Abstract: This research aims to study the lead pollution in the air of Babylon governorate that resulted generally from vehicles exhausts in addition to industrial and human activities.Vehicles number in Babylon governorate increased significantly after year 2003 that resulted with increase in lead emissions into the air.Measurement of lead emissions was done in seven stations distributed randomly in Babylon governorate. These stations where located in Industrial (Al-Sena'ay) Quarter, 60 street (near to Babylon sewer directorate), 40 Street (near to the first intersection), Al-Hashmia city, Al-Mahaweel city, , Al- Musayab city in addition to another station in Sayd Idris village belong to Abugharaq district (Agricultural station for comparison). The measured concentrations in these stations were compared with the standard limits of Environmental Protection Agency EPA (2 μg /m3). The results of this study showed that the average of lead concentrations ,in Babylon governorate during year 2010, was (3.13 μg/m3) which was greater than standard limits (2 μg/m3). The maximum concentration of lead was (6.41 μg / m3) recorded in the Industrial (Al-Sena'ay) Quarter during April month, while the minimum concentrations was (0.36 μg / m3) recorded in the agricultural station (Abugharaq) during December month.
Abstract: A mammography image is composed of low contrast area where the breast tissues and the breast abnormalities such as microcalcification can hardly be differentiated by the medical practitioner. This paper presents the application of active contour models (Snakes) for the segmentation of microcalcification in mammography images. Comparison on the microcalcifiation areas segmented by the Balloon Snake, Gradient Vector Flow (GVF) Snake, and Distance Snake is done against the true value of the microcalcification area. The true area value is the average microcalcification area in the original mammography image traced by the expert radiologists. From fifty images tested, the result obtained shows that the accuracy of the Balloon Snake, GVF Snake, and Distance Snake in segmenting boundaries of microcalcification are 96.01%, 95.74%, and 95.70% accuracy respectively. This implies that the Balloon Snake is a better segmentation method to locate the exact boundary of a microcalcification region.
Abstract: Carbon disulfide is widely used for the production of
viscose rayon, rubber, and other organic materials and it is a
feedstock for the synthesis of sulfuric acid. The objective of this
paper is to analyze possibilities for efficient production of CS2 from
sour natural gas reformation (H2SMR) (2H2S+CH4 =CS2 +4H2) .
Also, the effect of H2S to CH4 feed ratio and reaction temperature on
carbon disulfide production is investigated numerically in a
reforming reactor. The chemical reaction model is based on an
assumed Probability Density Function (PDF) parameterized by the
mean and variance of mixture fraction and β-PDF shape. The results
show that the major factors influencing CS2 production are reactor
temperature. The yield of carbon disulfide increases with increasing
H2S to CH4 feed gas ratio (H2S/CH4≤4). Also the yield of C(s)
increases with increasing temperature until the temperature reaches
to 1000°K, and then due to increase of CS2 production and
consumption of C(s), yield of C(s) drops with further increase in the
temperature. The predicted CH4 and H2S conversion and yield of
carbon disulfide are in good agreement with result of Huang and TRaissi.
Abstract: In this paper, the effect of width and height of the
model on the earthquake response in the finite element method is
discussed. For this purpose an earth dam as a soil structure under
earthquake has been considered. Various dam-foundation models are
analyzed by Plaxis, a finite element package for solving geotechnical
problems. The results indicate considerable differences in the seismic
responses.
Abstract: Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.
Abstract: The objective of the present study was to determine
the effect of different concentration of spermatozoa and length of
storage in 5 0C on sperm motility. Semen was collected using
artificial vagina from goat aged 2 to 2.5 years. Fresh goat semen
with sperm motility ≥ 70% was used as material. Semen was
divided into 4 treatments of concentration (40 x 10 6 / ml, 50 x
106/ml, 60x106/ml, 70x106/ml) with length of storage 0,12,24,36 h. in
5 0C. There were interactions (P
Abstract: Addition of milli or micro sized particles to the heat
transfer fluid is one of the many techniques employed for improving
heat transfer rate. Though this looks simple, this method has
practical problems such as high pressure loss, clogging and erosion
of the material of construction. These problems can be overcome by
using nanofluids, which is a dispersion of nanosized particles in a
base fluid. Nanoparticles increase the thermal conductivity of the
base fluid manifold which in turn increases the heat transfer rate.
Nanoparticles also increase the viscosity of the basefluid resulting in
higher pressure drop for the nanofluid compared to the base fluid. So
it is imperative that the Reynolds number (Re) and the volume
fraction have to be optimum for better thermal hydraulic
effectiveness. In this work, the heat transfer enhancement using
aluminium oxide nanofluid using low and high volume fraction
nanofluids in turbulent pipe flow with constant wall temperature has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach. Nanofluid, up till
a volume fraction of 1% is found to be an effective heat transfer
enhancement technique. The Nusselt number (Nu) and friction factor
predictions for the low volume fractions (i.e. 0.02%, 0.1 and 0.5%)
agree very well with the experimental values of Sundar and Sharma
(2010). While, predictions for the high volume fraction nanofluids
(i.e. 1%, 4% and 6%) are found to have reasonable agreement with
both experimental and numerical results available in the literature.
So the computationally inexpensive single phase approach can be
used for heat transfer and pressure drop prediction of new nanofluids.
Abstract: This paper describes the design of a programmable
FSK-modulator based on VCO and its implementation in 0.35m
CMOS process. The circuit is used to transmit digital data at
100Kbps rate in the frequency range of 400-600MHz. The design
and operation of the modulator is discussed briefly. Further the
characteristics of PLL, frequency synthesizer, VCO and the whole
design are elaborated. The variation among the proposed and tested
specifications is presented. Finally, the layout of sub-modules, pin
configurations, final chip and test results are presented.
Abstract: Dynamic Causal Modeling (DCM) functional
Magnetic Resonance Imaging (fMRI) is a promising technique to
study the connectivity among brain regions and effects of stimuli
through modeling neuronal interactions from time-series
neuroimaging. The aim of this study is to study characteristics of a
mirror neuron system (MNS) in elderly group (age: 60-70 years old).
Twenty volunteers were MRI scanned with visual stimuli to study a
functional brain network. DCM was employed to determine the
mechanism of mirror neuron effects. The results revealed major
activated areas including precentral gyrus, inferior parietal lobule,
inferior occipital gyrus, and supplementary motor area. When visual
stimuli were presented, the feed-forward connectivity from visual
area to conjunction area was increased and forwarded to motor area.
Moreover, the connectivity from the conjunction areas to premotor
area was also increased. Such findings can be useful for future
diagnostic process for elderly with diseases such as Parkinson-s and
Alzheimer-s.
Abstract: In comparison to the original SVM, which involves a
quadratic programming task; LS–SVM simplifies the required
computation, but unfortunately the sparseness of standard SVM is
lost. Another problem is that LS-SVM is only optimal if the training
samples are corrupted by Gaussian noise. In Least Squares SVM
(LS–SVM), the nonlinear solution is obtained, by first mapping the
input vector to a high dimensional kernel space in a nonlinear
fashion, where the solution is calculated from a linear equation set. In
this paper a geometric view of the kernel space is introduced, which
enables us to develop a new formulation to achieve a sparse and
robust estimate.
Abstract: This paper considers the problem of finding low cost
chip set for a minimum cost partitioning of a large logic circuits. Chip
sets are selected from a given library. Each chip in the library has a
different price, area, and I/O pin. We propose a low cost chip set
selection algorithm. Inputs to the algorithm are a netlist and a chip
information in the library. Output is a list of chip sets satisfied with
area and maximum partitioning number and it is sorted by cost. The
algorithm finds the sorted list of chip sets from minimum cost to
maximum cost. We used MCNC benchmark circuits for experiments.
The experimental results show that all of chip sets found satisfy the
multiple partitioning constraints.
Abstract: The utilize of renewable energy sources becomes
more crucial and fascinatingly, wider application of renewable
energy devices at domestic, commercial and industrial levels is not
only affect to stronger awareness but also significantly installed
capacities. Moreover, biomass principally is in form of woods and
converts to be energy for using by humans for a long time.
Gasification is a process of conversion of solid carbonaceous fuel
into combustible gas by partial combustion. Many gasified models
have various operating conditions because the parameters kept in
each model are differentiated. This study applied the experimental
data including three inputs variables including biomass consumption;
temperature at combustion zone and ash discharge rate and gas flow
rate as only one output variable. In this paper, response surface
methods were applied for identification of the gasified system
equation suitable for experimental data. The result showed that linear
model gave superlative results.
Abstract: This paper proposes a new solution to string matching problem. This solution constructs an inverted list representing a string pattern to be searched for. It then uses a new algorithm to process an input string in a single pass. The preprocessing phase takes 1) time complexity O(m) 2) space complexity O(1) where m is the length of pattern. The searching phase time complexity takes 1) O(m+α ) in average case 2) O(n/m) in the best case and 3) O(n) in the worst case, where α is the number of comparing leading to mismatch and n is the length of input text.
Abstract: Fischer-Tropsch synthesis is one of the most
important catalytic reactions that convert the synthetic gas to light
and heavy hydrocarbons. One of the main issues is selecting the type
of reactor. The slurry bubble reactor is suitable choice for Fischer-
Tropsch synthesis because of its good qualification to transfer heat
and mass, high durability of catalyst, low cost maintenance and
repair. The more common catalysts for Fischer-Tropsch synthesis are
Iron-based and Cobalt-based catalysts, the advantage of these
catalysts on each other depends on which type of hydrocarbons we
desire to produce. In this study, Fischer-Tropsch synthesis is modeled
with Iron and Cobalt catalysts in a slurry bubble reactor considering
mass and momentum balance and the hydrodynamic relations effect
on the reactor behavior. Profiles of reactant conversion and reactant
concentration in gas and liquid phases were determined as the
functions of residence time in the reactor. The effects of temperature,
pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid
and liquid-solid mass transfer coefficients and kinetic
coefficients on the reactant conversion have been studied. With 5%
increase of liquid velocity (with Iron catalyst), H2 conversions
increase about 6% and CO conversion increase about 4%, With 8%
increase of liquid velocity (with Cobalt catalyst), H2 conversions
increase about 26% and CO conversion increase about 4%. With
20% increase of gas-liquid mass transfer coefficient (with Iron
catalyst), H2 conversions increase about 12% and CO conversion
increase about 10% and with Cobalt catalyst H2 conversions increase
about 10% and CO conversion increase about 6%. Results show that
the process is sensitive to gas-liquid mass transfer coefficient and
optimum condition operation occurs in maximum possible liquid
velocity. This velocity must be more than minimum fluidization
velocity and less than terminal velocity in such a way that avoid
catalysts particles from leaving the fluidized bed.
Abstract: This paper presents a robust method to detect obstacles in stereo images using shadow removal technique and color information. Stereo vision based obstacle detection is an algorithm that aims to detect and compute obstacle depth using stereo matching and disparity map. The proposed advanced method is divided into three phases, the first phase is detecting obstacles and removing shadows, the second one is matching and the last phase is depth computing. We propose a robust method for detecting obstacles in stereo images using a shadow removal technique based on color information in HIS space, at the first phase. In this paper we use Normalized Cross Correlation (NCC) function matching with a 5 × 5 window and prepare an empty matching table τ and start growing disparity components by drawing a seed s from S which is computed using canny edge detector, and adding it to τ. In this way we achieve higher performance than the previous works [2,17]. A fast stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. The obstacle identified in phase one which appears in the disparity map of phase two enters to the third phase of depth computing. Finally, experimental results are presented to show the effectiveness of the proposed method.
Abstract: Nowadays there are several grid connected converter
in the grid system. These grid connected converters are generally the
converters of renewable energy sources, industrial four quadrant
drives and other converters with DC link. These converters are
connected to the grid through a three phase bridge. The standards
prescribe the maximal harmonic emission which could be easily
limited with high switching frequency. The increased switching
losses can be reduced to the half with the utilization of the wellknown
Flat-top modulation. The suggested control method is the
expansion of the Flat-top modulation with which the losses could be
also reduced to the half compared to the Flat-top modulation.
Comparing to traditional control these requirements can be
simultaneously satisfied much better with the DLF (DC Link
Floating) method.
Abstract: This paper is concerned with a nonautonomous three species food chain model with Crowley–Martin type functional response and time delay. Using the Mawhin-s continuation theorem in theory of degree, sufficient conditions for existence of periodic solutions are obtained.
Abstract: This study aims to examine the determinants of
purchase intention in C2C e-commerce. Specifically the role of
instant messaging in the C2C e-commerce contextis investigated. In
addition to instant messaging, we brought in two antecedents of
purchase intention - trust and customer satisfaction - to establish a
theoretical research model. Structural equation modeling using
LISREL was used to analyze the data.We discussed the research
findings and suggested some implications for researchers and
practitioners.
Abstract: A learning management system (commonly
abbreviated as LMS) is a software application for the administration,
documentation, tracking, and reporting of training programs,
classroom and online events, e-learning programs, and training
content (Ellis 2009). (Hall 2003) defines an LMS as \"software that
automates the administration of training events. All Learning
Management Systems manage the log-in of registered users, manage
course catalogs, record data from learners, and provide reports to
management\". Evidence of the worldwide spread of e-learning in
recent years is easy to obtain. In April 2003, no fewer than 66,000
fully online courses and 1,200 complete online programs were listed
on the TeleCampus portal from TeleEducation (Paulsen 2003). In the
report \" The US market in the Self-paced eLearning Products and
Services:2010-2015 Forecast and Analysis\" The number of student
taken classes exclusively online will be nearly equal (1% less) to the
number taken classes exclusively in physical campuses. Number of
student taken online course will increase from 1.37 million in 2010 to
3.86 million in 2015 in USA. In another report by The Sloan
Consortium three-quarters of institutions report that the economic
downturn has increased demand for online courses and programs.
Abstract: The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to control the amount of de-noising in any region of image, according to relative information of local feature scale. Experimental results demonstrate the efficient of the proposed algorithm. Compared with standard Total Variation, our algorithm can better preserve smaller-scaled features and show better performance.