Abstract: Animal fats (camel, sheep, goat, rabbit and chicken)
and vegetable oils (corn, sunflower, palm oil and olive oil) were
substituted with different proportions (1, 5, 10 and 20%) of lard.
Fatty acid composition in TG and 2-MG were determined using
lipase hydrolysis and gas chromatography before and after
adulteration. Results indicated that, genuine lard had a high
proportion (60.97%) of the total palmitic acid at 2-MG. However, it
was 8.70%, 16.40%, 11.38%, 10.57%, 29.97 and 8.97% for camel,
beef, sheep, goat, rabbit and chicken, respectively. It could be noticed
also the position-2-MG is mostly occupied by unsaturated fatty acids
among all tested fats except lard. Vegetable oils (corn, sunflower,
palm oil and olive oil) revealed that the levels of palmitic acid
esterifies at 2-MG position was 6.84, 1.43, 9.86 and 1.70%,
respectively. It could be observed also the studied oils had a higher
level of unsaturated fatty acids in the same position, compared with
animal fats under investigation. Moreover, palmitic acid esterifies at
2-MG and PAEF increased gradually as the substituted levels
increased among all tested fat and oil samples. Statistical analysis
showed that the PAEF correlated well with lard level. The detection
of lard in some commercial processed foods (5 French fries, 4 Butter
fats, 5 processed meat and 6 candy samples) was carried out. Results
revealed that 2 samples of French fries and 4 samples of processed
meat contained lard due to their higher PAEF, while butter fat and
candy were free of lard.
Abstract: In this paper, we study the rainfall using a time series
for weather stations in Nakhon Ratchasima province in Thailand by
various statistical methods to enable us to analyse the behaviour of
rainfall in the study areas. Time-series analysis is an important tool in
modelling and forecasting rainfall. The ARIMA and Holt-Winter
models were built on the basis of exponential smoothing. All the
models proved to be adequate. Therefore it is possible to give
information that can help decision makers establish strategies for the
proper planning of agriculture, drainage systems and other water
resource applications in Nakhon Ratchasima province. We obtained
the best performance from forecasting with the ARIMA
Model(1,0,1)(1,0,1)12.
Abstract: This paper proposes a backward/forward sweep
method to analyze the power flow in radial distribution systems. The
distribution system has radial structure and high R/X ratios. So the
newton-raphson and fast decoupled methods are failed with
distribution system. The proposed method presents a load flow study
using backward/forward sweep method, which is one of the most
effective methods for the load-flow analysis of the radial distribution
system. By using this method, power losses for each bus branch and
voltage magnitudes for each bus node are determined. This method
has been tested on IEEE 33-bus radial distribution system and
effective results are obtained using MATLAB.
Abstract: The electric power supplied by a photovoltaic power
generation systems depends on the solar irradiation and temperature.
The PV system can supply the maximum power to the load at a
particular operating point which is generally called as maximum
power point (MPP), at which the entire PV system operates with
maximum efficiency and produces its maximum power. Hence, a
Maximum power point tracking (MPPT) methods are used to
maximize the PV array output power by tracking continuously the
maximum power point. The proposed MPPT controller is designed
for 10kW solar PV system installed at Cape Institute of Technology.
This paper presents the fuzzy logic based MPPT algorithm. However,
instead of one type of membership function, different structures of
fuzzy membership functions are used in the FLC design. The
proposed controller is combined with the system and the results are
obtained for each membership functions in Matlab/Simulink
environment. Simulation results are decided that which membership
function is more suitable for this system.
Abstract: In this paper, Least Mean Square (LMS) adaptive
noise reduction algorithm is proposed to enhance the speech signal
from the noisy speech. In this, the speech signal is enhanced by
varying the step size as the function of the input signal. Objective and
subjective measures are made under various noises for the proposed
and existing algorithms. From the experimental results, it is seen that
the proposed LMS adaptive noise reduction algorithm reduces Mean
square Error (MSE) and Log Spectral Distance (LSD) as compared to
that of the earlier methods under various noise conditions with
different input SNR levels. In addition, the proposed algorithm
increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR
improvement (ΔSNRseg) values; improves the Mean Opinion Score
(MOS) as compared to that of the various existing LMS adaptive
noise reduction algorithms. From these experimental results, it is
observed that the proposed LMS adaptive noise reduction algorithm
reduces the speech distortion and residual noise as compared to that
of the existing methods.
Abstract: To practically apply vacuum insulation panels (VIPs)
to buildings or home appliances, VIPs have demanded long-term
lifespan with outstanding insulation performance. Service lives of
VIPs enveloped with Al-foil and three-layer Al-metallized envelope
are calculated. For Al-foil envelope, the service life is longer but edge
conduction is too large compared with the Al-metallized envelope. To
increase service life even more, the proposed double enveloping
method and metal-barrier-added enveloping method are further
analyzed. The service lives of the VIP to employ two enveloping
methods are calculated. Also, pressure increase and thermal insulation
performance characteristics are investigated. For the metalbarrier-
added enveloping method, effective thermal conductivity
increase with time is close to that of Al-foil envelope, especially, for
getter-inserted VIPs. For double enveloping method, if water vapor is
perfectly adsorbed, the effect of service life enhancement becomes
much greater. From these methods, the VIP can be guaranteed for
service life of more than 20 years.
Abstract: The dramatic rise in the use of Social Media (SM)
platforms such as Facebook and Twitter provide access to an
unprecedented amount of user data. Users may post reviews on
products and services they bought, write about their interests, share
ideas or give their opinions and views on political issues. There is a
growing interest in the analysis of SM data from organisations for
detecting new trends, obtaining user opinions on their products and
services or finding out about their online reputations. A recent
research trend in SM analysis is making predictions based on
sentiment analysis of SM. Often indicators of historic SM data are
represented as time series and correlated with a variety of real world
phenomena like the outcome of elections, the development of
financial indicators, box office revenue and disease outbreaks. This
paper examines the current state of research in the area of SM mining
and predictive analysis and gives an overview of the analysis
methods using opinion mining and machine learning techniques.
Abstract: A key issue in seismic risk analysis within the context
of Performance-Based Earthquake Engineering is the evaluation of
the expected seismic damage of structures under a specific
earthquake ground motion. The assessment of the seismic
performance strongly depends on the choice of the seismic Intensity
Measure (IM), which quantifies the characteristics of a ground
motion that are important to the nonlinear structural response. Several
conventional IMs of ground motion have been used to estimate their
damage potential to structures. Yet, none of them has been proved to
be able to predict adequately the seismic damage. Therefore,
alternative, scalar intensity measures, which take into account not
only ground motion characteristics but also structural information
have been proposed. Some of these IMs are based on integration of
spectral values over a range of periods, in an attempt to account for
the information that the shape of the acceleration, velocity or
displacement spectrum provides. The adequacy of a number of these
IMs in predicting the structural damage of 3D R/C buildings is
investigated in the present paper. The investigated IMs, some of
which are structure specific and some are non structure-specific, are
defined via integration of spectral values. To achieve this purpose
three symmetric in plan R/C buildings are studied. The buildings are
subjected to 59 bidirectional earthquake ground motions. The two
horizontal accelerograms of each ground motion are applied along
the structural axes. The response is determined by nonlinear time
history analysis. The structural damage is expressed in terms of the
maximum interstory drift as well as the overall structural damage
index. The values of the aforementioned seismic damage measures
are correlated with seven scalar ground motion IMs. The comparative
assessment of the results revealed that the structure-specific IMs
present higher correlation with the seismic damage of the three
buildings. However, the adequacy of the IMs for estimation of the
structural damage depends on the response parameter adopted.
Furthermore, it was confirmed that the widely used spectral
acceleration at the fundamental period of the structure is a good
indicator of the expected earthquake damage level.
Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: In oases, the surface water resources are becoming
increasingly scarce and groundwater resources, which generally have
a poor quality due to the high levels of salinity, are often
overexploited. Water saving have therefore become imperative for
better oases sustainability. If drip irrigation is currently recommended
in Morocco for saving water and valuing, its use in the sub-desert
areas does not keep water safe from high evaporation rates. An
alternative to this system would be the use of subsurface drip
irrigation. This technique is defined as an application of water under
the soil surface through drippers, which deliver water at rates
generally similar to surface drip irrigation. As subsurface drip
irrigation is a recently introduced in Morocco, a better understanding
of the infiltration process around a buried source, in local conditions,
and its impact on plant growth is necessarily required. This study
aims to contribute to improving the water use efficiency by testing
the performance of subsurface irrigation system, especially in areas
where water is a limited source. The objectives of this research are
performance evaluation in arid conditions of the subsurface drip
irrigation system for young date palms compared to the surface drip.
In this context, an experimental test is installed at a farmer’s field in
the area of Erfoud (Errachidia Province, southeastern Morocco),
using the subsurface drip irrigation system in comparison with the
classic drip system for young date palms. Flow measurement to
calculate the uniformity of the application of water was done through
two methods: a flow measurement of drippers above the surface and
another one underground. The latter method has also helped us to
estimate losses through evaporation for both irrigation techniques. In
order to compare the effect of two irrigation modes, plants were
identified for each type of irrigation to monitor certain agronomic
parameters (cumulative numbers of palms and roots development).
Experimentation referred to a distribution uniformity of about 88%;
considered acceptable for subsurface drip irrigation while it is around
80% for the surface drip irrigation. The results also show an increase
in root development and in the number of palm, as well as a
substantial water savings due to lower evaporation losses compared
to the classic drip irrigation.
The results of this study showed that subsurface drip irrigation is
an efficient technique, which allows sustainable irrigation in arid
areas.
Abstract: Particles are the most common and cheapest
reinforcement producing discontinuous reinforced composites with
isotropic properties. Conventional fabrication methods can be used to
produce a wide range of product forms, making them relatively
inexpensive. Optimising composite development must include
consideration of all the fundamental aspect of particles including
their size, shape, volume fraction, distribution and mechanical
properties. Research has shown that the challenges of low fracture
toughness, poor crack growth resistance and low thermal stability can
be overcome by reinforcement with particles. The unique properties
exhibited by micro particles reinforced ceramic composites have
made them to be highly attractive in a vast array of applications.
Abstract: Two Lithium Disilicate (LD) glass ceramics based on
SiO2-Li2O-K2O-Al2O3 system were prepared through a glass melting
method. The glass rods were then fabricated into dental crowns via a
hot pressing at 900˚C and 850˚C in order to study the effect of the
pressing temperatures on the phase formation and microstructure of
the glasses. Different samples of as cast glass and heat treated
samples (600˚C and 700˚C) were used to press for investigating the
effect of an initial microstructure on the hot pressing technique. Xray
diffraction (XRD) and scanning electron microscopy (SEM) were
performed to determine the phase formation and microstructure of the
samples, respectively. XRD results show that the main crystalline
structure was Li2Si2O5 by having Li3PO4, Li0.6Al0.6Si2O6, Li2SiO3,
Ca5 (PO4)3F and SiO2 as minor phases. Glass compositions with
different heat treatment temperatures exhibited a difference phase
formations but have less effect during pressing. SEM micrographs
showed the microstructure of Li2Si2O5 as lath-like shape in all
glasses. With increasing the initial heat treatment temperature, the
longer the lath-like crystals of lithium disilicate were increased
especially when using glass heat treatment at 700˚C followed by
pressing at 900˚C. This could be suggested that LD1 heat treatment at
700˚C which pressing at 900˚C presented the best formation by the
hot pressing and compiled microstructure.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: Key frame extraction methods select the most
representative frames of a video, which can be used in different areas
of video processing such as video retrieval, video summary, and video
indexing. In this paper we present a novel approach for extracting key
frames from video sequences. The frame is characterized uniquely by
his contours which are represented by the dominant blocks. These
dominant blocks are located on the contours and its near textures.
When the video frames have a noticeable changement, its dominant
blocks changed, then we can extracte a key frame. The dominant
blocks of every frame is computed, and then feature vectors are
extracted from the dominant blocks image of each frame and arranged
in a feature matrix. Singular Value Decomposition is used to calculate
sliding windows ranks of those matrices. Finally the computed ranks
are traced and then we are able to extract key frames of a video.
Experimental results show that the proposed approach is robust
against a large range of digital effects used during shot transition.
Abstract: There are a variety of reference current identification
methods, for the shunt active power filter (SAPF), such as the
instantaneous active and reactive power, the instantaneous active and
reactive current and the synchronous detection method are evaluated
and compared under ideal, non sinusoidal and unbalanced voltage
conditions. The SAPF performances, for the investigated
identification methods, are tested for a non linear load. The
simulation results, using Matlab Power System Blockset Toolbox
from a complete structure, are presented and discussed.
Abstract: Existing methods of data mining cannot be applied on
spatial data because they require spatial specificity consideration, as
spatial relationships.
This paper focuses on the classification with decision trees, which
are one of the data mining techniques. We propose an extension of
the C4.5 algorithm for spatial data, based on two different approaches
Join materialization and Querying on the fly the different tables.
Similar works have been done on these two main approaches, the
first - Join materialization - favors the processing time in spite of
memory space, whereas the second - Querying on the fly different
tables- promotes memory space despite of the processing time.
The modified C4.5 algorithm requires three entries tables: a target
table, a neighbor table, and a spatial index join that contains the
possible spatial relationship among the objects in the target table and
those in the neighbor table. Thus, the proposed algorithms are applied
to a spatial data pattern in the accidentology domain.
A comparative study of our approach with other works of
classification by spatial decision trees will be detailed.
Abstract: In recent decades with the development of technology
and lack of food sources, sewage sludge in production of human
foods is inevitable. Various sources of municipal and industrial
sewage sludge that is produced can provide the requirement of plant
nutrients. Soils in arid, semi-arid climate of central Iran that most
affected by water drainage, iron and zinc deficiencies, using of
sewage sludge is helpful. Therefore, the aim of this study is
investigation of sewage sludge and manure application on Ni, Pb and
Cd uptake by Savory. An experiment in a randomized complete block
design with three replications was performed. Sewage sludge
treatments consisted of four levels, control, 15, 30, 80 tons per
hectares; the manure was used in four levels of control, 20, 40 and 80
tons per hectare. Results showed that the wet and dry weights was not
affected by sewage sludge using, while, manure has significant effect
on them. The effect of sewage sludge on the cadmium and lead
concentrations were significant. Interactions of sewage sludge and
manure on dry weight values were not significant. Compare mean
analysis showed that increasing the amount of sewage sludge had no
significant effect on cadmium concentration and it reduced when
sewage sludge usage increased. This is probably due to increased
plant growth and reduced concentrations of these elements in the
plant.
Abstract: The efficiency of wood vinegar mixed with each
individual of three plants extract such as: citronella grass
(Cymbopogon nardus), neem seed (Azadirachta indica A. Juss), and
yam bean seed (Pachyrhizus erosus Urb.) were tested against the
second instar larvae of housefly (Musca domestica L.). Steam
distillation was used for extraction of the citronella grass while neem
and yam bean were simple extracted by fermentation with ethyl
alcohol. Toxicity test was evaluated in laboratory based on two
methods of larvicidal bioassay: topical application method (contact
poison) and feeding method (stomach poison). Larval mortality was
observed daily and larval survivability was recorded until the
survived larvae developed to pupae and adults. The study resulted
that treatment of wood vinegar mixed with citronella grass showed
the highest larval mortality by topical application method (50.0%)
and by feeding method (80.0%). However, treatment of mixed wood
vinegar and neem seed showed the longest pupal duration to 25 day
and 32 days for topical application method and feeding method
respectively. Additional, larval duration on treated M. domestica
larvae was extended to 13 days for topical application method and 11
days for feeding method. Thus, the feeding method gave higher
efficiency compared with the topical application method.
Abstract: The purpose of this study was to investigate
perceptions of climate change risk to forest ecosystems and forestbased
communities as well as perceived effectiveness of adaptation
strategies for climate change as well as challenges for adaptation.
Data was gathered using a pre-tested semi-structured questionnaire.
Simple random selection technique was applied. For the majority of
issues, the responses were obtained on multi-point likert scales, and
the scores provided were, in turn, used to estimate the means and
other useful estimates. A composite knowledge index developed
using correct responses to a set of self-rated statements were used to
evaluate the issues. The mean of the knowledge index was 0.64. Also
all respondents recorded values of the knowledge index above 0.25.
Increase forest fire was perceived by respondents as the greatest risk
to forest eco-system. Decrease access to water supplies was perceived
as the greatest risk to livelihoods of forest based communities. The
most effective adaptation strategy relevant to climate change risks to
forest eco-systems and forest based communities livelihoods in
Kathmandu valley in Nepal as perceived by the respondents was
reforestation and afforestation. As well, lack of public awareness was
perceived as the major limitation for climate change adaptation.
However, perceived risks as well as effective adaptation strategies
showed an inconsistent association with knowledge indicators and
social-cultural variables. The results provide useful information to
any party who involve with climate change issues in Nepal, since
such attempts would be more effective once the people’s perceptions
on these aspects are taken into account.
Abstract: Background: Bleeding during first half of pregnancy
mostly originates from placenta, some abort, others are at risk of
complications. Objective: Study was done to know perinatal outcome
with bleeding up to 20 weeks in singleton pregnancy. Material
Methods: Subjects were 1020, equal controls managed over 2 years,
435 had viable pregnancy at admission, 135 excluded, 300 followed
for perinatal outcome, 99 (19.52% up to 10 weeks), 201 (39.18% of
11-20 weeks). Results: Hypertensive disorders occurred in 24% cases
of bleeding within 10 weeks, 22% 11-20 weeks 14.79% controls,
placenta previa 4% in 10 weeks, 0.9% 11-20 weeks, 0.97% controls,
prelabor rupture of membranes in 16%, 7.45% controls. 20% up to 10
weeks, 35% 11-20 weeks, 18% controls had fetal growth restriction,
34.34% up to 10 weeks 30.35% of 11-20 weeks 17.17% controls had
preterm births, perinatal mortality rate in study was 118.62, in
controls 68.16 (Uneventful pregnancy in 13.52% study, 46.11%
controls). Conclusion: Once bleeding occurs, one third continue
pregnancy, maternal neonatal outcome gets affected with variations
in cases of bleeding within first 10 weeks & 11-20 weeks.