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: The fixed partial dentures are mainly used in the frontal
part of the dental arch because of their great esthetics. There are
several factors that are associated with the stress state created in
ceramic restorations, including: thickness of ceramic layers,
mechanical properties of the materials, elastic modulus of the
supporting substrate material, direction, magnitude and frequency of
applied load, size and location of occlusal contact areas, residual
stresses induced by processing or pores, restoration-cement
interfacial defects and environmental defects. The purpose of this
study is to evaluate the capability of Polarization Sensitive Optical
Coherence Tomography (PSOCT) in detection and analysis of
possible material defects in metal-ceramic and integral ceramic fixed
partial dentures. As a conclusion, it is important to have a non
invasive method to investigate fixed partial prostheses before their
insertion in the oral cavity in order to satisfy the high stress
requirements and the esthetic function.
Abstract: This paper reports on the enhanced photoluminescence
(PL) of nanocomposites through the layered structuring of phosphor
and quantum dot (QD). Green phosphor of Sr2SiO4:Eu, red QDs of
CdSe/CdS/CdZnS/ZnS core-multishell, and thermo-curable resin
were used for this study. Two kinds of composite (layered and mixed)
were prepared, and the schemes for optical energy transfer between
QD and phosphor were suggested and investigated based on PL decay
characteristics. It was found that the layered structure is more effective
than the mixed one in the respects of PL intensity, PL decay and
thermal loss. When this layered nanocomposite (QDs on phosphor) is
used to make white light emitting diode (LED), the brightness is
increased by 37 %, and the color rendering index (CRI) value is raised
to 88.4 compared to the mixed case of 80.4.
Abstract: Previous studies on political budget cycles (PBCs)
implicitly assume the executive has full discretion power over fiscal
policy, neglecting the role of checks and balances of the legislature.
This paper goes beyond traditional PBCs models and sheds light on
the case study of Japan, South Korea, and Taiwan over the 1988-2007
periods. Based on the results, we find no evidence of electoral impacts
on the public expenditures in South Korean and Taiwan's
congressional elections. We also noted that PBCs are found on
Taiwan-s government expenditures during our sample periods.
Furthermore, the results also show that Japan-s legislature has a
significant checks and balances on government-s expenditures.
However, empirical results show that the legislature veto player in
Taiwan neither has effect on the reduction of public expenditures, nor
has the moderating effect over Taiwan-s political budget cycles, albeit
that they are statistically insignificant.We suggest that the existence of
PBCs in Taiwan is due to a weaker systemof checks and balances. Our
conjecture is that Taiwan either has no legislative veto player or has
observed low compliance to the law during the time period examined
in our study.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
relationship between the minimum direct and indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of direct and indirect jerks are found using the dynamic optimization
methods together with the numerical approximation. This is to allow
us to simulate and compare visually and statistically the time history
of control inputs employed by minimum direct and indirect jerk
designs. By considering minimum indirect jerk problem, the
numerical solution becomes much easier and yields to the similar
results as minimum direct jerk problem.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: In this paper, an analytical approach is used to study the coupled lateral-torsional vibrations of laminated composite beam. It is known that in such structures due to the fibers orientation in various layers, any lateral displacement will produce a twisting moment. This phenomenon is modeled by the bending-twisting material coupling rigidity and its main feature is the coupling of lateral and torsional vibrations. In addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies. Then, the governing differential equations are derived using the Hamilton-s principle and the mathematical model matches the Timoshenko beam model when neglecting the effect of bending-twisting rigidity. The equations of motion which form a system of three coupled PDEs are solved analytically to study the free vibrations of the beam in lateral and rotational modes due to the bending, as well as the torsional mode caused by twisting. The analytic solution is carried out in three steps: 1) assuming synchronous motion for the kinematic variables which are the lateral, rotational and torsional displacements, 2) solving the ensuing eigenvalue problem which contains three coupled second order ODEs and 3) imposing different boundary conditions related to combinations of simply, clamped and free end conditions. The resulting natural frequencies and mode shapes are compared with similar results in the literature and good agreement is achieved.
Abstract: In this paper, we present a maintenance model of a
two-unit series system with economic dependence. Unit#1 which is
considered to be more expensive and more important, is subject to
condition monitoring (CM) at equidistant, discrete time epochs and
unit#2, which is not subject to CM has a general lifetime distribution.
The multivariate observation vectors obtained through condition
monitoring carry partial information about the hidden state of unit#1,
which can be in a healthy or a warning state while operating. Only the
failure state is assumed to be observable for both units. The objective
is to find an optimal opportunistic maintenance policy minimizing
the long-run expected average cost per unit time. The problem
is formulated and solved in the partially observable semi-Markov
decision process framework. An effective computational algorithm
for finding the optimal policy and the minimum average cost is
developed, illustrated by a numerical example.
Abstract: Mobile ad-hoc networks (MANETs) are a form of
wireless networks which do not require a base station for providing
network connectivity. Mobile ad-hoc networks have many
characteristics which distinguish them from other wireless networks
which make routing in such networks a challenging task. Cluster
based routing is one of the routing schemes for MANETs in which
various clusters of mobile nodes are formed with each cluster having
its own clusterhead which is responsible for routing among clusters.
In this paper we have proposed and implemented a distributed
weighted clustering algorithm for MANETs. This approach is based
on combined weight metric that takes into account several system
parameters like the node degree, transmission range, energy and
mobility of the nodes. We have evaluated the performance of
proposed scheme through simulation in various network situations.
Simulation results show that proposed scheme outperforms the
original distributed weighted clustering algorithm (DWCA).
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: Currently is characterized production engineering
together with the integration of industrial automation and robotics
such very quick view of to manufacture the products. The production
range is continuously changing, expanding and producers have to be
flexible in this regard. It means that need to offer production
possibilities, which can respond to the quick change. Engineering
product development is focused on supporting CAD software, such
systems are mainly used for product design. That manufacturers are
competitive, it should be kept procured machines made available
capable of responding to output flexibility. In response to that
problem is the development of flexible manufacturing systems,
consisting of various automated systems. The integration of flexible
manufacturing systems and subunits together with product design and
of engineering is a possible solution for this issue. Integration is
possible through the implementation of CIM systems. Such a solution
and finding a hyphen between CAD and procurement system ICIM
3000 from Festo Co. is engaged in the research project and this
contribution. This can be designed the products in CAD systems and
watch the manufacturing process from order to shipping by the
development of methods and processes of integration, This can be
modeled in CAD systems products and watch the manufacturing
process from order to shipping to develop methods and processes of
integration, which will improve support for product design
parameters by monitoring of the production process, by creating of
programs for production using the CAD and therefore accelerates the
a total of process from design to implementation.
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: This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.
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: In the present study, the incorporation of graphene
into blends of acrylonitrile-butadiene-styrene terpolymer with
polypropylene (ABS/PP) was investigated focusing on the
improvement of their thermomechanical characteristics and the effect
on their rheological behavior. The blends were prepared by melt
mixing in a twin-screw extruder and were characterized by measuring
the MFI as well as by performing DSC, TGA and mechanical tests.
The addition of graphene to ABS/PP blends tends to increase their
melt viscosity, due to the confinement of polymer chains motion.
Also, graphene causes an increment of the crystallization temperature
(Tc), especially in blends with higher PP content, because of the
reduction of surface energy of PP nucleation, which is a consequence
of the attachment of PP chains to the surface of graphene through the
intermolecular CH-π interaction. Moreover, the above nanofiller
improves the thermal stability of PP and increases the residue of
thermal degradation at all the investigated compositions of blends,
due to the thermal isolation effect and the mass transport barrier
effect. Regarding the mechanical properties, the addition of graphene
improves the elastic modulus, because of its intrinsic mechanical
characteristics and its rigidity, and this effect is particularly strong in
the case of pure PP.
Abstract: In this report we present a rule-based approach to
detect anomalous telephone calls. The method described here uses
subscriber usage CDR (call detail record) data sampled over two
observation periods: study period and test period. The study period
contains call records of customers- non-anomalous behaviour.
Customers are first grouped according to their similar usage
behaviour (like, average number of local calls per week, etc). For
customers in each group, we develop a probabilistic model to describe
their usage. Next, we use maximum likelihood estimation (MLE) to
estimate the parameters of the calling behaviour. Then we determine
thresholds by calculating acceptable change within a group. MLE is
used on the data in the test period to estimate the parameters of the
calling behaviour. These parameters are compared against thresholds.
Any deviation beyond the threshold is used to raise an alarm. This
method has the advantage of identifying local anomalies as compared
to techniques which identify global anomalies. The method is tested
for 90 days of study data and 10 days of test data of telecom
customers. For medium to large deviations in the data in test window,
the method is able to identify 90% of anomalous usage with less than
1% false alarm rate.
Abstract: This paper presents an integrated model that
automatically measures the change of rivers, damage area of bridge
surroundings, and change of vegetation. The proposed model is on the
basis of a neurofuzzy mechanism enhanced by SOM optimization
algorithm, and also includes three functions to deal with river imagery.
High resolution imagery from FORMOSAT-2 satellite taken before
and after the invasion period is adopted. By randomly selecting a
bridge out of 129 destroyed bridges, the recognition results show that
the average width has increased 66%. The ruined segment of the
bridge is located exactly at the most scour region. The vegetation
coverage has also reduced to nearly 90% of the original. The results
yielded from the proposed model demonstrate a pinpoint accuracy rate
at 99.94%. This study brings up a successful tool not only for
large-scale damage assessment but for precise measurement to
disasters.
Abstract: Atherosclerosis was identified as a chronic inflammatory process resulting from interactions between plasma lipoproteins, cellular components (monocyte, macrophages, T lymphocytes, endothelial cells and smooth muscle cells) and the extracellular matrix of the arterial wall. Several types of genes were known to express during formation of atherosclerosis. This study is carried out to identify unknown differentially expressed gene (DEG) in atherogenesis. Rabbit’s aorta tissues were stained by H&E for histomorphology. GeneFishing™ PCR analysis was performed from total RNA extracted from the aorta tissues. The DNA fragment from DEG was cloned, sequenced and validated by Real-time PCR. Histomorphology showed intimal thickening in the aorta. DEG detected from ACP-41 was identified as cathepsin B gene and showed upregulation at week-8 and week-12 of atherogenesis. Therefore, ACP-based GeneFishing™ PCR facilitated identification of cathepsin B gene which was differentially expressed during development of atherosclerosis.
Abstract: The interaction of tunneling or mining with
groundwater has become a very relevant problem not only due to the
need to guarantee the safety of workers and to assure the efficiency of
the tunnel drainage systems, but also to safeguard water resources
from impoverishment and pollution risk. Therefore it is very
important to forecast the drainage processes (i.e., the evaluation of
drained discharge and drawdown caused by the excavation). The aim
of this study was to know better the system and to quantify the flow
drained from the Fontane mines, located in Val Germanasca (Turin,
Italy). This allowed to understand the hydrogeological local changes
in time. The work has therefore been structured as follows: the
reconstruction of the conceptual model with the geological,
hydrogeological and geological-structural study; the calculation of
the tunnel inflows (through the use of structural methods) and the
comparison with the measured flow rates; the water balance at the
basin scale. In this way it was possible to understand what are the
relationships between rainfall, groundwater level variations and the
effect of the presence of tunnels as a means of draining water.
Subsequently, it the effects produced by the excavation of the mining
tunnels was quantified, through numerical modeling. In particular,
the modeling made it possible to observe the drawdown variation as a
function of number, excavation depth and different mines linings.
Abstract: This paper presents an experimental investigation on
the machinability of laser-sintered material using small ball end mill focusing on wear mechanisms. Laser-sintered material was produced
by irradiating a laser beam on a layer of loose fine SCM-Ni-Cu powder. Bulk carbon steel JIS S55C was selected as a reference steel.
The effects of powder consolidation mechanisms and unsintered
powder on the tool life and wear mechanisms were carried out. Results indicated that tool life in cutting laser-sintered material is
lower than that in cutting JIS S55C. Adhesion of the work material and chipping were the main wear mechanisms of the ball end mill in
cutting laser-sintered material. Cutting with the unsintered powder
surrounding the tool and laser-sintered material had caused major fracture on the cutting edge.