Abstract: The paper presents a one-dimensional transient
mathematical model of compressible non-isothermal multicomponent
fluid mixture flow in a pipe. The set of the mass,
momentum and enthalpy conservation equations for gas phase is
solved in the model. Thermo-physical properties of multi-component
gas mixture are calculated by solving the Equation of State (EOS)
model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas
mixture viscosity is calculated on the basis of the Lee-Gonzales-
Eakin (LGE) correlation. Numerical analysis of rapid gas
decompression process in rich and base natural gases is made on the
basis of the proposed mathematical model. The model is successfully
validated on the experimental data [1]. The proposed mathematical
model shows a very good agreement with the experimental data [1] in
a wide range of pressure values and predicts the decompression in
rich and base gas mixtures much better than analytical and
mathematical models, which are available from the open source
literature.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.
Abstract: The software industry has been considered a critical
infrastructure for any nation. Several studies have indicated that
national competitiveness increasingly depends upon Information and
Communication Technology (ICT), and software is one of the major
components of ICT, important for both large and small enterprises.
Even though there has been strong growth in the software industry in
Thailand, the industry has faced many challenges and problems that
need to be resolved. For example, the amount of pirated software has
been rising, and Thailand still has a large gap in the digital divide.
Additionally, the adoption among SMEs has been slow. This paper
investigates various issues in the software industry in Thailand, using
information acquired through analysis of secondary sources,
observation, and focus groups. The results of this study can be used
as “lessons learned" for the development of the software industry in
any developing country.
Abstract: In this research, the use of light beam size to design the adjustable mirror bender is presented. The focused beam line characterized by its size towards the synchrotron light beam line is investigated. The COSMOSWorks is used in all simulation components of curvature adjustment system to analyze in finite element method. The results based on simulation covers the use of applied forces during adjustment of the mirror radius are presented.
Abstract: The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.
Abstract: Principle component analysis is often combined with
the state-of-art classification algorithms to recognize human faces.
However, principle component analysis can only capture these
features contributing to the global characteristics of data because it is a
global feature selection algorithm. It misses those features
contributing to the local characteristics of data because each principal
component only contains some levels of global characteristics of data.
In this study, we present a novel face recognition approach using
non-negative principal component analysis which is added with the
constraint of non-negative to improve data locality and contribute to
elucidating latent data structures. Experiments are performed on the
Cambridge ORL face database. We demonstrate the strong
performances of the algorithm in recognizing human faces in
comparison with PCA and NREMF approaches.
Abstract: Rotation or tilt present in an image capture by digital
means can be detected and corrected using Artificial Neural Network
(ANN) for application with a Face Recognition System (FRS). Principal
Component Analysis (PCA) features of faces at different angles
are used to train an ANN which detects the rotation for an input image
and corrected using a set of operations implemented using another
system based on ANN. The work also deals with the recognition
of human faces with features from the foreheads, eyes, nose and
mouths as decision support entities of the system configured using
a Generalized Feed Forward Artificial Neural Network (GFFANN).
These features are combined to provide a reinforced decision for
verification of a person-s identity despite illumination variations. The
complete system performing facial image rotation detection, correction
and recognition using re-enforced decision support provides a
success rate in the higher 90s.
Abstract: Lean manufacturing is a production philosophy made
popular by Toyota Motor Corporation (TMC). It is globally known as
the Toyota Production System (TPS) and has the ultimate aim of
reducing cost by thoroughly eliminating wastes or muda. TPS
embraces the Just-in-time (JIT) manufacturing; achieving cost
reduction through lead time reduction. JIT manufacturing can be
achieved by implementing Pull system in the production.
Furthermore, TPS aims to improve productivity and creating
continuous flow in the production by arranging the machines and
processes in cellular configurations. This is called as Cellular
Manufacturing Systems (CMS). This paper studies on integrating the
CMS with the Pull system to establish a Big Island-Pull system
production for High Mix Low Volume (HMLV) products in an
automotive component industry. The paper will use the build-in JIT
system steps adapted from TMC to create the Pull system production
and also create a shojinka line which, according to takt time, has the
flexibility to adapt to demand changes simply by adding and taking
out manpower. This will lead to optimization in production.
Abstract: Sesame is one of the oldest and most important oil
crops as main crop and second crop agriculture. This study was
carried out to determine the effects of different inter- and intra-row
spacings on the yield and yield components on second crop sesame;
was set up in Antalya West Mediterranean Agricultural Research
Institue in 2009. Muganlı 57 sesame cultivar was used as plant
material. The field experiment was set up in a split plot design and
row spacings (30, 40, 50, 60 and 70 cm) were assigned to the main
plots and and intra-row spacings (5, 10, 20 and 30 cm) were assigned
to the subplots. Seed yield, oil ratio, oil yield, protein ratio and
protein yield were investigated. In general, wided inter row spacings
and intra-row spacings, resulted in decreased seed yield, oil yield and
protein yield. The highest seed yield, oil yield and protein yield
(respectively, 1115.0 kg ha-1, 551.3 kg ha-1, 224.7 kg ha-1) were
obtained from 30x5 cm plant density while the lowest seed yield, oil
yield and protein yield (respectively, 677.0 kg ha-1, 327.0 kg ha-1,
130.0 kg ha-1) were recorded from 70x30 cm plant density. As a
result, in terms of oil yield for second crop sesame agriculture, 30 cm
row spacing, and 5 cm intra row spacing are the most suitable plant
densities.
Abstract: The automatic transmission (AT) is one of the most
important components of many automobile transmission systems. The
shift quality has a significant influence on the ride comfort of the
vehicle. During the AT shift process, the joint elements such as the
clutch and bands engage or disengage, linking sets of gears to create a
fixed gear ratio. Since these ratios differ between gears in a fixed gear
ratio transmission, the motion of the vehicle could change suddenly
during the shift process if the joint elements are engaged or disengaged
inappropriately, additionally impacting the entire transmission system
and increasing the temperature of connect elements.The objective was
to establish a system model for an AT powertrain using
Matlab/Simulink. This paper further analyses the effect of varying
hydraulic pressure and the associated impact on shift quality during
both engagment and disengagement of the joint elements, proving that
shift quality improvements could be achieved with appropriate
hydraulic pressure control.
Abstract: In this study, we discussed the effects on the thermal
comfort of super high-rise residences that how effected by the high
thermal capacity structural components. We considered different
building orientations, structures, and insulation methods. We used the
dynamic simulation software THERB (simulation of the thermal
environment of residential buildings). It can estimate the temperature,
humidity, sensible temperature, and heating/cooling load for multiple
buildings. In the past studies, we examined the impact of
air-conditioning loads (hereinafter referred to as AC loads) on the
interior structural parts and the AC-usage patterns of super-high-rise
residences.
Super-high-rise residences have more structural components such
as pillars and beams than do ordinary apartment buildings. The
skeleton is generally made of concrete and steel, which have high
thermal-storage capacities. The thermal-storage capacity of
super-high-rise residences is considered to have a larger impact on the
AC load and thermal comfort than that of ordinary residences.
We show that the AC load of super-high-rise units would be
reduced by installing insulation on the surfaces of interior walls that
are not usually insulated in Japan.
Abstract: Today many developers use the Java components
collected from the Internet as external LIBs to design and
develop their own software. However, some unknown security
bugs may exist in these components, such as SQL injection bug
may comes from the components which have no specific check
for the input string by users. To check these bugs out is very
difficult without source code. So a novel method to check the
bugs in Java bytecode based on points-to dataflow analysis is in
need, which is different to the common analysis techniques base
on the vulnerability pattern check. It can be used as an assistant
tool for security analysis of Java bytecode from unknown
softwares which will be used as extern LIBs.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.
Abstract: The purpose of the present study is the calculation of Gutenber-Richter parameters (a, b) and analyze the mean annual rate of exceedance of earthquake magnitude (Om ) of southern segment of the Sagaing fault and its associate components. The study area is situated about 200 km radius centered at Yangon. Earthquake data file is using from 1975 to 2006 August 31. The bounded Gutenberg- Richter recurrence law for 0 M is 4.0 and max M is 7.5.
Abstract: Effective employee selection is a critical component
of a successful organization. Many important criteria for personnel
selection such as decision-making ability, adaptability, ambition, and
self-organization are naturally vague and imprecise to evaluate. The
rough sets theory (RST) as a new mathematical approach to
vagueness and uncertainty is a very well suited tool to deal with
qualitative data and various decision problems. This paper provides
conceptual, descriptive, and simulation results, concentrating chiefly
on human resources and personnel selection factors. The current
research derives certain decision rules which are able to facilitate
personnel selection and identifies several significant features based
on an empirical study conducted in an IT company in Iran.
Abstract: Nylon 6-clay hybrid/neat nylon 6, sheath/core
bicomponent nanocomposite fibers containing 4 wt% of clay in
sheath section were melt spun at different take-up speeds. Their
orientation and crystalline structure were compared to those of neat
nylon 6 fibers. Birefringence measurements showed that the
orientation development in sheath and core parts of bicomponent
fibers was different. Crystallinity results showed that clay did not act
as a nucleating agent for bicomponent fibers. The neat nylon 6 fiber
had a smooth surface while striped pattern was appeared on the
surface of bicomponent fiber containing clay due to thermal
shrinkage of the core part.
Abstract: The entomopathogenic nematodes Steinernema
feltiaeare are components of many biological pesticides. The
biological pesticides are applicated by means a spraying machines.
The influence of high pressure operating time on viability of
nematodes has been experimentally investigated in order to explain if
static pressure inside of the sprayers installation was able to destroy
nematodes. The value of pressure was 55 MPa and its maximum
operating time was 3 hours. Changes were found in viability of
pressurized samples of nematodes, mixed with water.
Abstract: A clustering is process to identify a homogeneous
groups of object called as cluster. Clustering is one interesting topic
on data mining. A group or class behaves similarly characteristics.
This paper discusses a robust clustering process for data images with
two reduction dimension approaches; i.e. the two dimensional
principal component analysis (2DPCA) and principal component
analysis (PCA). A standard approach to overcome this problem is
dimension reduction, which transforms a high-dimensional data into
a lower-dimensional space with limited loss of information. One of
the most common forms of dimensionality reduction is the principal
components analysis (PCA). The 2DPCA is often called a variant of
principal component (PCA), the image matrices were directly treated
as 2D matrices; they do not need to be transformed into a vector so
that the covariance matrix of image can be constructed directly using
the original image matrices. The decomposed classical covariance
matrix is very sensitive to outlying observations. The objective of
paper is to compare the performance of robust minimizing vector
variance (MVV) in the two dimensional projection PCA (2DPCA)
and the PCA for clustering on an arbitrary data image when outliers
are hiden in the data set. The simulation aspects of robustness and
the illustration of clustering images are discussed in the end of
paper
Abstract: This paper examines the use of mechanical aerator for
oxidation-ditch process. The rotor, which controls the aeration, is the
main component of the aeration process. Therefore, the objective of
this study is to find out the variations in overall oxygen transfer
coefficient (KLa) and aeration efficiency (AE) for different
configurations of aerator by varying the parameters viz. speed of
aerator, depth of immersion, blade tip angles so as to yield higher
values of KLa and AE. Six different configurations of aerator were
developed and fabricated in the laboratory and were tested for abovementioned
parameters. The curved blade rotor (CBR) emerged as a
potential aerator with blade tip angle of 47°.
The mathematical models are developed for predicting the
behaviour of CBR w.r.t kLa and power. In laboratory studies, the
optimum value of KLa and AE were observed to be 10.33 h-1 and
2.269 kg O2/ kWh.