Abstract: A numerical simulation of micro Poiseuille flow has
performed for rarefied and compressible flow at slip flow regimes.
The wall roughness is simulated in two cases with triangular
microelements and random micro peaks distributed on wall surfaces
to study the effects of roughness shape and distribution on flow field.
Two values of Mach and Knudsen numbers have used to investigate
the effects of rarefaction as well as compressibility. The numerical
results have also checked with available theoretical and experimental
relations and good agreements has achieved. High influence of
roughness shape can be seen for both compressible and
incompressible rarefied flows. In addition it is found that rarefaction
has more significant effect on flow field in microchannels with
higher relative roughness. It is also found that compressibility has
more significant effects on Poiseuille number when relative
roughness increases.
Abstract: The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.
Abstract: The study was conducted to investigate the profile of
hepatitis in Kingdom of Saudi Arabia, and to determine which age
group hepatitis viruses most commonly infect. The epidemiology of
viral hepatitis in Saudi Arabia has undergone major changes,
concurrent with major socioeconomic developments over the last two
to three decades. This disease represents a major public health
problem in Saudi Arabia resulting in the need for considerable
healthcare resources. A retrospective cross sectional analysis of the
reported cases of viral hepatitis was conducted based on the reports
of The Ministry of Health in Saudi Arabia about Hepatitis A, B and C
infections in all regions from the period of January 2006 to December
2010. The study demonstrated that incidence of viral Hepatitis is
decreasing, except for Hepatitis B that showed minimal increase. Of
hepatitis A, B, and C, Hepatitis B virus (HBV) was the most
predominant type, accounting for (53%) of the cases, followed by
Hepatitis C virus (HCV) (30%) and HAV (17%). HAV infection
predominates in children (5–14 years) with 60% of viral hepatitis
cases, HBV in young adults (15–44 years) with 69% of viral hepatitis
cases, and HCV in older adults (>45 years) with 59% of viral
hepatitis cases. Despite significant changes in the prevalence of viral
hepatitis A, B and C, it remains a major public health problem in
Saudi Arabia; however, it showed a significant decline in the last two
decades that could be attributed to the vaccination programs and the
improved health facilities. Further researches are needed to identify
the risk factors making a specific age group or a specific region in
Saudi Arabia targeted for a specific type of hepatitis viruses.
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: 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: 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: 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: Based on Rayleigh beam theory, the sub-impacts of a
free-free beam struck horizontally by a round-nosed rigid mass is
simulated by the finite difference method and the impact-separation
conditions. In order to obtain the sub-impact force, a uniaxial
compression elastic-plastic contact model is employed to analyze the
local deformation field on contact zone. It is found that the horizontal
impact is a complicated process including the elastic plastic
sub-impacts in sequence. There are two sub-zones of sub-impact. In
addition, it found that the elastic energy of the free-free beam is more
suitable for the Poisson collision hypothesis to explain compression
and recovery processes.
Abstract: Spatial trends are one of the valuable patterns in geo
databases. They play an important role in data analysis and
knowledge discovery from spatial data. A spatial trend is a regular
change of one or more non spatial attributes when spatially moving
away from a start object. Spatial trend detection is a graph search
problem therefore heuristic methods can be good solution. Artificial
immune system (AIS) is a special method for searching and
optimizing. AIS is a novel evolutionary paradigm inspired by the
biological immune system. The models based on immune system
principles, such as the clonal selection theory, the immune network
model or the negative selection algorithm, have been finding
increasing applications in fields of science and engineering.
In this paper, we develop a novel immunological algorithm based
on clonal selection algorithm (CSA) for spatial trend detection. We
are created neighborhood graph and neighborhood path, then select
spatial trends that their affinity is high for antibody. In an
evolutionary process with artificial immune algorithm, affinity of
low trends is increased with mutation until stop condition is satisfied.
Abstract: The size, complexity and number of databases used
for protein information have caused bioinformatics to lag behind in
adapting to the need to handle this distributed information.
Integrating all the information from different databases into one
database is a challenging problem. Our main research is to develop a
tool which can be used to access and manipulate protein information
from difference databases. In our approach, we have integrated
difference databases such as Swiss-prot, PDB, Interpro, and EMBL
and transformed these databases in flat file format into relational
form using XML and Bioperl. As a result, we showed this tool can
search different sizes of protein information stored in relational
database and the result can be retrieved faster compared to flat file
database. A web based user interface is provided to allow user to
access or search for protein information in the local database.
Abstract: In this research it is aimed that the effect of some demographic factors on Turkish Adolescents' subjective well being is investigated. 432 adolescents who are 247 girls and 185 boys are participated in this study. They are ages 15-17, and also are high school students. The Positive and Negative Affect Scale and Life Satisfaction Scale are used for measuring adolescents' subjective well being. The ANOVA method is used in order to examine the effect of ages. For gender differences, independent t-test method is used, and finally the Pearson Correlation method is used so as to examine the effect of socio economic statues of adolescents' parents. According to results, there is no gender difference on adolescents' subjective well being. On the other hand, SES and age are effect significantly lover level on adolescents' subjective well being.
Abstract: An optimal power flow (OPF) based on particle swarm
optimization (PSO) was developed with more realistic generator
security constraint using the capability curve instead of only Pmin/Pmax
and Qmin/Qmax. Neural network (NN) was used in designing digital
capability curve and the security check algorithm. The algorithm is
very simple and flexible especially for representing non linear
generation operation limit near steady state stability limit and under
excitation operation area. In effort to avoid local optimal power flow
solution, the particle swarm optimization was implemented with
enough widespread initial population. The objective function used in
the optimization process is electric production cost which is
dominated by fuel cost. The proposed method was implemented at
Java Bali 500 kV power systems contain of 7 generators and 20
buses. The simulation result shows that the combination of generator
power output resulted from the proposed method was more economic
compared with the result using conventional constraint but operated
at more marginal operating point.
Abstract: The join dependency provides the basis for obtaining
lossless join decomposition in a classical relational schema. The
existence of Join dependency shows that that the tables always
represent the correct data after being joined. Since the classical
relational databases cannot handle imprecise data, they were
extended to fuzzy relational databases so that uncertain, ambiguous,
imprecise and partially known information can also be stored in
databases in a formal way. However like classical databases, the
fuzzy relational databases also undergoes decomposition during
normalization, the issue of joining the decomposed fuzzy relations
remains intact. Our effort in the present paper is to emphasize on this
issue. In this paper we define fuzzy join dependency in the
framework of type-1 fuzzy relational databases & type-2 fuzzy
relational databases using the concept of fuzzy equality which is
defined using fuzzy functions. We use the fuzzy equi-join operator
for computing the fuzzy equality of two attribute values. We also
discuss the dependency preservation property on execution of this
fuzzy equi- join and derive the necessary condition for the fuzzy
functional dependencies to be preserved on joining the decomposed
fuzzy relations. We also derive the conditions for fuzzy join
dependency to exist in context of both type-1 and type-2 fuzzy
relational databases. We find that unlike the classical relational
databases even the existence of a trivial join dependency does not
ensure lossless join decomposition in type-2 fuzzy relational
databases. Finally we derive the conditions for the fuzzy equality to
be non zero and the qualification of an attribute for fuzzy key.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.
Abstract: The precision of heat flux simulation influences the
temperature field and test aberration for TB test and also reflects the
test level for spacecraft development. This paper describes TB tests for
a small satellite using solar simulator, electric heaters, calrod heaters
to evaluate the difference of the three methods. Under the same
boundary condition, calrod heaters cases were about 6oC higher than
solar simulator cases and electric heaters cases for
non-external-heat-flux cases (extreme low temperature cases). While
calrod heaters cases and electric heaters cases were 5~7oC and 2~3oC
lower than solar simulator cases respectively for high temperature
cases. The results show that the solar simulator is better than calrod
heaters for its better collimation, non-homogeneity and stability.
Abstract: In this study, active tendons with Proportional Integral
Derivation type controllers were applied to a SDOF and a MDOF
building model. Physical models of buildings were constituted with
virtual springs, dampers and rigid masses. After that, equations of
motion of all degrees of freedoms were obtained. Matlab Simulink
was utilized to obtain the block diagrams for these equations of
motion. Parameters for controller actions were found by using a trial
method. After earthquake acceleration data were applied to the
systems, building characteristics such as displacements, velocities,
accelerations and transfer functions were analyzed for all degrees of
freedoms. Comparisons on displacement vs. time, velocity vs. time,
acceleration vs. time and transfer function (Db) vs. frequency (Hz)
were made for uncontrolled and controlled buildings. The results
show that the method seems feasible.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in the form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studied with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: This article outlines conceptualization and
implementation of an intelligent system capable of extracting
knowledge from databases. Use of hybridized features of both the
Rough and Fuzzy Set theory render the developed system flexibility
in dealing with discreet as well as continuous datasets. A raw data set
provided to the system, is initially transformed in a computer legible
format followed by pruning of the data set. The refined data set is
then processed through various Rough Set operators which enable
discovery of parameter relationships and interdependencies. The
discovered knowledge is automatically transformed into a rule base
expressed in Fuzzy terms. Two exemplary cancer repository datasets
(for Breast and Lung Cancer) have been used to test and implement
the proposed framework.
Abstract: Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.