Abstract: The effect of beak trimming on behavior of two strains
of Thai native pullets kept in floor pens was studied. Six general
activities (standing, crouching, moving, comforting, roosting, and
nesting), 6 beak related activities (preening, feeding, drinking,
pecking at inedible object, feather pecking, and litter pecking), and 4
agonistic activities (head pecking, threatening, avoiding, and fighting)
were measured twice a for 15 consecutive days, started when the
pullets were 19 wk old. It was found that beak trimmed pullets drank
more frequent (P
Abstract: Appropriate description of business processes through
standard notations has become one of the most important assets for
organizations. Organizations must therefore deal with quality faults
in business process models such as the lack of understandability and
modifiability. These quality faults may be exacerbated if business
process models are mined by reverse engineering, e.g., from existing
information systems that support those business processes. Hence,
business process refactoring is often used, which change the internal
structure of business processes whilst its external behavior is
preserved. This paper aims to choose the most appropriate set of
refactoring operators through the quality assessment concerning
understandability and modifiability. These quality features are
assessed through well-proven measures proposed in the literature.
Additionally, a set of measure thresholds are heuristically established
for applying the most promising refactoring operators, i.e., those that
achieve the highest quality improvement according to the selected
measures in each case.
Abstract: Group-III nitride material as particularly AlxGa1-xN is
one of promising optoelectronic materials to require for shortwavelength
devices. To achieve the high-quality AlxGa1-xN films for
a high performance of such devices, AlN-nucleation layers are the
important factor. To improve the AlN-nucleation layers with a
variation of Ga-addition, XRD measurements were conducted to
analyze the crystalline quality of the subsequent Al0.1Ga0.9N with the
minimum ω-FWHMs of (0002) and (10-10) reflections of 425 arcsec
and 750 arcsec, respectively. SEM and AFM measurements were
performed to observe the surface morphology and TEM
measurements to identify the microstructures and orientations.
Results showed that the optimized Ga-atoms in the Al(Ga)Nnucleation
layers improved the surface diffusion to form moreuniform
crystallites in structure and size, better alignment of each
crystallite, and better homogeneity of island distribution. This, hence,
improves the orientation of epilayers on the Si-surface and finally
improves the crystalline quality and reduces the residual strain of
subsequent Al0.1Ga0.9N layers.
Abstract: The back propagation algorithm calculates the weight
changes of artificial neural networks, and a common approach is to
use a training algorithm consisting of a learning rate and a
momentum factor. The major drawbacks of above learning algorithm
are the problems of local minima and slow convergence speeds. The
addition of an extra term, called a proportional factor reduces the
convergence of the back propagation algorithm. We have applied the
three term back propagation to multiplicative neural network
learning. The algorithm is tested on XOR and parity problem and
compared with the standard back propagation training algorithm.
Abstract: Pharmaceutical industries and effluents of sewage treatment plants are the main sources of residual pharmaceuticals in water resources. These emergent pollutants may adversely impact the biophysical environment. Pharmaceutical industries often generate wastewater that changes in characteristics and quantity depending on the used manufacturing processes. Carbamazepine (CBZ), {5Hdibenzo [b,f]azepine-5-carboxamide, (C15H12N2O)}, is a significant non-biodegradable pharmaceutical contaminant in the Jordanian pharmaceutical wastewater, which is not removed by the activated sludge processes in treatment plants. Activated carbon may potentially remove that pollutant from effluents, but the high cost involved suggests that more attention should be given to the potential use of low-cost materials in order to reduce cost and environmental contamination. Powders of Jordanian non-metallic raw materials namely, Azraq Bentonite (AB), Kaolinite (K), and Zeolite (Zeo) were activated (acid and thermal treatment) and evaluated by removing CBZ. The results of batch and column techniques experiments showed around 46% and 67% removal of CBZ respectively.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.
Abstract: The belief K-modes method (BKM) approach is a new
clustering technique handling uncertainty in the attribute values of
objects in both the cluster construction task and the classification one.
Like the standard version of this method, the BKM results depend on
the chosen initial modes. So, one selection method of initial modes
is developed, in this paper, aiming at improving the performances of
the BKM approach. Experiments with several sets of real data show
that by considered the developed selection initial modes method, the
clustering algorithm produces more accurate results.
Abstract: The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.
Abstract: This paper discusses the landscape design that could
increase energy efficiency in a house. By planting trees in a house
compound, the tree shades prevent direct sunlight from heating up
the building, and it enables cooling off the surrounding air. The
requirement for air-conditioning could be minimized and the air
quality could be improved. During the life time of a tree, the saving
cost from the mentioned benefits could be up to US $ 200 for each
tree. The project intends to visually describe the landscape design in
a house compound that could enhance energy efficiency and
consequently lead to energy saving. The house compound model was
developed in three dimensions by using AutoCAD 2005, the
animation was programmed by using LightWave 3D softwares i.e.
Modeler and Layout to display the tree shadings in the wall. The
visualization was executed on a VRML Pad platform and
implemented on a web environment.
Abstract: This study investigated the seasonal prevalence of
Aedes aegypti and Ae. albopictus larvae in three topographical areas
(i.e. mangrove, rice paddy and mountainous areas). Samples were
collected from 300 households in both wet and dry seasons in nine
districts in Nakhon Si Thammarat province. Ae. aegypti and Ae.
albopictus were found in 21 out of 29 types of water containers in
mangrove, rice paddy and mountainous areas. Ae. aegypti and Ae.
albopictus laid eggs in different container types depending on season
and topographical areas. Ae. aegypti larvae were found most in metal
box in mangrove and mountainous areas in wet season. Ae.
albopictus larvae were also found most in metal box in mangrove and
mountainous areas in both wet and dry seasons. All Ae. albopictus
larval indices were higher than Ae. aegypti larval indices in all three
topographical areas and both seasons. HI and BI did not differ in
three topographical areas but differed between Aedes sp. HI for both
Ae. aegypti and Ae. albopictus in all three topographical areas in both
seasons were greater than 10 %, except Aedes aegypti in rice paddy
area in wet season. This indicated high risks of DHF transmission in
these areas.
Abstract: To investigate the energy performance of solar shading devices, this paper carried out a survey on the current status of solar shading utilization in buildings in Ningbo and performed building simulations to evaluate the energy savings potential by adopting different solar shading devices. Results show that solar shading utilization in this area is not popular and effective, and should be considered firstly in the design stage since the potential for energy savings is up to 6.8% for residential buildings and 9.4% for commercial buildings.
Abstract: For more than 120 years, gold mining formed the
backbone the South Africa-s economy. The consequence of mine
closure was observed in large-scale land degradation and widespread
pollution of surface water and groundwater. This paper investigates
the feasibility of using natural zeolite in removing heavy metals
contaminating the Wonderfonteinspruit Catchment Area (WCA), a
water stream with high levels of heavy metals and radionuclide
pollution. Batch experiments were conducted to study the adsorption
behavior of natural zeolite with respect to Fe2+, Mn2+, Ni2+, and Zn2+.
The data was analysed using the Langmuir and Freudlich isotherms.
Langmuir was found to correlate the adsorption of Fe2+, Mn2+, Ni2+,
and Zn2+ better, with the adsorption capacity of 11.9 mg/g, 1.2 mg/g,
1.3 mg/g, and 14.7 mg/g, respectively. Two kinetic models namely,
pseudo-first order and pseudo second order were also tested to fit the
data. Pseudo-second order equation was found to be the best fit for
the adsorption of heavy metals by natural zeolite. Zeolite
functionalization with humic acid increased its uptake ability.
Abstract: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: The objective of this research is to study of microbial lipid production by locally photosynthetic microalgae and oleaginous yeast via integrated cultivation technique using CO2 emissions from yeast fermentation. A maximum specific growth rate of Chlorella sp. KKU-S2 of 0.284 (1/d) was obtained under an integrated cultivation and a maximum lipid yield of 1.339g/L was found after cultivation for 5 days, while 0.969g/L of lipid yield was obtained after day 6 of cultivation time by using CO2 from air. A high value of volumetric lipid production rate (QP, 0.223 g/L/d), specific product yield (YP/X, 0.194), volumetric cell mass production rate (QX, 1.153 g/L/d) were found by using ambient air CO2 coupled with CO2 emissions from yeast fermentation. Overall lipid yield of 8.33 g/L was obtained (1.339 g/L of Chlorella sp. KKU-S2 and 7.06g/L of T. maleeae Y30) while low lipid yield of 0.969g/L was found using non-integrated cultivation technique. To our knowledge this is the unique report about the lipid production from locally microalgae Chlorella sp. KKU-S2 and yeast T. maleeae Y30 in an integrated technique to improve the biomass and lipid yield by using CO2 emissions from yeast fermentation.
Abstract: As the gradual increase of the enterprise scale, the
firms may possess many manufacturing plants located in different
places geographically. This change will result in the multi-site
production planning problems under the environment of multiple
plants or production resources. Our research proposes the structural
framework to analyze the multi-site planning problems. The analytical
framework is composed of six elements: multi-site conceptual model,
product structure (bill of manufacturing), production strategy,
manufacturing capability and characteristics, production planning
constraints, and key performance indicators. As well as the discussion
of these six ingredients, we also review related literatures in this paper
to match our analytical framework. Finally we take a real-world
practical example of a TFT-LCD manufacturer in Taiwan to explain
our proposed analytical framework for the multi-site production
planning problems.
Abstract: Clustering in high dimensional space is a difficult
problem which is recurrent in many fields of science and
engineering, e.g., bioinformatics, image processing, pattern
reorganization and data mining. In high dimensional space some of
the dimensions are likely to be irrelevant, thus hiding the possible
clustering. In very high dimensions it is common for all the objects in
a dataset to be nearly equidistant from each other, completely
masking the clusters. Hence, performance of the clustering algorithm
decreases.
In this paper, we propose an algorithmic framework which
combines the (reduct) concept of rough set theory with the k-means
algorithm to remove the irrelevant dimensions in a high dimensional
space and obtain appropriate clusters. Our experiment on test data
shows that this framework increases efficiency of the clustering
process and accuracy of the results.
Abstract: Short Message Service (SMS) has grown in
popularity over the years and it has become a common way of
communication, it is a service provided through General System
for Mobile Communications (GSM) that allows users to send text
messages to others.
SMS is usually used to transport unclassified information, but
with the rise of mobile commerce it has become a popular tool for
transmitting sensitive information between the business and its
clients. By default SMS does not guarantee confidentiality and
integrity to the message content.
In the mobile communication systems, security (encryption)
offered by the network operator only applies on the wireless link.
Data delivered through the mobile core network may not be
protected. Existing end-to-end security mechanisms are provided
at application level and typically based on public key
cryptosystem.
The main concern in a public-key setting is the authenticity of
the public key; this issue can be resolved by identity-based (IDbased)
cryptography where the public key of a user can be derived
from public information that uniquely identifies the user.
This paper presents an encryption mechanism based on the IDbased
scheme using Elliptic curves to provide end-to-end security
for SMS. This mechanism has been implemented over the standard
SMS network architecture and the encryption overhead has been
estimated and compared with RSA scheme. This study indicates
that the ID-based mechanism has advantages over the RSA
mechanism in key distribution and scalability of increasing
security level for mobile service.
Abstract: Using mobile Internet access technologies and eservices,
various economic agents can efficiently offer their products
or services to a large number of clients. With the support of mobile
communications networks, the clients can have access to e-services,
anywhere and anytime. This is a base to establish a convergence of
technological and financial interests of mobile operators, software
developers, mobile terminals producers and e-content providers. In
this paper, a client server system is presented, using 3G, EDGE,
mobile terminals, for Stock Exchange e-services access.
Abstract: Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.