Abstract: The microbiological and physicochemical
characteristics of wetland soils in Eket Local Government Area were
studied between May 2001 and June 2003. Total heterotrophic
bacterial counts (THBC), total fungal counts (TFC), and total
actinomycetes counts (TAC) were determined from soil samples
taken from four locations at two depths in the wet and dry seasons.
Microbial isolates were characterized and identified. Particle size and
chemical parameters were also determined using standard methods.
THBC ranged from 5.2 (+0.17) x106 to 1.7 (+0.18) x107 cfu/g and
from 2.4 (+0.02) x106 to 1.4 (+0.04) x107cfu/g in the wet and dry
seasons, respectively. TFC ranged from 1.8 (+0.03) x106 to 6.6 (+
0.18) x106 cfu/g and from 1.0 (+0.04) x106 to 4.2 (+ 0.01) x106 cfu/g
in the wet and dry seasons, respectively .TAC ranged from 1.2
(+0.53) x106 to 6.0 (+0.05) x106 cfu/g and from 0.6 (+0.01) x106 to
3.2 (+ 0.12) x106 cfu/g in the wet and dry season, respectively.
Acinetobacter, Alcaligenes, Arthrobacter, Bacillus, Beijerinckja,
Enterobacter, Micrococcus, Flavobacterium, Serratia, Enterococcus,
and Pseudomonas species were predominant bacteria while
Aspergillus, Fusarium, Mucor, Penicillium, and Rhizopus were the
dominant fungal genera isolated. Streptomyces and Norcadia were
the actinomycetes genera isolated. The particle size analysis showed
high sand fraction but low silt and clay. The pH and % organic
matter were generally acidic and low, respectively at all locations.
Calcium dominated the exchangeable bases with low electrical
conductivity and micronutrients. These results provide the baseline
data of Eket wetland soils for its management for sustainable
agriculture.
Abstract: Phase-Contrast MR imaging methods are widely used
for measurement of blood flow velocity components. Also there are
some other tools such as CT and Ultrasound for velocity map
detection in intravascular studies. These data are used in deriving
flow characteristics. Some clinical applications are investigated
which use pressure distribution in diagnosis of intravascular disorders
such as vascular stenosis. In this paper an approach to the problem of
measurement of intravascular pressure field by using velocity field
obtained from flow images is proposed. The method presented in this
paper uses an algorithm to calculate nonlinear equations of Navier-
Stokes, assuming blood as an incompressible and Newtonian fluid.
Flow images usually suffer the lack of spatial resolution. Our
attempt is to consider the effect of spatial resolution on the pressure
distribution estimated from this method. In order to achieve this aim,
velocity map of a numerical phantom is derived at six different
spatial resolutions. To determine the effects of vascular stenoses on
pressure distribution, a stenotic phantom geometry is considered. A
comparison between the pressure distribution obtained from the
phantom and the pressure resulted from the algorithm is presented. In
this regard we also compared the effects of collocated and staggered
computational grids on the pressure distribution resulted from this
algorithm.
Abstract: The production of a plant can be measured in terms of
seeds. The generation of seeds plays a critical role in our social and
daily life. The fruit production which generates seeds, depends on the
various parameters of the plant, such as shoot length, leaf number,
root length, root number, etc When the plant is growing, some leaves
may be lost and some new leaves may appear. It is very difficult to
use the number of leaves of the tree to calculate the growth of the
plant.. It is also cumbersome to measure the number of roots and
length of growth of root in several time instances continuously after
certain initial period of time, because roots grow deeper and deeper
under ground in course of time. On the contrary, the shoot length of
the tree grows in course of time which can be measured in different
time instances. So the growth of the plant can be measured using the
data of shoot length which are measured at different time instances
after plantation. The environmental parameters like temperature, rain
fall, humidity and pollution are also play some role in production of
yield. The soil, crop and distance management are taken care to
produce maximum amount of yields of plant. The data of the growth
of shoot length of some mustard plant at the initial stage (7,14,21 &
28 days after plantation) is available from the statistical survey by a
group of scientists under the supervision of Prof. Dilip De. In this
paper, initial shoot length of Ken( one type of mustard plant) has
been used as an initial data. The statistical models, the methods of
fuzzy logic and neural network have been tested on this mustard
plant and based on error analysis (calculation of average error) that
model with minimum error has been selected and can be used for the
assessment of shoot length at maturity. Finally, all these methods
have been tested with other type of mustard plants and the particular
soft computing model with the minimum error of all types has been
selected for calculating the predicted data of growth of shoot length.
The shoot length at the stage of maturity of all types of mustard
plants has been calculated using the statistical method on the
predicted data of shoot length.
Abstract: This paper presents a new heuristic algorithm useful
for long-term planning of survivable WDM networks. A multi-period
model is formulated that combines network topology design and
capacity expansion. The ability to determine network expansion
schedules of this type becomes increasingly important to the
telecommunications industry and to its customers. The solution
technique consists of a Genetic Algorithm that allows generating
several network alternatives for each time period simultaneously and
shortest-path techniques to deduce from these alternatives a least-cost
network expansion plan over all time periods. The multi-period
planning approach is illustrated on a realistic network example.
Extensive simulations on a wide range of problem instances are
carried out to assess the cost savings that can be expected by
choosing a multi-period planning approach instead of an iterative
network expansion design method.
Abstract: The paper presents a technique suitable in robot
vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods
are based on the correspondence of image features established at a
training step and exactly the same image features extracted at the
execution step, for a different object pose. When such a
correspondence is not feasible because of the lack of specific features
a new method is proposed. In the first step the method computes
from two views the 3D pose of feature points. Subsequently, using a
registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted
at the training phase. The result is a Euclidean transform which have
to be used by robot head for reorientation at execution step.
Abstract: This article illustrates a model selection management approach for virtual prototypes in interactive simulations. In those numerical simulations, the virtual prototype and its environment are modelled as a multiagent system, where every entity (prototype,human, etc.) is modelled as an agent. In particular, virtual prototyp ingagents that provide mathematical models of mechanical behaviour inform of computational methods are considered. This work argues that selection of an appropriate model in a changing environment,supported by models? characteristics, can be managed by the deter-mination a priori of specific exploitation and performance measures of virtual prototype models. As different models exist to represent a single phenomenon, it is not always possible to select the best one under all possible circumstances of the environment. Instead the most appropriate shall be selecting according to the use case. The proposed approach consists in identifying relevant metrics or indicators for each group of models (e.g. entity models, global model), formulate their qualification, analyse the performance, and apply the qualification criteria. Then, a model can be selected based on the performance prediction obtained from its qualification. The authors hope that this approach will not only help to inform engineers and researchers about another approach for selecting virtual prototype models, but also assist virtual prototype engineers in the systematic or automatic model selection.
Abstract: In this study, the powders of Ni and Ti with 50.5 at.%
Ni for 12 h were blended and cold pressed at the different pressures
(50, 75 and100 MPa).The porous product obtained after Ni-Ti
compacts were synthesized by SHS (self-propagating hightemperature
synthesis) in the different preheating temperatures (200,
250 and 300oC) and heating rates (30, 60 and 90oC/min). The effects
of the pressure, preheating temperature and heating rate were
investigated on biocompatibility in vivo. The porosity in the
synthesized products was in the range of 50.7–59.7 vol. %. The
pressure, preheating temperature and heating rate were found to have
an important effect on the biocompatibility in-vivo of the synthesized
products. Max. fibrotic tissue within the porous implant was found in
vivo periods (6 months), in which compacting pressure 100MPa.
Abstract: We report on the development of a model to
understand why the range of experience with respect to HIV
infection is so diverse, especially with respect to the latency period.
To investigate this, an agent-based approach is used to extract highlevel
behaviour which cannot be described analytically from the set
of interaction rules at the cellular level. A network of independent
matrices mimics the chain of lymph nodes. Dealing with massively
multi-agent systems requires major computational effort. However,
parallelisation methods are a natural consequence and advantage of
the multi-agent approach and, using the MPI library, are here
implemented, tested and optimized. Our current focus is on the
various implementations of the data transfer across the network.
Three communications strategies are proposed and tested, showing
that the most efficient approach is communication based on the
natural lymph-network connectivity.
Abstract: Nowadays, organizing a repository of documents and
resources for learning on a special field as Information Technology
(IT), together with search techniques based on domain knowledge or
document-s content is an urgent need in practice of teaching, learning
and researching. There have been several works related to methods of
organization and search by content. However, the results are still
limited and insufficient to meet user-s demand for semantic
document retrieval. This paper presents a solution for the
organization of a repository that supports semantic representation and
processing in search. The proposed solution is a model which
integrates components such as an ontology describing domain
knowledge, a database of document repository, semantic
representation for documents and a file system; with problems,
semantic processing techniques and advanced search techniques
based on measuring semantic similarity. The solution is applied to
build a IT learning materials management system of a university with
semantic search function serving students, teachers, and manager as
well. The application has been implemented, tested at the University
of Information Technology, Ho Chi Minh City, Vietnam and has
achieved good results.
Abstract: This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.
Abstract: Soil chemical and physical properties have important
roles in compartment of the environment and agricultural
sustainability and human health. The objectives of this research is
determination of spatial distribution patterns of Cd, Zn, K, pH, TNV,
organic material and electrical conductivity (EC) in agricultural soils
of Natanz region in Esfehan province. In this study geostatistic and
non-geostatistic methods were used for prediction of spatial
distribution of these parameters. 64 composite soils samples were
taken at 0-20 cm depth. The study area is located in south of
NATANZ agricultural lands with area of 21660 hectares. Spatial
distribution of Cd, Zn, K, pH, TNV, organic material and electrical
conductivity (EC) was determined using geostatistic and geographic
information system. Results showed that Cd, pH, TNV and K data
has normal distribution and Zn, OC and EC data had not normal
distribution. Kriging, Inverse Distance Weighting (IDW), Local
Polynomial Interpolation (LPI) and Redial Basis functions (RBF)
methods were used to interpolation. Trend analysis showed that
organic carbon in north-south and east to west did not have trend
while K and TNV had second degree trend. We used some error
measurements include, mean absolute error(MAE), mean squared
error (MSE) and mean biased error(MBE). Ordinary
kriging(exponential model), LPI(Local polynomial interpolation),
RBF(radial basis functions) and IDW methods have been chosen as
the best methods to interpolating of the soil parameters. Prediction
maps by disjunctive kriging was shown that in whole study area was
intensive shortage of organic matter and more than 63.4 percent of
study area had shortage of K amount.
Abstract: The assessment of surface waters in Enugu metropolis
for fecal coliform bacteria was undertaken. Enugu urban was divided
into three areas (A1, A2 and A3), and fecal coliform bacteria
analysed in the surface waters found in these areas for four years
(2005-2008). The plate count method was used for the analyses. Data
generated were subjected to statistical tests involving; Normality test,
Homogeneity of variance test, correlation test, and tolerance limit
test. The influence of seasonality and pollution trends were
investigated using time series plots. Results from the tolerance limit
test at 95% coverage with 95% confidence, and with respect to EU
maximum permissible concentration show that the three areas suffer
from fecal coliform pollution. To this end, remediation procedure
involving the use of saw-dust extracts from three woods namely;
Chlorophora-Excelsa (C-Excelsa),Khayan-Senegalensis,(CSenegalensis)
and Erythrophylum-Ivorensis (E-Ivorensis) in
controlling the coliforms was studied. Results show that mixture of
the acetone extracts of the woods show the most effective
antibacterial inhibitory activities (26.00mm zone of inhibition)
against E-coli. Methanol extract mixture of the three woods gave best
inhibitory activity (26.00mm zone of inhibition) against S-areus, and
25.00mm zones of inhibition against E-Aerogenes. The aqueous
extracts mixture gave acceptable zones of inhibitions against the
three bacteria organisms.
Abstract: It is well known that Logistic Regression is the gold
standard method for predicting clinical outcome, especially
predicting risk of mortality. In this paper, the Decision Tree method
has been proposed to solve specific problems that commonly use
Logistic Regression as a solution. The Biochemistry and
Haematology Outcome Model (BHOM) dataset obtained from
Portsmouth NHS Hospital from 1 January to 31 December 2001 was
divided into four subsets. One subset of training data was used to
generate a model, and the model obtained was then applied to three
testing datasets. The performance of each model from both methods
was then compared using calibration (the χ2 test or chi-test) and
discrimination (area under ROC curve or c-index). The experiment
presented that both methods have reasonable results in the case of the
c-index. However, in some cases the calibration value (χ2) obtained
quite a high result. After conducting experiments and investigating
the advantages and disadvantages of each method, we can conclude
that Decision Trees can be seen as a worthy alternative to Logistic
Regression in the area of Data Mining.
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: Online auctions are not very popular in Croatia. The
main reason for this is a very limited number of services which can
be used by Croatian users. Until recent times, even selling through
the most popular online auction site eBay wasn't possible because
PayPal services could not make payment to bank or debit card
accounts in Croatia. Furthermore, many foreign sellers do not offer
delivery of their products to Croatia which means that large
quantities of goods initially offered on such sites are not available.
With that in mind, it is necessary to analyze the buying and selling
habits of Croatian users and existing online auction sites, both
Croatian and foreign, and create a model for new domestic site. This
site will have to exploit every positive aspect of existing models and
neutralize every negative perception indicated by users in the survey
so that, hopefully, it would attract new users.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Internet security attack could endanger the privacy of
World Wide Web users and the integrity of their data. The attack can
be carried out on today's most secure systems- browsers, including
Netscape Navigator and Microsoft Internet Explorer. There are too
many types, methods and mechanisms of attack where new attack
techniques and exploits are constantly being developed and
discovered. In this paper, various types of internet security attack
mechanisms are explored and it is pointed out that when different
types of attacks are combined together, network security can suffer
disastrous consequences.
Abstract: The Integrated Performance Modelling Environment
(IPME) is a powerful simulation engine for task simulation and
performance analysis. However, it has no high level cognition such
as memory and reasoning for complex simulation. This article
introduces a knowledge representation and reasoning scheme that can
accommodate uncertainty in simulations of military personnel with
IPME. This approach demonstrates how advanced reasoning models
that support similarity-based associative process, rule-based abstract
process, multiple reasoning methods and real-time interaction can be
integrated with conventional task network modelling to provide
greater functionality and flexibility when modelling operator
performance.
Abstract: Routing places an important role in determining the
quality of service in wireless networks. The routing methods adopted
in wireless networks have many drawbacks. This paper aims to
review the current routing methods used in wireless networks. This
paper proposes an innovative solution to overcome the problems in
routing. This solution is aimed at improving the Quality of Service.
This solution is different from others as it involves the resuage of the
part of the virtual circuits. This improvement in quality of service is
important especially in propagation of multimedia applications like
video, animations etc. So it is the dire need to propose a new solution
to improve the quality of service in ATM wireless networks for
multimedia applications especially during this era of multimedia
based applications.
Abstract: In seismic survey, the information regarding the
velocity of compression wave (Vp) as well as shear wave (Vs) are
very useful especially during the seismic interpretation. Previous
studies showed that both Vp and Vs determined by above methods
are totally different with respect to each other but offered good
approximation. In this study, both Vp and Vs of consolidated granite
rock were studied by using ultrasonic testing method and seismic
refraction method. In ultrasonic testing, two different condition of
rock are used which is dry and wet. The differences between Vp and
Vs getting by using ultrasonic testing and seismic refraction were
investigated and studied. The effect of water content in granite rock
towards the value of Vp and Vs during ultrasonic testing are also
measured. Within this work, the tolerance of the differences between
the velocity of seismic wave getting from ultrasonic testing and the
velocity of seismic wave getting from seismic refraction are also
measured and investigated.