Abstract: Pentachlorophenol (PCP) is a polychlorinated
aromatic compound that is widespread in industrial effluents and is
considered to be a serious pollutant. Among the variety of industrial
effluents encountered, effluents from tanning industry are very
important and have a serious pollution potential. PCP is also formed
unintentionally in effluents of paper and pulp industries. It is highly
persistent in soils and is lethal to a wide variety of beneficial
microorganisms and insects, human beings and animals. The natural
processes that breakdown toxic chemicals in the environment have
become the focus of much attention to develop safe and environmentfriendly
deactivation technologies. Microbes and plants are among
the most important biological agents that remove and degrade waste
materials to enable their recycling in the environment. The present
investigation was carried out with the aim of developing a microbial
system for bioremediation of PCP polluted soils. A number of plant
species were evaluated for their ability to tolerate different
concentrations of pentachlorophenol (PCP) in the soil. The
experiment was conducted for 30 days under pot culture conditions.
The toxic effect of PCP on plants was studied by monitoring seed
germination, plant growth and biomass. As the concentration of PCP
was increased to 50 ppm, the inhibition of seed germination, plant
growth and biomass was also increased. Although PCP had a
negative effect on all plant species tested, maize and groundnut
showed the maximum tolerance to PCP. Other tolerating crops
included wheat, safflower, sunflower, and soybean. From the
rhizosphere soil of the tolerant seedlings, as many as twenty seven
PCP tolerant bacteria were isolated. From soybean, 8; sunflower, 3;
safflower 8; maize 2; groundnut and wheat, 3 each isolates were
made. They were screened for their PCP degradation potentials.
HPLC analyses of PCP degradation revealed that the isolate MAZ-2
degraded PCP completely. The isolate MAZ-1 was the next best
isolate with 90 per cent PCP degradation. These strains hold promise
to be used in the bioremediation of PCP polluted soils.
Abstract: In a wind power generator using doubly fed induction
generator (DFIG), the three-phase pulse width modulation (PWM)
voltage source converter (VSC) is used as grid side converter (GSC)
and rotor side converter (RSC). The standard linear control laws
proposed for GSC provides not only instablity against comparatively
large-signal disturbances, but also the problem of stability due to
uncertainty of load and variations in parameters. In this paper, a
nonlinear controller is designed for grid side converter (GSC) of a
DFIG for wind power application. The nonlinear controller is
designed based on the input-output feedback linearization control
method. The resulting closed-loop system ensures a sufficient
stability region, make robust to variations in circuit parameters and
also exhibits good transient response. Computer simulations and
experimental results are presented to confirm the effectiveness of the
proposed control strategy.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: For gamma radiation detection, assemblies having
scintillation crystals and a photomultiplier tube, also there is a
preamplifier connected to the detector because the signals from
photomultiplier tube are of small amplitude. After pre-amplification
the signals are sent to the amplifier and then to the multichannel
analyser. The multichannel analyser sorts all incoming electrical
signals according to their amplitudes and sorts the detected photons
in channels covering small energy intervals. The energy range of
each channel depends on the gain settings of the multichannel
analyser and the high voltage across the photomultiplier tube. The
exit spectrum data of the two main isotopes studied ,putting data in
biomass program ,process it by Matlab program to get the solid
holdup image (solid spherical nuclear fuel)
Abstract: The new semi-experimental method for simulation of
the turbine flow meters rotation in the transitional flow has been
developed. The method is based on the experimentally established
exponential low of changing of dimensionless relative turbine gas
meter rotation frequency and meter inertia time constant. For
experimental evaluation of the meter time constant special facility
has been developed. The facility ensures instant switching of turbine
meter under test from one channel to the other channel with different
flow rate and measuring the meter response. The developed method
can be used for evaluation and predication of the turbine meters
response and dynamic error in the transitional flow with any arbitrary
law of flow rate changing. The examples of the method application
are presented.
Abstract: In this paper, a parametric experimental study for producing paving blocks using fine and coarse waste glass is presented. Some of the physical and mechanical properties of paving blocks having various levels of fine glass (FG) and coarse glass (CG) replacements with fine aggregate (FA) are investigated. The test results show that the replacement of FG by FA at level of 20% by weight has a significant effect on the compressive strength, flexural strength, splitting tensile strength and abrasion resistance of the paving blocks as compared with the control sample because of puzzolanic nature of FG. The compressive strength, flexural strength, splitting tensile strength and abrasion resistance of the paving block samples in the FG replacement level of 20% are 69%, 90%, 47% and 15 % higher as compared with the control sample respectively. It is reported in the earlier works the replacement of FG by FA at level of 20% by weight suppress the alkali-silica reaction (ASR) in the concrete. The test results show that the FG at level of 20% has a potential to be used in the production of paving blocks. The beneficial effect on these properties of CG replacement with FA is little as compared with FG.
Abstract: The objective of global optimization is to find the
globally best solution of a model. Nonlinear models are ubiquitous
in many applications and their solution often requires a global
search approach; i.e. for a function f from a set A ⊂ Rn to
the real numbers, an element x0 ∈ A is sought-after, such that
∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application,
the question whether a found solution x0 is not only a local minimum
but a global one is very important.
This article presents a probabilistic approach to determine the
probability of a solution being a global minimum. The approach is
independent of the used global search method and only requires a
limited, convex parameter domain A as well as a Lipschitz continuous
function f whose Lipschitz constant is not needed to be known.
Abstract: The article examines the methods of protection of
citizens' personal data on the Internet using biometric identity
authentication technology. It`s celebrated their potential danger due
to the threat of loss of base biometric templates. To eliminate the
threat of compromised biometric templates is proposed to use neural
networks large and extra-large sizes, which will on the one hand
securely (Highly reliable) to authenticate a person by his biometrics,
and on the other hand make biometrics a person is not available for
observation and understanding. This article also describes in detail
the transformation of personal biometric data access code. It`s formed
the requirements for biometrics converter code for his work with the
images of "Insider," "Stranger", all the "Strangers". It`s analyzed the
effect of the dimension of neural networks on the quality of
converters mystery of biometrics in access code.
Abstract: In the paper a detailed analysis of the dynamic
response of a cooling tower shell to mining tremors originated from
two main regions of mining activity in Poland (Upper Silesian Coal
Basin and Legnica-Glogow Copper District) was presented. The
representative time histories registered in the both regions were used
as ground motion data in calculations of the dynamic response of the
structure. It was proved that the dynamic response of the shell is
strongly dependent not only on the level of vibration amplitudes but
on the dominant frequency range of the mining shock typical for the
mining region as well. Also a vertical component of vibrations
occurred to have considerable influence on the total dynamic
response of the shell. Finally, it turned out that non-uniformity of
kinematic excitation resulting from spatial variety of ground motion
plays a significant role in dynamic analysis of large-dimensional
shells under mining shocks.
Abstract: Real-time embedded systems should benefit from
component-based software engineering to handle complexity and
deal with dependability. In these systems, applications should not
only be logically correct but also behave within time windows.
However, in the current component based software engineering
approaches, a few of component models handles time properties in
a manner that allows efficient analysis and checking at the
architectural level. In this paper, we present a meta-model for
component-based software description that integrates timing
issues. To achieve a complete functional model of software
components, our meta-model focuses on four functional aspects:
interface, static behavior, dynamic behavior, and interaction
protocol. With each aspect we have explicitly associated a time
model. Such a time model can be used to check a component-s
design against certain properties and to compute the timing
properties of component assemblies.
Abstract: Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.
Abstract: One of the most used assumptions in logic programming
and deductive databases is the so-called Closed World Assumption
(CWA), according to which the atoms that cannot be inferred
from the programs are considered to be false (i.e. a pessimistic
assumption). One of the most successful semantics of conventional
logic programs based on the CWA is the well-founded semantics.
However, the CWA is not applicable in all circumstances when
information is handled. That is, the well-founded semantics, if
conventionally defined, would behave inadequately in different cases.
The solution we adopt in this paper is to extend the well-founded
semantics in order for it to be based also on other assumptions. The
basis of (default) negative information in the well-founded semantics
is given by the so-called unfounded sets. We extend this concept
by considering optimistic, pessimistic, skeptical and paraconsistent
assumptions, used to complete missing information from a program.
Our semantics, called extended well-founded semantics, expresses
also imperfect information considered to be missing/incomplete,
uncertain and/or inconsistent, by using bilattices as multivalued
logics. We provide a method of computing the extended well-founded
semantics and show that Kripke-Kleene semantics is captured by
considering a skeptical assumption. We show also that the complexity
of the computation of our semantics is polynomial time.
Abstract: The stab resistance performance of newly developed
fabric composites composed of hexagonal paper honeycombs, filled
with shear thickening fluid (STF), and woven Kevlar® fabric or
UHMPE was investigated in this study. The STF was prepared by
dispersing submicron SiO2 particles into polyethylene glycol (PEG).
Our results indicate that the STF-Kevlar composite possessed lower
penetration depth than that of neat Kevlar. In other words, the
STF-Kevlar composite can attain the same energy level in
stab-resistance test with fewer layers of Kevlar fabrics than that of the
neat Kevlar fabrics. It also indicates that STF can be used for the
fabrication of flexible body armors and can provide improved
protection against stab threats. We found that the stab resistance of the
STF-Kevlar composite increases with the increase of SiO2
concentration in STF. Moreover, the silica particles functionalized
with silane coupling agent can further improve the stab resistance.
Abstract: In this paper, the problem of estimating the optimal
radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple-
output (MIMO) system operating in a Rayleigh fading environment
is examined. The optimisation between the radio capacity
and the theoretically achievable average channel capacity (in the
sense of information theory) per user of a MIMO single-cell SS system
operating in a Rayleigh fading environment is presented. Then,
the spectral efficiency is estimated in terms of the achievable average
channel capacity per user, during the operation over a broadcast
time-varying link, and leads to a simple novel-closed form expression
for the optimal radio capacity value based on the maximization
of the achieved spectral efficiency. Numerical results are presented to
illustrate the proposed analysis.
Abstract: This paper presents an approach which is based on the
use of supervised feed forward neural network, namely multilayer
perceptron (MLP) neural network and finite element method (FEM)
to solve the inverse problem of parameters identification. The
approach is used to identify unknown parameters of ferromagnetic
materials. The methodology used in this study consists in the
simulation of a large number of parameters in a material under test,
using the finite element method (FEM). Both variations in relative
magnetic permeability and electrical conductivity of the material
under test are considered. Then, the obtained results are used to
generate a set of vectors for the training of MLP neural network.
Finally, the obtained neural network is used to evaluate a group of
new materials, simulated by the FEM, but not belonging to the
original dataset. Noisy data, added to the probe measurements is used
to enhance the robustness of the method. The reached results
demonstrate the efficiency of the proposed approach, and encourage
future works on this subject.
Abstract: Because today-s media centric students have adopted
digital as their native form of communication, teachers are having
increasingly difficult time motivating reluctant readers to read and
write. Our research has shown these text-averse individuals can learn
to understand the importance of reading and writing if the instruction
is based on digital narratives. While these students are naturally
attracted to story, they are better at consuming them than creating
them. Therefore, any intervention that utilizes story as its basis needs
to include instruction on the elements of story making. This paper
presents a series of digitally-based tools to identify potential
weaknesses of visually impaired visual learners and to help motivate
these and other media-centric students to select and complete books
that are assigned to them
Abstract: This paper discusses the development of a qualitative
simulator (abbreviated QRiOM) for predicting the behaviour of
organic chemical reactions. The simulation technique is based on the
qualitative process theory (QPT) ontology. The modelling constructs
of QPT embody notions of causality which can be used to explain the
behaviour of a chemical system. The major theme of this work is
that, in a qualitative simulation environment, students are able to
articulate his/her knowledge through the inspection of explanations
generated by software. The implementation languages are Java and
Prolog. The software produces explanation in various forms that
stresses on the causal theories in the chemical system which can be
effectively used to support learning.
Abstract: Chicken feathers were used as biosorbent for Pb
removal from aqueous solution. In this paper, the kinetics and
equilibrium studies at several pH, temperature, and metal
concentration values are reported. For tested conditions, the Pb
sorption capacity of this poultry waste ranged from 0.8 to 8.3 mg/g.
Optimal conditions for Pb removal by chicken feathers have been
identified. Pseudo-first order and pseudo-second order equations
were used to analyze the experimental data. In addition, the sorption
isotherms were fitted to classical Langmuir and Freundlich models.
Finally, thermodynamic parameters for the sorption process have
been determined. In summary, the results showed that chicken
feathers are an alternative and promising sorbent for the treatment of
effluents polluted by Pb ions.
Abstract: Breast carcinoma is the most common form of cancer
in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is
a common method for staging breast carcinoma. The interpretation
of m-FISH images is complicated due to two effects: (i) Spectral
overlap in the emission spectra of fluorochrome marked DNA probes
and (ii) tissue autofluorescence. In this paper hyper-spectral images of
m-FISH samples are used and spectral unmixing is applied to produce
false colour images with higher contrast and better information
content than standard RGB images. The spectral unmixing is realised
by combinations of: Orthogonal Projection Analysis (OPA), Alterating
Least Squares (ALS), Simple-to-use Interactive Self-Modeling
Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied
on the data to reduce tissue autofluorescence and resolve the spectral
overlap in the emission spectra. The results show that spectral unmixing
methods reduce the intensity caused by tissue autofluorescence by
up to 78% and enhance image contrast by algorithmically reducing
the overlap of the emission spectra.
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.