Abstract: Computer worm detection is commonly performed by
antivirus software tools that rely on prior explicit knowledge of the
worm-s code (detection based on code signatures). We present an
approach for detection of the presence of computer worms based on
Artificial Neural Networks (ANN) using the computer's behavioral
measures. Identification of significant features, which describe the
activity of a worm within a host, is commonly acquired from security
experts. We suggest acquiring these features by applying feature
selection methods. We compare three different feature selection
techniques for the dimensionality reduction and identification of the
most prominent features to capture efficiently the computer behavior
in the context of worm activity. Additionally, we explore three
different temporal representation techniques for the most prominent
features. In order to evaluate the different techniques, several
computers were infected with five different worms and 323 different
features of the infected computers were measured. We evaluated
each technique by preprocessing the dataset according to each one
and training the ANN model with the preprocessed data. We then
evaluated the ability of the model to detect the presence of a new
computer worm, in particular, during heavy user activity on the
infected computers.
Abstract: This paper is to present context-aware sensor grid
framework for agriculture and its design challenges. Use of sensor
networks in the domain of agriculture is not new. However, due to
the unavailability of any common framework, solutions that are
developed in this domain are location, environment and problem
dependent. Keeping the need of common framework for agriculture,
Context-Aware Sensor Grid Framework is proposed. It will be
helpful in developing solutions for majority of the problems related
to irrigation, pesticides spray, use of fertilizers, regular monitoring of
plot and yield etc. due to the capability of adjusting according to
location and environment. The proposed framework is composed of
three layer architecture including context-aware application layer,
grid middleware layer and sensor network layer.
Abstract: The role of the pollen grain, with to the reproductive
process of higher plants, is to deliver the spermatic cells to the
embryo sac for egg fertilization. The aim of this project was study
the effect of electromagnetic fields on structure and pollen grains
development in Chenopodium album. Anthers of Chenopodium
album L. were collected at different stages of development from
control (without electromagnetic field) and plants grown at 10m from
the field sources. Structure and development of pollen grains were
studied and compared. The studying pollen structure by Light and
Scanning electron microscopy showed that electromagnetic fields
reduction of pollen grains number and male sterility, thus , in some
anthers, pollen grains were attached together and deformed compared
to control ones. The data presented suggest that prolonged exposures
of plants to magnetic field may cause different biological effects at
the cellular tissue and organ levels.
Abstract: Sensors possess several properties of physical
measures. Whether devices that convert a sensed signal into an
electrical signal, chemical sensors and biosensors, thus all these
sensors can be considered as an interface between the physical and
electrical equipment. The problem is the analysis of the multitudes of
saved settings as input variables. However, they do not all have the
same level of influence on the outputs. In order to identify the most
sensitive parameters, those that can guide users in gathering
information on the ground and in the process of model calibration
and sensitivity analysis for the effect of each change made.
Mathematical models used for processing become very complex.
In this paper a fuzzy rule-based system is proposed as a solution
for this problem. The system collects the available signals
information from sensors. Moreover, the system allows the study of
the influence of the various factors that take part in the decision
system. Since its inception fuzzy set theory has been regarded as a
formalism suitable to deal with the imprecision intrinsic to many
problems. At the same time, fuzzy sets allow to use symbolic models.
In this study an example was applied for resolving variety of
physiological parameters that define human health state. The
application system was done for medical diagnosis help. The inputs
are the signals expressed the cardiovascular system parameters, blood
pressure, Respiratory system paramsystem was done, it will be able
to predict the state of patient according any input values.
Abstract: The effect of varying holding temperature on hatching success, occurrence of deformities and mortality rates were investigated for goldlined seabream eggs. Wild broodstock (600 g) were stocked at a 2:1 male-female ratio in a 2 m3 fiberglass tank supplied with filtered seawater (37 g L-1 salinity, temp. range 24±0.5 oC [day] and 22±1 oC [night], DO2 in excess of 5.0mg L-1). Females were injected with 200 IU kg-1 HCG between 08.00 and 10.00 h and returned to tanks to spawn following which eggs were collected by hand using a 100μm net. Fertilized eggs at the gastrulation stage (120 L-1) were randomly placed into one of 12 experimental 6 L aerated (DO2 5 mg L-1) plastic containers with water temperatures maintained at 24±0.5 oC (ambient), 26±0.5 oC, 28± 0.5 oC and 30±0.5 oC using thermostats. Each treatment was undertaken in triplicate using a 12:12 photophase:scotophase photoperiod. No differences were recorded between eggs reared at 24 and 26 oC with respect to viability, deformity, mortality or unhatched egg rates. Increasing temperature reduced the number of viable eggs with those at 30 oC returning poorest performance (P < 0.05). Mortality levels were lowest for eggs incubated at 24 and 26 oC. The greatest level of deformities recorded was that for eggs reared at 28 oC.
Abstract: Silicon is a beneficial element for plant growth. It
helps plants to overcome multiple stresses, alleviates metal toxicity
and improves nutrient imbalance. Field experiment was conducted as
split-split plot arranged in a randomized complete block design with
four replications. Irrigation system include continues flooding and
deficit as main plots and nitrogen rates N0, N46, N92, and N138 kg/ha
as sub plots and silicon rates Si0 & Si500 kg/ha as sub-subplots.
Results indicate that grain yield had not significant difference
between irrigation systems. Flooding irrigation had higher biological
yield than deficit irrigation whereas, no significant difference in grain
and straw yield. Nitrogen application increased grain, biological and
straw yield. Silicon application increased grain, biological and straw
yield but, decreased harvest index. Flooding irrigation had higher
number of total tillers / hill than deficit irrigation, but deficit
irrigation had higher number of fertile tillers / hill than flooding
irrigation. Silicon increased number of filled spikelet and decreased
blank spikelet. With high nitrogen application decreased 1000-grain
weight. It can be concluded that if the nitrogen application was high
and water supplied was available we could have silicon application
until increase grain yield.
Abstract: International literature emphasizes on the concern regarding the phenomenon of aggression in hospital. This paper focuses on the reality of aggressive interactions reigning within an emergency triage involving three chaps of protagonists: the professionals, the patients and their carers. The data collection was made from a grid of observation, in which the various variables exposed in the literature were integrated. They observations took place around the clock, for three weeks, at the rate of one week a month. In this research 331 aggressive interactions have been listed and analyzed by means of the software SPSS. This research is one of the very few continuous observation surveys in the literature. It shows the various human factors at play in the emergence of aggressive interaction. The data may be used both for taking steps in primary prevention, thanks to the analysis of interaction modes, and in secondary prevention by integrating the useful results in situational prevention.
Abstract: Transmission network expansion planning (TNEP) is an important component of power system planning that its task is to minimize the network construction and operational cost while satisfying the demand increasing, imposed technical and economic conditions. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, the lines adequacy rate has not been studied after the planning horizon, i.e. when the expanded network misses its adequacy and needs to be expanded again. In this paper, in order to take transmission lines condition after expansion in to account from the line loading view point, the adequacy of transmission network is considered for solution of STNEP problem. To obtain optimal network arrangement, a decimal codification genetic algorithm (DCGA) is being used for minimizing the network construction and operational cost. The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the annual worth of network adequacy has a considerable effect on the network arrangement. In addition, the obtained network, based on the DCGA, has lower investment cost and higher adequacy rate. Thus, the network satisfies the requirements of delivering electric power more safely and reliably to load centers.
Abstract: Analysis of blood vessel mechanics in normal and
diseased conditions is essential for disease research, medical device
design and treatment planning. In this work, 3D finite element
models of normal vessel and atherosclerotic vessel with 50% plaque
deposition were developed. The developed models were meshed
using finite number of tetrahedral elements. The developed models
were simulated using actual blood pressure signals. Based on the
transient analysis performed on the developed models, the parameters
such as total displacement, strain energy density and entropy per unit
volume were obtained. Further, the obtained parameters were used to
develop artificial neural network models for analyzing normal and
atherosclerotic blood vessels. In this paper, the objectives of the
study, methodology and significant observations are presented.
Abstract: The modified Claus process is the major technology
for the recovery of elemental sulfur from hydrogen sulfide. The
chemical reactions that can occur in the reaction furnace are
numerous and many byproducts such as carbon disulfide and carbon
carbonyl sulfide are produced. These compounds can often contribute
from 20 to 50% of the pollutants and therefore, should be hydrolyzed
in the catalytic converter. The inlet temperature of the first catalytic
reactor should be maintained over than 250 °C, to hydrolyze COS
and CS2. In this paper, the various configurations for the first
converter reheating of sulfur recovery unit are investigated. As a
result, the performance of each method is presented for a typical
clause unit. The results show that the hot gas method seems to be
better than the other methods.
Abstract: In this paper we used data mining techniques to
identify outlier patients who are using large amount of drugs over a
long period of time. Any healthcare or health insurance system
should deal with the quantities of drugs utilized by chronic diseases
patients. In Kingdom of Bahrain, about 20% of health budget is spent
on medications. For the managers of healthcare systems, there is no
enough information about the ways of drug utilization by chronic
diseases patients, is there any misuse or is there outliers patients. In
this work, which has been done in cooperation with information
department in the Bahrain Defence Force hospital; we select the data
for Cardiac patients in the period starting from 1/1/2008 to
December 31/12/2008 to be the data for the model in this paper. We
used three techniques for finding the drug utilization for cardiac
patients. First we applied a clustering technique, followed by
measuring of clustering validity, and finally we applied a decision
tree as classification algorithm. The clustering results is divided into
three clusters according to the drug utilization, for 1603 patients, who
received 15,806 prescriptions during this period can be partitioned
into three groups, where 23 patients (2.59%) who received 1316
prescriptions (8.32%) are classified to be outliers. The classification
algorithm shows that the use of average drug utilization and the age,
and the gender of the patient can be considered to be the main
predictive factors in the induced model.
Abstract: The incidence of oral cancer in Taiwan increased year
by year. It replaced the nasopharyngeal as the top incurrence among
head and neck cancers since 1994. Early examination and earlier
identification for earlier treatment is the most effective medical
treatment for these cancers. Although the government fully subsidized
the expenses with tremendous promotion program for oral cancer
screening, the citizen-s participation remained low. Purpose of this
study is to understand the factors affecting the citizens- behavior
intensions of taking an oral cancer screening. Based on the Theory of
Planned Behavior, this study adopted four distinctive variables in
explaining the captioned behavior intentions.700 questionnaires were
dispatched with 500 valid responses or 71.4% returned by the citizens
with an age 30 or above from the eastern counties of Taiwan. Test
results has shown that attitude toward, subjective norms of, and
perceived behavioral control over the oral cancer screening varied
from some demographic factors to another. The study proofed that
attitude toward, subjective norms of, and perceived behavioral control
over the oral cancer screening had positive impacts on the
corresponding behavior intention. The test concluded that the theory
of planned behavior was appropriate as a theoretical framework in
explaining the influencing factors of intentions of taking oral cancer
screening. This study suggested the healthcare professional should
provide high accessibility of screening services other than just
delivering knowledge on oral cancer to promote the citizens-
intentions of taking the captioned screening. This research also
provided a practical implication to the healthcare professionals when
formulating and implementing promotion instruments for lifting the
screening rate of oral cancer.
Abstract: Three reactor types were explored and successfully
used for pigment production by Monascus: shake flasks, and shaken
and stirred miniaturized reactors. Also, the use of dielectric
spectroscopy for the on-line measurement of biomass levels was
explored. Shake flasks gave good pigment yields, but scale up is
difficult, and they cannot be automated. Shaken bioreactors were less
successful with pigment production than stirred reactors.
Experiments with different impeller speeds in different volumes of
liquid in the reactor confirmed that this is most likely due oxygen
availability. The availability of oxygen appeared to affect biomass
levels less than pigment production; red pigment production in
particular needed very high oxygen levels. Dielectric spectroscopy
was effectively used to continuously measure biomass levels during
the submerged fungal fermentation in the shaken and stirred
miniaturized bioreactors, despite the presence of the solid substrate
particles. Also, the capacitance signal gave useful information about
the viability of the cells in the culture.
Abstract: Carbon tetrachloride (CCl4) is a well-known
hepatotoxin and exposure to this chemical is known to induce
oxidative stress and causes liver injury by the formation of free
radicals. Flacourtia indica commonly known as 'Baichi' has been
reported as an effective remedy for the treatment of a variety of
diseases. The objective of this study was to investigate the
hepatoprotective activity of aqueous extract of leaves of Flacourtia
indica against CCl4 induced hepatotoxicity. Animals were pretreated
with the aqueous extract of Flacourtia indica (250 & 500 mg/kg
body weight) for one week and then challenged with CCl4 (1.5 ml/kg
bw) in olive oil (1:1, v/v) on 7th day. Serum marker enzymes (ALP,
AST, ALT, Total Protein & Total Bilirubin) and TBARS level
(Marker for oxidative stress) were estimated in all the study groups.
Alteration in the levels of biochemical markers of hepatic damage
like AST, ALT, ALP, Total Protein, Total Bilirubin and lipid
peroxides (TBARS) were tested in both CCl4 treated and extract
treated groups. CCl4 has enhanced the AST, ALT, ALP and the
Lipid peroxides (TBARS) in liver. Treatment of aqueous extract of
Flacourtia indica leaves (250 & 500 mg/kg) exhibited a significant
protective effect by altering the serum levels of AST, ALT, ALP,
Total Protein, Total Bilirubin and liver TBARS. These biochemical
observations were supported by histopathological study of liver
sections. From this preliminary study it has been concluded that the
aqueous extract of the leaves of Flacourtia indica protects liver
against oxidative damages and could be used as an effective protector
against CCl4 induced hepatic damage. Our findings suggested that
Flacourtia indica possessed good hepatoprotective activity
Abstract: A prototype model of an emulsion separator was
designed and manufactured. Generally, it is a cylinder filled with
different fractal modules. The emulsion was fed into the reactor by a
peristaltic pump through an inlet placed at the boundary between the
two phases. For hydrodynamic design and sizing of the reactor the
assumptions of the theory of filtration were used and methods to
describe the separation process were developed. Based on this
methodology and using numerical methods and software of Autodesk
the process is simulated in different operating modes. The basic
hydrodynamic characteristics - speed and performance for different
types of fractal systems and decisions to optimize the design of the
reactor were also defined.
Abstract: In this study, The physico-chemical and nutritional
properties of `Musmula` Medlar (Mespilus germanica L.) fruit and
seed grown in Northeast Anatolia was investigated. In the fruit,
length, width, thickness, weight, total soluble solids, colour (1),
colour (2) [L, a, b values], protein, crude ash, crude fiber, crude oil,
texture and pH were determinated as 4.34 cm, 4.22 cm, 3.67 cm,
38.36 g, 23.97 %, S60O60Y41,, [53.85, 17.15, 33.75], 1.06 %, 0.79 %,
4.24 %, 0.005 %, 1.21 kg/cm2 and 4.26 respectively. Also, pulp ratio,
seed ratio and pulp/seed ratio were found to be 92.88 %, 7.11 % and
14.07 %, respectively. In addition, the mineral composition of medlar
fruit in Northeast Anatolia was studied. In the fruit, 23 minerals were
analyzed and 19 minerals were present at detectable levels. The
medlar fruit was richest in potassium (6962 ppm), calcium (1186.378
ppm), magnesium (1070.08 ppm) and phosphor (763.425 ppm).
Abstract: In this work we study elliptic divisibility sequences over
finite fields. MorganWard in [11, 12] gave arithmetic theory of elliptic
divisibility sequences. We study elliptic divisibility sequences, equivalence
of these sequences and singular elliptic divisibility sequences
over finite fields Fp, p > 3 is a prime.
Abstract: Robots- visual perception is a field that is gaining
increasing attention from researchers. This is partly due to emerging
trends in the commercial availability of 3D scanning systems or
devices that produce a high information accuracy level for a variety of
applications. In the history of mining, the mortality rate of mine workers
has been alarming and robots exhibit a great deal of potentials to
tackle safety issues in mines. However, an effective vision system
is crucial to safe autonomous navigation in underground terrains.
This work investigates robots- perception in underground terrains
(mines and tunnels) using statistical region merging (SRM) model.
SRM reconstructs the main structural components of an imagery
by a simple but effective statistical analysis. An investigation is
conducted on different regions of the mine, such as the shaft, stope
and gallery, using publicly available mine frames, with a stream of
locally captured mine images. An investigation is also conducted on a
stream of underground tunnel image frames, using the XBOX Kinect
3D sensors. The Kinect sensors produce streams of red, green and
blue (RGB) and depth images of 640 x 480 resolution at 30 frames per
second. Integrating the depth information to drivability gives a strong
cue to the analysis, which detects 3D results augmenting drivable and
non-drivable regions in 2D. The results of the 2D and 3D experiment
with different terrains, mines and tunnels, together with the qualitative
and quantitative evaluation, reveal that a good drivable region can be
detected in dynamic underground terrains.
Abstract: The ever-growing usage of aspect-oriented
development methodology in the field of software engineering
requires tool support for both research environments and industry. So
far, tool support for many activities in aspect-oriented software
development has been proposed, to automate and facilitate their
development. For instance, the AJaTS provides a transformation
system to support aspect-oriented development and refactoring. In
particular, it is well established that the abstract interpretation of
programs, in any paradigm, pursued in static analysis is best served
by a high-level programs representation, such as Control Flow Graph
(CFG). This is why such analysis can more easily locate common
programmatic idioms for which helpful transformation are already
known as well as, association between the input program and
intermediate representation can be more closely maintained.
However, although the current researches define the good concepts
and foundations, to some extent, for control flow analysis of aspectoriented
programs but they do not provide a concrete tool that can
solely construct the CFG of these programs. Furthermore, most of
these works focus on addressing the other issues regarding Aspect-
Oriented Software Development (AOSD) such as testing or data flow
analysis rather than CFG itself. Therefore, this study is dedicated to
build an aspect-oriented control flow graph construction tool called
AJcFgraph Builder. The given tool can be applied in many software
engineering tasks in the context of AOSD such as, software testing,
software metrics, and so forth.
Abstract: A dynamic risk management framework for software
projects is presented. Currently available software risk management
frameworks and risk assessment models are static in nature and lacks
feedback capability. Such risk management frameworks are not
capable of providing the risk assessment of futuristic changes in risk
events. A dynamic risk management framework for software project
is needed that provides futuristic assessment of risk events.