Abstract: Ontology Matching is a task needed in various applica-tions, for example for comparison or merging purposes. In literature,many algorithms solving the matching problem can be found, butmost of them do not consider instances at all. Mappings are deter-mined by calculating the string-similarity of labels, by recognizinglinguistic word relations (synonyms, subsumptions etc.) or by ana-lyzing the (graph) structure. Due to the facts that instances are oftenmodeled within the ontology and that the set of instances describesthe meaning of the concepts better than their meta information,instances should definitely be incorporated into the matching process.In this paper several novel instance-based matching algorithms arepresented which enhance the quality of matching results obtainedwith common concept-based methods. Different kinds of formalismsare use to classify concepts on account of their instances and finallyto compare the concepts directly.KeywordsInstances, Ontology Matching, Semantic Web
Abstract: The prevalence of non organic constipation differs
from country to country and the reliability of the estimate rates is
uncertain. Moreover, the clinical relevance of subdividing the
heterogeneous functional constipation disorders into pre-defined
subgroups is largely unknown.. Aim: to estimate the prevalence of
constipation in a population-based sample and determine whether
clinical subgroups can be identified. An age and gender stratified
sample population from 5 Italian cities was evaluated using a
previously validated questionnaire. Data mining by cluster analysis
was used to determine constipation subgroups. Results: 1,500
complete interviews were obtained from 2,083 contacted households
(72%). Self-reported constipation correlated poorly with symptombased
constipation found in 496 subjects (33.1%). Cluster analysis
identified four constipation subgroups which correlated to subgroups
identified according to pre-defined symptom criteria. Significant
differences in socio-demographics and lifestyle were observed
among subgroups.
Abstract: Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using a voting methodology of bagging and boosting ensembles with 10 subclassifiers in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-classifiers, as well as other well known combining methods, on standard benchmark datasets and the proposed technique was the most accurate.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: Ultrathin (UTD) and Nanoscale (NSD) SOI-MOSFET devices, sharing a similar W/L but with a channel thickness of 46nm and 1.6nm respectively, were fabricated using a selective “gate recessed” process on the same silicon wafer. The electrical transport characterization at room temperature has shown a large difference between the two kinds of devices and has been interpreted in terms of a huge unexpected series resistance. Electrical characteristics of the Nanoscale device, taken in the linear region, can be analytically derived from the ultrathin device ones. A comparison of the structure and composition of the layers, using advanced techniques such as Focused Ion Beam (FIB) and High Resolution TEM (HRTEM) coupled with Energy Dispersive X-ray Spectroscopy (EDS), contributes an explanation as to the difference of transport between the devices.
Abstract: A method and apparatus for noninvasive measurement
of blood glucose concentration based on transilluminated laser beam
via the Index Finger has been reported in this paper. This method
depends on atomic gas (He-Ne) laser operating at 632.8nm
wavelength. During measurement, the index finger is inserted into the
glucose sensing unit, the transilluminated optical signal is converted
into an electrical signal, compared with the reference electrical
signal, and the obtained difference signal is processed by signal
processing unit which presents the results in the form of blood
glucose concentration. This method would enable the monitoring
blood glucose level of the diabetic patient continuously, safely and
noninvasively.
Abstract: In this communication an expression for mean
velocity of waste flow via an open channel is proposed which
is an improvement over Manning formula. The discharges,
storages and depths are computed at all locations of the Lyari river
by utilizing proposed expression. The results attained through
proposed expression are in good agreement with the observed data
and better than those acquired using Manning formula.
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.
Abstract: This paper investigates the effectiveness of the use of
seismic isolation devices on the overall 3D seismic response of
curved highway viaducts with an emphasis on expansion joints.
Furthermore, an evaluation of the effectiveness of the use of cable
restrainers is presented. For this purpose, the bridge seismic
performance has been evaluated on four different radii of curvature,
considering two cases: restrained and unrestrained curved viaducts.
Depending on the radius of curvature, three-dimensional non-linear
dynamic analysis shows the vulnerability of curved viaducts to
pounding and deck unseating damage. In this study, the efficiency of
using LRB supports combined with cable restrainers on curved
viaducts is demonstrated, not only by reducing in all cases the
possible damage, but also by providing a similar behavior in the
viaducts despite of curvature radius.
Abstract: This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: In this paper, an analytical approach for free vibration
analysis of four edges simply supported rectangular Kirchhoff plates
is presented. The method is based on wave approach. From wave
standpoint vibration propagate, reflect and transmit in a structure.
Firstly, the propagation and reflection matrices for plate with simply
supported boundary condition are derived. Then, these matrices are
combined to provide a concise and systematic approach to free
vibration analysis of a simply supported rectangular Kirchhoff plate.
Subsequently, the eigenvalue problem for free vibration of plates is
formulated and the equation of plate natural frequencies is
constructed. Finally, the effectiveness of the approach is shown by
comparison of the results with existing classical solution.
Abstract: Sorting appears the most attention among all computational tasks over the past years because sorted data is at the heart of many computations. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. Many parallel sorting algorithms have been investigated for a variety of parallel computer architectures. In this paper, three parallel sorting algorithms have been implemented and compared in terms of their overall execution time. The algorithms implemented are the odd-even transposition sort, parallel merge sort and parallel rank sort. Cluster of Workstations or Windows Compute Cluster has been used to compare the algorithms implemented. The C# programming language is used to develop the sorting algorithms. The MPI (Message Passing Interface) library has been selected to establish the communication and synchronization between processors. The time complexity for each parallel sorting algorithm will also be mentioned and analyzed.
Abstract: This paper presents Faults Forecasting System (FFS)
that utilizes statistical forecasting techniques in analyzing process
variables data in order to forecast faults occurrences. FFS is
proposing new idea in detecting faults. Current techniques used in
faults detection are based on analyzing the current status of the
system variables in order to check if the current status is fault or not.
FFS is using forecasting techniques to predict future timing for faults
before it happens. Proposed model is applying subset modeling
strategy and Bayesian approach in order to decrease dimensionality
of the process variables and improve faults forecasting accuracy. A
practical experiment, designed and implemented in Okayama
University, Japan, is implemented, and the comparison shows that
our proposed model is showing high forecasting accuracy and
BEFORE-TIME.
Abstract: Scatter behavior of fatigue life in die-cast AM60B
alloy was investigated. For comparison, those in rolled AM60B alloy
and die-cast A365-T5 aluminum alloy were also studied. Scatter
behavior of pore size was also investigated to discuss dominant
factors for fatigue life scatter in die-cast materials. Three-parameter
Weibull function was suitable to explain the scatter behavior of both
fatigue life and pore size. The scatter of fatigue life in die-cast
AM60B alloy was almost comparable to that in die-cast A365-T5
alloy, while it was significantly large compared to that in the rolled
AM60B alloy. Scatter behavior of pore size observed at fracture
nucleation site on the fracture surface was comparable to that
observed on the specimen cross-section and also to that of fatigue
life. Therefore, the dominant factor for large scatter of fatigue life in
die-cast alloys would be the large scatter of pore size. This
speculation was confirmed by the fracture mechanics fatigue life
prediction, where the pore observed at fatigue crack nucleation site
was assumed as the pre-existing crack.
Abstract: The paper presents a part of the results obtained in a
complex research project on Romanian Grey Steppe breed, owner of
some remarkable qualities such as hardiness, longevity, adaptability,
special resistance to ban weather and diseases and included in the
genetic fund (G.D. no. 822/2008.) from Romania.
Following the researches effectuated, we identified alleles of six
loci, codifying the six types of major milk proteins: alpha-casein S1
(α S1-cz); beta-casein (β-cz); kappa-casein (K-cz); beta-lactoglobulin
(β-lg); alpha-lactalbumin (α-la) and alpha-casein S2 (α S2-cz). In
system αS1-cz allele αs1-Cn B has the highest frequency (0.700), in
system β-cz allele β-Cn A2 ( 0.550 ), in system K-cz allele k-CnA2 (
0.583 ) and heterozygote genotype AB ( 0.416 ) and BB (0.375), in
system β-lg allele β-lgA1 has the highest frequency (0.542 ) and
heterozygote genotype AB ( 0.500 ), in system α-la there is
monomorphism for allele α-la B and similarly in system αS2-cz for
allele αs2-Cn A.
The milk analysis by the isoelectric focalization technique (I.E.F.)
allowed the identification of a new allele for locus αS1-casein, for two
of the individuals under analysis, namely allele called αS1-casein
IRV. When experiments were repeated, we noticed that this is not a
proteolysis band and it really was a new allele that has not been
registered in the specialized literature so far. We identified two
heterozygote individuals, carriers of this allele, namely: BIRV and
CIRV. This discovery is extremely important if focus is laid on the
national genetic patrimony.
Abstract: In wireless sensor network (WSN) the use of mobile
sink has been attracting more attention in recent times. Mobile sinks
are more effective means of balancing load, reducing hotspot
problem and elongating network lifetime. The sensor nodes in WSN
have limited power supply, computational capability and storage and
therefore for continuous data delivery reliability becomes high
priority in these networks. In this paper, we propose a Reliable
Energy-efficient Data Dissemination (REDD) scheme for WSNs with
multiple mobile sinks. In this strategy, sink first determines the
location of source and then directly communicates with the source
using geographical forwarding. Every forwarding node (FN) creates a
local zone comprising some sensor nodes that can act as
representative of FN when it fails. Analytical and simulation study
reveals significant improvement in energy conservation and reliable
data delivery in comparison to existing schemes.
Abstract: Proteins levels produced by bacteria may be increased
in stressful surroundings, such as in the presence of antibiotics. It
appears that many antimicrobial agents or antibiotics, when used at
low concentrations, have in common the ability to activate or repress
gene transcription, which is distinct from their inhibitory effect.
There have been comparatively few studies on the potential of
antibiotics or natural compounds in nature as a specific chemical
signal that can trigger a variety of biological functions. Therefore,
this study was focusing on the effect of essential oils from
Cymbopogon flexuosus and C. nardus in regulating proteins
production by Bacillus subtilis ATCC 21332. The Minimum
Inhibition Concentrations (MICs) of both essential oils on B. subtilis
were determined by using microdilution assay, resulting 0.2% and
1.56% for each C. flexuosus and C. nardus subsequently. The
bacteria were further exposed to each essential oils at concentration
of 0.01XMIC for 2 days. The proteins were then isolated and
analyzed by sodium dodecyl sulfate polyacrylamide gel
electrophoresis (SDS-PAGE). Protein profile showed that a band
with approximate size of 250 kD was appeared for the treated
bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in
stressful condition with the presence of essential oils at low
concentration could induce the protein production.
Abstract: In this paper, a double balanced radio frequency multiplier
is presented which is customized for transmitted reference
ultra wideband (UWB) receivers. The multiplier uses 90nm model
parameters and exploits compensating transistors to provide controllable
gain for a Gilbert core. After performing periodic and quasiperiodic
non linear analyses the RF mixer (multiplier) achieves a
voltage conversion gain of 16 dB and a DSB noise figure of 8.253
dB with very low power consumption. A high degree of LO to RF
isolation (in the range of -94dB), RF to IF isolation (in the range of
-95dB) and LO to IF isolation (in the range of -143dB) is expected
for this design with an input-referred IP3 point of -1.93 dBm and an
input referred 1 dB compression point of -10.67dBm. The amount of
noise at the output is 7.7 nV/√Hz when the LO input is driven by
a 10dBm signal. The mixer manifests better results when compared
with other reported multiplier circuits and its Zero-IF performance
ensures its applicability as TR-UWB multipliers.