Abstract: Thailand is one of the world-s leaders of rice
producers and exporters. Farmers have to increase the rice cultivation
frequency for serving the national increasing of export-s demand. It
leads to an elimination of rice residues by open burning which is the
quickest and costless management method. The open burning of rice
residue is one of the major causes of air pollutants and greenhouse
gas (GHG) emission. Under ASEAN agreement on trans-boundary
haze, Thailand set the master plan to mitigate air pollutant emission
from open burning of agricultural residues. In this master plan,
residues incorporation is promoted as alternative management
method to open burning. However, the assessment of both options in
term of GHG emission in order to investigate their contribution to
long-term global warming is still scarce or inexistent. In this study, a
method on rice residues assessment was first developed in order to
estimate and compare GHG emissions from rice cultivation under
rice residues open burning and the case with incorporation of the
same amount of rice residues, using 2006 IPCC guidelines for
emission estimation and Life Cycle Analysis technique. The
emission from rice cultivation in different preparing area practice
was also discussed.
Abstract: Hospitals in southern Hualien teamed with the
Hypertension Joint Care Network. Working with the network, the
team provided a special designed health education to the individual
who had been identified as a hypertension patient in the outpatient
department. Some metabolism improvements achieved. This is a
retrospective study by purposively taking 106 patients from a hospital
between 2008 and 2010. Records of before and after education
intervention of the objects was collected and analyzed to see the how
the intervention affected the patients- hypertension control via clinical
parameter monitoring. The results showed that the clinical indicators,
the LDL-C, the cholesterol and the systolic blood pressure were
significantly improved. The study provides evidence for the
effectiveness of the network in controlling hypertension.
Abstract: In this paper, perceptions of actors on changes in
crop productivity, quantity and quality of water, and determinants of
their perception are analyzed using descriptive statistics and ordered
logit model. Data collected from 297 Ethiopian farmers and 103
agricultural professionals from December 2009 to January 2010 are
employed. Results show that the majority of the farmers and
professionals recognized decline in water resources, reasoning
climate changes and soil erosion as some of the causes. However,
there is a variation in views on changes in productivity. The
household asset, education level, age and geographical positions are
found to affect farmers- perception on changes in crop productivity.
But, the study underlines that there is no evidence that farmers-
economic status, age, or education level affects recognition of
degradation of water resources. Thus, more focus shall be given on
providing them different coping mechanisms and alternative
resource conserving technologies than educating about the
problems.
Abstract: In this paper we present an extension to Vision Based
LRTA* (VLRTA*) known as Vision Based Moving Target Search
(VMTS) for capturing unknown moving target in unknown territory
with randomly generated obstacles. Target position is unknown to the
agents and they cannot predict its position using any probability
method. Agents have omni directional vision but can see in one
direction at some point in time. Agent-s vision will be blocked by the
obstacles in the search space so agent can not see through the
obstacles. Proposed algorithm is evaluated on large number of
scenarios. Scenarios include grids of sizes from 10x10 to 100x100.
Grids had obstacles randomly placed, occupying 0% to 50%, in
increments of 10%, of the search space. Experiments used 2 to 9
agents for each randomly generated maze with same obstacle ratio.
Observed results suggests that VMTS is effective in locate target
time, solution quality and virtual target. In addition, VMTS becomes
more efficient if the number of agents is increased with proportion to
obstacle ratio.
Abstract: In intensity modulated radiation therapy (IMRT)
treatment planning, beam angles are usually preselected on the basis of
experience and intuition. Therefore, getting an appropriate beam
configuration needs a very long time. Based on the present situation,
the paper puts forward beam orientation optimization using ant colony
optimization (ACO). We use ant colony optimization to select the
beam configurations, after getting the beam configuration using
Conjugate Gradient (CG) algorithm to optimize the intensity profiles.
Combining with the information of the effect of pencil beam, we can
get the global optimal solution accelerating. In order to verify the
feasibility of the presented method, a simulated and clinical case was
tested, compared with dose-volume histogram and isodose line
between target area and organ at risk. The results showed that the
effect was improved after optimizing beam configurations. The
optimization approach could make treatment planning meet clinical
requirements more efficiently, so it had extensive application
perspective.
Abstract: With the widespread growth of applications of
Wireless Sensor Networks (WSNs), the need for reliable security
mechanisms these networks has increased manifold. Many security
solutions have been proposed in the domain of WSN so far. These
solutions are usually based on well-known cryptographic
algorithms.
In this paper, we have made an effort to survey well known
security issues in WSNs and study the behavior of WSN nodes that
perform public key cryptographic operations. We evaluate time
and power consumption of public key cryptography algorithm for
signature and key management by simulation.
Abstract: Multidrug resistant organisms have been taunting the
medical world for the last few decades. Even with new antibiotics
developed, resistant strains have emerged soon after. With the
advancement of nanotechnology, we investigated colloidal silver
nanoparticles for its antimicrobial activity against Pseudomonas
aeruginosa. This organism is a multidrug resistant which contributes
to the high morbidity and mortality in immunocompromised patients.
Five multidrug resistant strains were used in this study. The
antimicrobial effect was studied using the disc diffusion and broth
dilution techniques. An inhibition zone of 11 mm was observed with
10 μg dose of the nanoparticles. The nanoparticles exhibited MIC of
50 μg/ml when added at the lag phase and the subinhibitory
concentration was measured as 100 μg/ml. The MIC50 value showed
to be 15 μg/ml. This study suggests that silver nanoparticles can be
further developed as an antimicrobial agent, hence decreasing the
burden of the multidrug resistance phenomena.
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: In this paper, we present a novel objective nonreference
performance assessment algorithm for image fusion. It takes
into account local measurements to estimate how well the important
information in the source images is represented by the fused image.
The metric is based on the Universal Image Quality Index and uses
the similarity between blocks of pixels in the input images and the
fused image as the weighting factors for the metrics. Experimental
results confirm that the values of the proposed metrics correlate well
with the subjective quality of the fused images, giving a significant
improvement over standard measures based on mean squared error
and mutual information.
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: It is shown that the relationship of tick-borne
encephalitis virus with the human body comes in two ways, the
development of acute infection with the outcome in convalescence
and long stay by the virus in the body, its persistence in the nervous
tissue with periodic reactivation and prolonged circulating
immunoglobulin M. In spite of the fact that tick-borne encephalitis
virus has a tropism for nerve tissue, involvement in the process of
blood cells is an integral component of the infection. Comprehensive
study of the relation of factors of innate and adaptive immunity in the
tick-borne encephalitis providing insight into the features of chronic
disease.
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: Many organisations are nowadays interested to adopt
lean manufacturing strategy that would enable them to compete in
this competitive globalisation market. In this respect, it is necessary
to assess the implementation of lean manufacturing in different
organisations so that the important best practices can be identified.
This paper describes the development of key areas which will be
used to assess the adoption and implementation of lean
manufacturing practices. There are some key areas developed to
evaluate and reduce the most optimal projects so as to enhance their
production efficiency and increase the purpose of the economic
benefits of the manufacturing unit.
Lean manufacturing is becoming lean enterprise by treating its
customers and suppliers as partners. This gives the extra edge in
today-s cost and time competitive markets. The organisation is
becoming strong in all the conventional competition points. They are
Price, Quality and Delivery. Lean enterprise owners can deliver high
quality products quickly, with low price.
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: In the present study, the effects of ultrasound as
emerging technology were investigated on germination stimulation,
amount of alpha-amylase activity on dry barley seeds before steeping
stage of malting process. All experiments were carried out at 20 KHz
on the ultrasonic generator in 3 different ultrasonic intensities (20, 60
and 100% setting from total power of device) and time (5, 10 and 15
min) at constant temperature (30C). For determining the effects of
these parameters on enzyme the Fuwa method assay based on the
decreased staining value of blue starch–iodine complexes employed
for measurement an activity. The results of these assays were
analyzed by Qualitek4 software using the Taguchi statistical method
to evaluate the factor-s effects on enzyme activity. It has been found
that when malting barley is irradiated with an ultrasonic power, a
stimulating effect occurs as to the enzyme activity.
Abstract: In this study, a low temperature sensor highly selective to CO in presence of methane is fabricated by using 4 nm SnO2 quantum dots (QDs) prepared by sonication assisted precipitation. SnCl4 aqueous solution was precipitated by ammonia under sonication, which continued for 2 h. A part of the sample was then dried and calcined at 400°C for 1.5 h and characterized by XRD and BET. The average particle size and the specific surface area of the SnO2 QDs as well as their sensing properties were compared with the SnO2 nano-particles which were prepared by conventional sol-gel method. The BET surface area of sonochemically as-prepared product and the one calcined at 400°C after 1.5 hr are 257 m2/gr and 212 m2/gr respectively while the specific surface area for SnO2 nanoparticles prepared by conventional sol-gel method is about 80m2/gr. XRD spectra revealed pure crystalline phase of SnO2 is formed for both as-prepared and calcined samples of SnO2 QDs. However, for the sample prepared by sol-gel method and calcined at 400°C SnO crystals are detected along with those of SnO2. Quantum dots of SnO2 show exceedingly high sensitivity to CO with different concentrations of 100, 300 and 1000 ppm in whole range of temperature (25- 350°C). At 50°C a sensitivity of 27 was obtained for 1000 ppm CO, which increases to a maximum of 147 when the temperature rises to 225°C and then drops off while the maximum sensitivity for the SnO2 sample prepared by the sol-gel method was obtained at 300°C with the amount of 47.2. At the same time no sensitivity to methane is observed in whole range of temperatures for SnO2 QDs. The response and recovery times of the sensor sharply decreases with temperature, while the high selectivity to CO does not deteriorate.
Abstract: The great challenge of the agricultural sector is to
produce more crop from less water, which can be achieved by
increasing crop water productivity. The modernization of the
irrigation systems offers a number of possibilities to expand the
economic productivity of water and improve the virtual water status.
The objective of the present study is to assess the global water
productivity (GWP) within the major irrigation command areas of
I.R. Iran. For this purpose, fourteen irrigation command areas where
located in different areas of Iran were selected. In order to calculate
the global water productivity of irrigation command areas, all data on
the delivered water to cropping pattern, cultivated area, crops water
requirement, and yield production rate during 2002-2006 were
gathered. In each of the command areas it seems that the cultivated
crops have a higher amount of virtual water and thus can be replaced
by crops with less virtual water. This is merely suggested due to crop
water consumption and at the time of replacing crops, economic
value as well as cultural and political factors must be considered. The
results indicated that the lowest GWP belongs to Mahyar and
Borkhar irrigation areas, 0.24 kg m-3, and the highest is that of the
Dez irrigation area, 0.81 kg m-3. The findings demonstrated that
water management in the two irrigation areas is just efficient. The
difference in the GWP of irrigation areas is due to variations in the
cropping pattern, amount of crop productions, in addition to the
effective factors in the water use efficiency in the irrigation areas.
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: 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.