Abstract: The purpose of the study was to determine if, among
32 brain injured adults in community rehabilitation programs, there is
a statistically significant relationship between the degree of severity
of brain injury and these adults- level of self-esteem and stress. The
researcher hypothesized there would be a statistically significant
difference and a statistically significant relationship in self-esteem
and stress levels among and TBI adults. A Pearson product moment
correlational analysis was implemented and results found a
statistically significant relationship between self-esteem and stress
levels. Future recommendations were suggested upon completion of
research.
Abstract: Lately, significant work in the area of Intelligent
Manufacturing has become public and mainly applied within the
frame of industrial purposes. Special efforts have been made in the
implementation of new technologies, management and control
systems, among many others which have all evolved the field. Aware
of all this and due to the scope of new projects and the need of
turning the existing flexible ideas into more autonomous and
intelligent ones, i.e.: Intelligent Manufacturing, the present paper
emerges with the main aim of contributing to the design and analysis
of the material flow in either systems, cells or work stations under
this new “intelligent" denomination. For this, besides offering a
conceptual basis in some of the key points to be taken into account
and some general principles to consider in the design and analysis of
the material flow, also some tips on how to define other possible
alternative material flow scenarios and a classification of the states a
system, cell or workstation are offered as well. All this is done with
the intentions of relating it with the use of simulation tools, for which
these have been briefly addressed with a special focus on the Witness
simulation package. For a better comprehension, the previous
elements are supported by a detailed layout, other figures and a few
expressions which could help obtaining necessary data. Such data and
others will be used in the future, when simulating the scenarios in the
search of the best material flow configurations.
Abstract: The objective of this paper is to construct a creativity
composite index designed to capture the growing role of creativity in
driving economic and social development for the 27 European Union
countries.
The paper proposes a new approach for the measurement of EU-27
creative potential and for determining its capacity to attract and
develop creative human capital. We apply a modified version of the
3T model developed by Richard Florida and Irene Tinagli for
constructing a Euro-Creativity Index. The resulting indexes establish
a quantitative base for policy makers, supporting their efforts to
determine the contribution of creativity to economic development.
Abstract: Supersonic hydrogen-air cylindrical mixing layer is
numerically analyzed to investigate the effect of inlet swirl on
ignition time delay in scramjets. Combustion is treated using detail
chemical kinetics. One-equation turbulence model of Spalart and
Allmaras is chosen to study the problem and advection upstream
splitting method is used as computational scheme. The results show
that swirling both fuel and oxidizer streams may drastically decrease
the ignition distance in supersonic combustion, unlike using the swirl
just in fuel stream which has no helpful effect.
Abstract: Candida albicans ATCC 10231 had low endogenous activity of the alternative oxidase compared with that of C. albicans ATCC 10261. In C. albicans ATCC 10231 the endogenous activity declined as the cultures aged. Alternative oxidase activity could be induced in C. albicans ATCC 10231 by treatment with cyanide, but the induction of this activity required the presence of oxygen which could be replaced, at least in part, with high concentrations of potassium ferricyanide. We infer from this that the expression of the gene encoding the alternative oxidase is under the control of a redoxsensitive transcription factor.
Abstract: In this paper we present semantic assistant agent
(SAA), an open source digital library agent which takes user query
for finding information in the digital library and takes resources-
metadata and stores it semantically. SAA uses Semantic Web to
improve browsing and searching for resources in digital library. All
metadata stored in the library are available in RDF format for
querying and processing by SemanSreach which is a part of SAA
architecture. The architecture includes a generic RDF-based model
that represents relationships among objects and their components.
Queries against these relationships are supported by an RDF triple
store.
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: The paper presents a simple and an accurate formula
that has been developed for the conduction angle (δ) of a single
phase half-wave or full-wave controlled rectifier with RL load. This
formula can be also used for calculating the conduction angle (δ) in
case of A.C. voltage regulator with inductive load under
discontinuous current mode. The simulation results shows that the
conduction angle calculated from the developed formula agree very
well with that obtained from the exact solution arrived from the
iterative method. Applying the developed formula can reduce the
computational time and reduce the time for manual classroom
calculation. In addition, the proposed formula is attractive for real
time implementations.
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 main aim of this research is to develop a methodology to encourage people's awareness, knowledge and understanding on the participation of flood management for cultural heritage, as the cooperation and interaction among government section, private section, and public section through role-play gaming simulation theory. The format of this research is to develop Role-play gaming simulation from existing documents, game or role-playing from several sources and existing data of the research site. We found that role-play gaming simulation can be implemented to help improving the understanding of the existing problem and the impact of the flood on cultural heritage, and the role-play game can be developed into the tool to improve people's knowledge, understanding and awareness about people's participation for flood management on cultural heritage, moreover the cooperation among the government, private section and public section will be improved through the theory of role-play gaming simulation.
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: The approach of subset selection in polynomial
regression model building assumes that the chosen fixed full set of
predefined basis functions contains a subset that is sufficient to
describe the target relation sufficiently well. However, in most cases
the necessary set of basis functions is not known and needs to be
guessed – a potentially non-trivial (and long) trial and error process.
In our research we consider a potentially more efficient approach –
Adaptive Basis Function Construction (ABFC). It lets the model
building method itself construct the basis functions necessary for
creating a model of arbitrary complexity with adequate predictive
performance. However, there are two issues that to some extent
plague the methods of both the subset selection and the ABFC,
especially when working with relatively small data samples: the
selection bias and the selection instability. We try to correct these
issues by model post-evaluation using Cross-Validation and model
ensembling. To evaluate the proposed method, we empirically
compare it to ABFC methods without ensembling, to a widely used
method of subset selection, as well as to some other well-known
regression modeling methods, using publicly available data sets.
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.