the recent years, advertisements remain the favored method of sales promotion. Consequently, the challenge for an advertiser is to explore every possible avenue of making an advertisement more noticeable, attractive and impellent for consumers. One way to achieve this is through invoking celebrity endorsements. On the one hand, the use of a celebrity to endorse a product involves substantial costs, however, on the other hand, it does not immediately guarantee the success of an advertisement. The question of how celebrities can be used in advertising to the best advantage is therefore of utmost importance. Celebrity endorsements have become commonplace: empirical evidence indicates that approximately 20 to 25 per cent of advertisements feature some famous person as a product endorser. The popularity of celebrity endorsements demonstrates the relevance of the topic, especially in the context of the current global economic downturn, when companies are forced to save in order to survive, yet simultaneously to heavily invest in advertising and sales promotion. The issue of the effective use of celebrity endorsements also figures prominently in the academic discourse. The study presented below is thus aimed at exploring what qualities (characteristics) of a celebrity endorser have an impact on the ffectiveness of the advertisement in which he/she appears and how.
Abstract: The purpose of this work is to present a method for
rigid registration of medical images using 1D binary projections
when a part of one of the two images is missing. We use 1D binary
projections and we adjust the projection limits according to the
reduced image in order to perform accurate registration. We use the
variance of the weighted ratio as a registration function which we
have shown is able to register 2D and 3D images more accurately and
robustly than mutual information methods. The function is computed
explicitly for n=5 Chebyshev points in a [-9,+9] interval and it is
approximated using Chebyshev polynomials for all other points. The
images used are MR scans of the head. We find that the method is
able to register the two images with average accuracy 0.3degrees for
rotations and 0.2 pixels for translations for a y dimension of 156 with
initial dimension 256. For y dimension 128/256 the accuracy
decreases to 0.7 degrees for rotations and 0.6 pixels for translations.
Abstract: One of the essential components of much of DSP
application is noise cancellation. Changes in real time signals are
quite rapid and swift. In noise cancellation, a reference signal which
is an approximation of noise signal (that corrupts the original
information signal) is obtained and then subtracted from the noise
bearing signal to obtain a noise free signal. This approximation of
noise signal is obtained through adaptive filters which are self
adjusting. As the changes in real time signals are abrupt, this needs
adaptive algorithm that converges fast and is stable. Least mean
square (LMS) and normalized LMS (NLMS) are two widely used
algorithms because of their plainness in calculations and
implementation. But their convergence rates are small. Adaptive
averaging filters (AFA) are also used because they have high
convergence, but they are less stable. This paper provides the
comparative study of LMS and Normalized NLMS, AFA and new
enhanced average adaptive (Average NLMS-ANLMS) filters for noise
cancelling application using speech signals.
Abstract: In this paper, a new approach is introduced to solve
Blasius equation using parameter identification of a nonlinear
function which is used as approximation function. Bees Algorithm
(BA) is applied in order to find the adjustable parameters of
approximation function regarding minimizing a fitness function
including these parameters (i.e. adjustable parameters). These
parameters are determined how the approximation function has to
satisfy the boundary conditions. In order to demonstrate the
presented method, the obtained results are compared with another
numerical method. Present method can be easily extended to solve a
wide range of problems.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: The Lattice Boltzmann Method (LBM) with double populations is applied to solve the steady-state laminar natural convective heat transfer in a triangular cavity filled with water. The bottom wall is heated, the vertical wall is cooled, and the inclined wall is kept adiabatic. The buoyancy effect was modeled by applying the Boussinesq approximation to the momentum equation. The fluid velocity is determined by D2Q9 LBM and the energy equation is discritized by D2Q4 LBM to compute the temperature field. Comparisons with previously published work are performed and found to be in excellent agreement. Numerical results are obtained for a wide range of parameters: the Rayleigh number from to and the inclination angle from 0° to 360°. Flow and thermal fields were exhibited by means of streamlines and isotherms. It is observed that inclination angle can be used as a relevant parameter to control heat transfer in right-angled triangular enclosures.
Abstract: Nowadays, we are facing with network threats that
cause enormous damage to the Internet community day by day. In
this situation, more and more people try to prevent their network
security using some traditional mechanisms including firewall,
Intrusion Detection System, etc. Among them honeypot is a versatile
tool for a security practitioner, of course, they are tools that are meant
to be attacked or interacted with to more information about attackers,
their motives and tools. In this paper, we will describe usefulness of
low-interaction honeypot and high-interaction honeypot and
comparison between them. And then we propose hybrid honeypot
architecture that combines low and high -interaction honeypot to
mitigate the drawback. In this architecture, low-interaction honeypot
is used as a traffic filter. Activities like port scanning can be
effectively detected by low-interaction honeypot and stop there.
Traffic that cannot be handled by low-interaction honeypot is handed
over to high-interaction honeypot. In this case, low-interaction
honeypot is used as proxy whereas high-interaction honeypot offers
the optimal level realism. To prevent the high-interaction honeypot
from infections, containment environment (VMware) is used.
Abstract: This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Finally, simulation results are given to demonstrate the controller-s effectiveness.
Abstract: The aim of this research is to develop a fast and
reliable surveillance system based on a personal digital assistant
(PDA) device. This is to extend the capability of the device to detect
moving objects which is already available in personal computers.
Secondly, to compare the performance between Background
subtraction (BS) and Temporal Frame Differencing (TFD) techniques
for PDA platform as to which is more suitable. In order to reduce
noise and to prepare frames for the moving object detection part,
each frame is first converted to a gray-scale representation and then
smoothed using a Gaussian low pass filter. Two moving object
detection schemes i.e., BS and TFD have been analyzed. The
background frame is updated by using Infinite Impulse Response
(IIR) filter so that the background frame is adapted to the varying
illuminate conditions and geometry settings. In order to reduce the
effect of noise pixels resulting from frame differencing
morphological filters erosion and dilation are applied. In this
research, it has been found that TFD technique is more suitable for
motion detection purpose than the BS in term of speed. On average
TFD is approximately 170 ms faster than the BS technique