Abstract: Nodes in mobile Ad Hoc Network (MANET) do not
rely on a central infrastructure but relay packets originated by other
nodes. Mobile ad hoc networks can work properly only if the
participating nodes collaborate in routing and forwarding. For
individual nodes it might be advantageous not to collaborate, though.
In this conceptual paper we propose a new approach based on
relationship among the nodes which makes them to cooperate in an
Adhoc environment. The trust unit is used to calculate the trust
values of each node in the network. The calculated trust values are
being used by the relationship estimator to determine the relationship
status of nodes. The proposed enhanced protocol was compared with
the standard DSR protocol and the results are analyzed using the
network simulator-2.
Abstract: Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.
Abstract: Today, money laundering (ML) poses a serious threat
not only to financial institutions but also to the nation. This criminal
activity is becoming more and more sophisticated and seems to have
moved from the cliché of drug trafficking to financing terrorism and
surely not forgetting personal gain. Most international financial
institutions have been implementing anti-money laundering solutions
(AML) to fight investment fraud. However, traditional investigative
techniques consume numerous man-hours. Recently, data mining
approaches have been developed and are considered as well-suited
techniques for detecting ML activities. Within the scope of a
collaboration project for the purpose of developing a new solution for
the AML Units in an international investment bank, we proposed a
data mining-based solution for AML. In this paper, we present a
heuristics approach to improve the performance for this solution. We
also show some preliminary results associated with this method on
analysing transaction datasets.
Abstract: We demonstrate the synthesis of intermediary views
within a sequence of color encoded, materials discriminating, X-ray
images that exhibit animated depth in a visual display. During the
image acquisition process, the requirement for a linear X-ray detector
array is replaced by synthetic image. Scale Invariant Feature
Transform, SIFT, in combination with material segmented morphing
is employed to produce synthetic imagery. A quantitative analysis of
the feature matching performance of the SIFT is presented along with
a comparative study of the synthetic imagery. We show that the total
number of matches produced by SIFT reduces as the angular
separation between the generating views increases. This effect is
accompanied by an increase in the total number of synthetic pixel
errors. The trends observed are obtained from 15 different luggage
items. This programme of research is in collaboration with the UK
Home Office and the US Dept. of Homeland Security.
Abstract: Leave of absence is important in maintaining a good
status of human resource quality. Allowing the employees temporarily
free from the routine assignments can vitalize the workers- morality
and productivity. This is particularly critical to secure a satisfactory
service quality for healthcare professionals of which were typically
featured with labor intensive and complicated works to perform. As
one of the veteran hospitals that were found and operated by the
Veteran Department of Taiwan, the nursing staff of the case hospital
was squeezed to an extreme minimum level under the pressure of a
tight budgeting. Leave of absence on schedule became extremely
difficult, especially for the intensive care units (ICU), in which
required close monitoring over the cared patients, and that had more
easily driven the ICU nurses nervous. Even worse, the deferred leaves
were more than 10 days at any time in the ICU because of a fluctuating
occupancy. As a result, these had brought a bad setback to this
particular nursing team, and consequently defeated the job
performance and service quality. To solve this problem and
accordingly to strengthen their morality, a project team was organized
across different departments specific for this. Sufficient information
regarding jobs and positions requirements, labor resources, and actual
working hours in detail were collected and analyzed in the team
meetings. Several alternatives were finalized. These included job
rotating, job combination, leave on impromptu and cross-departmental
redeployment. Consequently, the deferred leave days sharply reduced
70% to a level of 3 or less days. This improvement had not only
provided good shelter for the ICU nurses that improved their job
performance and patient safety but also encouraged the nurses active
participating of a project and learned the skills of solving problems
with colleagues.
Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: Reinforced concrete crash barriers used in road traffic
must meet a number of criteria. Crash barriers are laid lengthwise,
one behind another, and joined using specially designed steel locks.
While developing BSV reinforced concrete crash barriers (type
ŽPSV), experiments and calculations aimed to optimize the shape of
a newly designed lock and the reinforcement quantity and
distribution in a crash barrier were carried out. The tension carrying
capacity of two parallelly joined locks was solved experimentally.
Based on the performed experiments, adjustments of nonlinear
properties of steel were performed in the calculations. The obtained
results served as a basis to optimize the lock design using a
computational model that takes into account the plastic behaviour of
steel and the influence of the surrounding concrete [6]. The response
to the vehicle impact has been analyzed using a specially elaborated
complex computational model, comprising both the nonlinear model
of the damping wall or crash barrier and the detailed model of the
vehicle [7].
Abstract: This study investigates the in-situ regeneration of deactivated Pt-Pd catalyst in a laboratory-scale catalysis reactor. Different regeneration conditions are tested and the activity and characteristics of regenerated catalysts are analyzed. Experimental results show that the conversion efficiencies of C3H6 by different regenerated Pt-Pd catalysts were significantly improved from 77%, 55% and 41% to 86%, 98% and 99%, respectively. The best regeneration conditions was 52ppm ozone, 500oC, and 10min. Regeneration temperature has more influences than ozone concentration and regeneration time. With the comparisons of characteristics of deactivated catalyst and regenerated catalyst, the major poison species (carbon, metals, chloride, and sulfate) on the spent catalysts can be effectively removed by ozone regeneration.
Abstract: We consider herein a concise view of discreet
programming models and methods. There has been conducted the
models and methods analysis. On the basis of discreet programming
models there has been elaborated and offered a new class of
problems, i.e. block-symmetry models and methods of applied tasks
statements and solutions.
Abstract: This paper attempts to explore a new method to
improve the teaching of algorithmic for beginners. It is well known
that algorithmic is a difficult field to teach for teacher and complex to
assimilate for learner. These difficulties are due to intrinsic
characteristics of this field and to the manner that teachers (the
majority) apprehend its bases. However, in a Technology Enhanced
Learning environment (TEL), assessment, which is important and
indispensable, is the most delicate phase to implement, for all
problems that generate (noise...). Our objective registers in the
confluence of these two axes. For this purpose, EASEL focused
essentially to elaborate an assessment approach of algorithmic
competences in a TEL environment. This approach consists in
modeling an algorithmic solution according to basic and elementary
operations which let learner draw his/her own step with all autonomy
and independently to any programming language. This approach
assures a trilateral assessment: summative, formative and diagnostic
assessment.
Abstract: This paper deals with the status of solid waste pollution in touristic spots of North coastal Andhra Pradesh. Case studies of Eco tourism, cultural tourism and pilgrim tourism are elaborately discussed and the study is based on both primary and secondary data. Data collection includes field collection of solid waste, semi structured interviews and observation of tourists. Results indicate generation of 72% Non biodegradable material in Eco touristic places like RK beach Visakhapatnam, Araku Valley. Pydithalli Jathra is a famous cultural touristic attraction and more than one lakh people converge here. The solid waste at this spot includes 20% coconut shells, 50% plastic bottles and covers, 20% Banana peelings and remaining are food materials. Radhasapthami is the most important festival celebrated at famous sun temple Arasavalli of Srikakulam. Here solid waste includes 50% water bottles, plastic covers, 10% papers, 10% hair, 30% left out food material and Banana peelings.
Abstract: Neoclassical and functionalist explanations of self
organization in multiagent systems have been criticized on several accounts including unrealistic explication of overadapted agents and
failure to resolve problems of externality. The paper outlines a more
elaborate and dynamic model that is capable of resolving these dilemmas. An illustrative example where behavioral diversity is
cobred in a repeated nonzero sum task via evolutionary computing is
presented.
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: China apparel industry, which is deeply embedded in
the global production network (GPN), faces the dual pressures of
social upgrading and economic upgrading. Based on the survey in
Ningbo apparel cluster, the paper shows the state of corporate social
responsibility (CSR) in China apparel industry is better than before.
And the investigation indicates that the firms who practice CSR
actively perform better both socially and economically than those who
inactively. The research demonstrates that CSR can be an initial
capital rather than cost, and “doing well by doing good" is also existed
in labor intensive industry.
Abstract: There is wide range of scientific workflow systems
today, each one designed to resolve problems at a specific level. In
large collaborative projects, it is often necessary to recognize the
heterogeneous workflow systems already in use by various partners
and any potential collaboration between these systems requires
workflow interoperability. Publish/Subscribe Scientific Workflow
Interoperability Framework (PS-SWIF) approach was proposed to
achieve workflow interoperability among workflow systems. This
paper evaluates the PS-SWIF approach and its system to achieve
workflow interoperability using Web Services with asynchronous
notification messages represented by WS-Eventing standard. This
experiment covers different types of communication models provided
by Workflow Management Coalition (WfMC). These models are:
Chained processes, Nested synchronous sub-processes, Event
synchronous sub-processes, and Nested sub-processes
(Polling/Deferred Synchronous). Also, this experiment shows the
flexibility and simplicity of the PS-SWIF approach when applied to a
variety of workflow systems (Triana, Taverna, Kepler) in local and
remote environments.
Abstract: Vinegar is a precious food additive and complement as well as effective preservative against food spoilage. Recently traditional vinegar production has been improved using various natural substrates and fruits such as grape, palm, cherry, coconut, date, sugarcane, rice and balsam. These neoclassical fermentations resulted in several vinegar types with different tastes, fragrances and nutritional values because of applying various acetic acid bacteria as starters. Acetic acid bacteria include genera Acetobacter, Gluconacetobacter and Gluconobacter according to latest edition of Bergy-s Manual of Systematic Bacteriology that classifies genera on the basis of their 16s RNA differences. Acetobacter spp as the main vinegar starters belong to family Acetobacteraceae that are gram negative obligate aerobes, chemoorganotrophic bacilli that are oxidase negative and oxidize ethanol to acetic acid. In this research we isolated and identified a native Acetobacter strain with high acetic acid productivity and tolerance against high ethanol concentrations from Iranian peach as a summer delicious fruit that is very susceptible to food spoilage and decay. We used selective and specific laboratorial culture media such as Standard GYC, Frateur and Carr medium. Also we used a new industrial culture medium and a miniature fermentor with a new aeration system innovated by Pars Yeema Biotechnologists Co., Isfahan Science and Technology Town (ISTT), Isfahan, Iran. The isolated strain was successfully cultivated in modified Carr media with 2.5% and 5% ethanol simultaneously in high temperatures, 34 - 40º C after 96 hours of incubation period. We showed that the increase of ethanol concentration resulted in rising of strain sensitivity to high temperature. In conclusion we isolated and characterized a new Acetobacter strain from Iranian peach that could be considered as a potential strain for production of a new vinegar type, peach vinegar, with a delicious taste and advantageous nutritional value in food biotechnology and industrial microbiology.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: Solar energy is not only sustainable but also a clean
alternative to be used as source of high temperature heat for many
processes and power generation. However, the major drawback of
solar energy is its transient nature. Especially in solar
thermochemical processing, it is crucial to maintain constant or semiconstant
temperatures inside the solar reactor. In our laboratory, we
have developed a mechanism allowing us to achieve semi-constant
temperature inside the solar reactor. In this paper, we introduce the
concept along with some updated designs and provide the optical
analysis of the concept under various incoming flux.
Abstract: This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.
Abstract: The tracing methods determine the contribution the
power system sources have in their supplying. The methods can be used
to assess the transmission prices, but also to recover the transmission
fixed cost. In this paper is presented the influence of the modification of
commons structure has on the specific price of transfer. The operator
must make use of a few basic principles about allocation. Most
tracing methods are based on the proportional sharing principle. In this
paper Kirschen method is used. In order to illustrate this method, the 25-
bus test system is used, elaborated within the Electrical Power
Engineering Department, from Timisoara, Romania.