Abstract: In this paper, we propose an approach of unsupervised
segmentation with fuzzy connectedness. Valid seeds are first specified
by an unsupervised method based on scale space theory. A region is
then extracted for each seed with a relative object extraction method of
fuzzy connectedness. Afterwards, regions are merged according to the
values between them of an introduced measure. Some theorems and
propositions are also provided to show the reasonableness of the
measure for doing mergence. Experiment results on a synthetic image,
a color image and a large amount of MR images of our method are
reported.
Abstract: Traditionally, Yemini Sidr honey has been reported to
cure liver problems, stomach ulcers, and respiratory disorders. In this
experiment, we evaluated Yemeni Sidr honey for its ability to protect
inflammations caused by acetic acid and formalin -induced writhing,
carrageenan and histamine-induced paw oedema in experimental rat
model. Hyperpyrexia, membrane stabilizing activity, and
phytochemical screening of the honey was also examined. Yemini
Sidr Honey at (100, 200 and 500 mg/kg) exhibited a concentration
dependant inhibition of acetic acid induced and formalin induced
writhing, paw oedema induced by carrageenan & histamine, and
hyperpyrexia induced by brewer's yeast, it also inhibited membrane
stabilizing activity. Phytochemical screenings of the honey reveal the
presence of flavonoids, steroid, alkaloids, saponins and tannins. This
study suggested that Yemeni Sidr honey possess very strong antiinflammatory,
analgesic and antipyretic effects and these effects
would be a result of the phytochemicals present.
Abstract: Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.
Abstract: Proximate (moisture, protein, total fat, total ash) and mineral (K, P, Na, Mg, Ca, Zn, Fe, Cu and Mn) composition of chicken giblets (heart, liver and gizzard) were investigated. Phosphorous content, as well as proximate composition, were determined according to recommended ISO methods. The content of all elements, except phosphorus, of the giblets tissues were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES), after dry ashing mineralization. Regarding proximate composition heart was the highest in total fat content, and the lowest in protein content. Liver was the highest in protein and total ash content, while gizzard was the highest in moisture and the lowest in total fat content. Regarding mineral composition liver was the highest for K, P, Ca, Mg, Fe, Zn, Cu, and Mn, while heart was the highest for Na content. The contents of almost all investigated minerals in analysed giblets tissues of chickens from Vojvodina were similar to values reported in the literature, i.e. in national food composition databases of other countries.
Abstract: This paper presents a new sufficient condition for the
existence, uniqueness and global asymptotic stability of the equilibrium point for Cohen-Grossberg neural networks with multiple time delays. The results establish a relationship between the network parameters
of the neural system independently of the delay parameters. The results are also compared with the previously reported results in
the literature.
Abstract: The present paper reports results of an experimental
program conducted to study performance of fly ash based
geopolymer pastes at elevated temperature. Three series of
geopolymer pastes differing in Na2O content (8.5%, 10% and 11.5%)
were manufactured by activating low calcium fly ash with a mixture
of sodium hydroxide and sodium silicate solution. The paste
specimens were subjected to temperatures as high as 900oC and the
behaviour at elevated temperatures were investigated on the basis of
physical appearance, weight losses, residual strength, shrinkage
measurements and sorptivity tests at different temperatures. Scanning
electron microscopy along with EDX and XRD tests were also
conducted to examine microstructure and mineralogical changes
during the thermal exposure. Specimens which were initially grey
turned reddish accompanied by appearance of small cracks as the
temperature increased to 900oC. Loss of weight was more in
specimens manufactured with highest Na2O content. Geopolymer
paste specimen containing minimum Na2O performed better than
those with higher Na2O content in terms of residual compressive
strength.
Abstract: Although achieving zero-defect software release is
practically impossible, software industries should take maximum
care to detect defects/bugs well ahead in time allowing only bare
minimums to creep into released version. This is a clear indicator of
time playing an important role in the bug detection. In addition to
this, software quality is the major factor in software engineering
process. Moreover, early detection can be achieved only through
static code analysis as opposed to conventional testing.
BugCatcher.Net is a static analysis tool, which detects bugs in .NET®
languages through MSIL (Microsoft Intermediate Language)
inspection. The tool utilizes a Parser based on Finite State Automata
to carry out bug detection. After being detected, bugs need to be
corrected immediately. BugCatcher.Net facilitates correction, by
proposing a corrective solution for reported warnings/bugs to end
users with minimum side effects. Moreover, the tool is also capable
of analyzing the bug trend of a program under inspection.
Abstract: MicroRNAs (miRNAs) are a class of non-coding
RNAs that hybridize to mRNAs and induce either translation
repression or mRNA cleavage. Recently, it has been reported that
miRNAs could possibly play an important role in human diseases. By
integrating miRNA target genes, cancer genes, miRNA and mRNA
expression profiles information, a database is developed to link
miRNAs to cancer target genes. The database provides experimentally
verified human miRNA target genes information, including oncogenes
and tumor suppressor genes. In addition, fragile sites information for
miRNAs, and the strength of the correlation of miRNA and its target
mRNA expression level for nine tissue types are computed, which
serve as an indicator for suggesting miRNAs could play a role in
human cancer. The database is freely accessible at
http://ppi.bioinfo.asia.edu.tw/mirna_target/index.html.
Abstract: The objective of this work was to examine the changes
in non destructive properties caused by carbonation of CEM II
mortar. Samples of CEM II mortar were prepared and subjected to
accelerated carbonation at 20°C, 65% relative humidity and 20% CO2
concentration. We examined the evolutions of the gas permeability,
the thermal conductivity, the thermal diffusivity, the volume of the
solid phase by helium pycnometry, the longitudinal and transverse
ultrasonic velocities. The principal contribution of this work is that,
apart of the gas permeability, changes in other non destructive
properties have never been studied during the carbonation of cement
materials. These properties are important in predicting/measuring the
durability of reinforced concrete in CO2 environment. The
carbonation depth and the porosity accessible to water were also
reported in order to explain comprehensively the changes in non
destructive parameters.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: The paper shows how the perceptions of five organizational virtuousness dimensions (optimism, trust, compassion, integrity, and forgiveness) explain organizational citizenship behaviors (altruism, sportsmanship, courtesy, conscientiousness, and civic virtue). A sample comprising 216 individuals from 14 industrial organizations was collected. Individuals reported their perceptions of organizational virtuousness, their organizational citizenship behaviors (OCB) being reported by their supervisors. The main findings are the following: (a) the perceptions of trust predict altruism; (b) the perceptions of integrity predict civic virtue.
Abstract: spherical porous carbon particles with
controllable porosity with a mean size of 2.5m have been
prepared using a spray drying method with organic particle
colloidal template. As a precursor, a mixing solution of carbon
nanopowder and polystyrene (PS) particles as a template was
used. The result showed that the particles with a good porous
structure could be obtained. The pore size and shape (spherical)
were identical to the initial template, giving a potential way for
further developments. The control of particle porosity was also
possible and reported in this paper, in which this control could
be achieved by means of PS concentration.
Abstract: This paper reports on the results of experimental investigations on the performance of a jet pump operated under selected primary flows to optimize the related parameters. For this purpose a two-phase flow jet pump was used employing various profiles of nozzles as the primary device which was designed, fabricated and used along with the combination of mixing tube and diffuser. The profiles employed were circular, conical, and elliptical. The diameter of the nozzle used was 4 mm. The area ratio of the jet pump was 0.16. The test facility created for this purpose was an open loop continuous circulation system. Performance of the jet pump was obtained as iso-efficiency curves on characteristic curves drawn for various water flow rates. To perform the suction capability, evacuation test was conducted at best efficiency point for all the profiles.
Abstract: This paper examines the readability of the chairman’s narratives, as determined by the Flesch score, of a Malaysian public listed company’s corporate reports from 1962 to 2009. It partially supports earlier studies which demonstrated that corporate reports were difficult to read, and had shown very negligible decrease in difficulty over time. Net profit to sales and readability was significantly positively correlated but number of financial statements was significantly negatively correlated with readability.
Abstract: The integral form of equations of motion of composite
beams subjected to varying time loads are discretized using a
developed finite element model. The model consists of a straight five
node twenty-two degrees of freedom beam element. The stability
analysis of the beams is studied by solving the matrix form
characteristic equations of the system. The principle of virtual work
and the first order shear deformation theory are employed to analyze
the beams with large deformation and small strains. The regions of
dynamic instability of the beam are determined by solving the
obtained Mathieu form of differential equations. The effects of nonconservative
loads, shear stiffness, and damping parameters on
stability and response of the beams are examined. Several numerical
calculations are presented to compare the results with data reported
by other researchers.
Abstract: We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.
Abstract: This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.
Abstract: This paper reports a distributed mutual exclusion
algorithm for mobile Ad-hoc networks. The network is clustered
hierarchically. The proposed algorithm considers the clustered
network as a logical tree and develops a token passing scheme
to get the mutual exclusion. The performance analysis and
simulation results show that its message requirement is optimal,
and thus the algorithm is energy efficient.
Abstract: Food borne illnesses have been reported to be a global
health challenge. Annual incidences of food–related diseases involve
76 million cases, of which only 14 million can be traced to known
pathogens. Poor hygienic practices have contributed greatly to this. It
has been reported that in the year 2000 about 2.1 million people died
from diarrheal diseases, hence, there is a need to ensure food safety at
all level. This study focused on the sterility examination and
inhibitory effect of honey samples on selected gram negative and
gram positive food borne pathogen from South West Nigeria. The
laboratory examinations revealed the presence of some bacterial and
fungal contaminations of honey samples and that inhibitory activity
of the honey sample was more pronounced on the gram negative
bacteria than the gram positive bacterial isolates. Antibiotic
sensitivity test conducted on the different bacterial isolates also
showed that honey was able to inhibit the proliferation of the tested
bacteria than the employed antibiotics.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.