Abstract: The culture of riding heavy motorcycles originates
from advanced countries and mainly comes from Europe, North
America, and Japan. Heavy duty motorcycle riders are different from
people who view motorcycles as a convenient mean of transportation.
They regard riding them as a kind of enjoyment and high-level taste.
The activities of riding heavy duty motorcycles have formes a
distinctive landscape in domestic land in Taiwan. Previous studies
which explored motorcycle culture in Taiwan still focused on the
objects of motorcycle engine displacement under 50 cc.. The study
aims to study the heavy duty motorcycles of engine displacement over
550 cc. and explores where their attractiveness is. For finding the
attractiveness of heavy duty motorcycle, the study chooses Miryoku
Engineering (Preference-Based Design) approach. Two steps are
adopted to proceed the research. First, through arranging the letters
obtained from interviewing experts, EGM (The Evaluation Grid
Method) was applied to find out the structure of attractiveness. The
attractive styles are eye-dazzling, leisure, classic, and racing
competitive styles. Secondarily, Quantification Theory Type I analysis
was adopted as a tool for analyzing the importance of attractiveness.
The relationship between style and attractive parts was also discussed.
The results could contribute to the design and research development of
heavy duty motorcycle industry in Taiwan.
Abstract: The present work represents an investigation of the
hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein
isolate (PuOC PI) by pepsin. To examine the effectiveness and
suitability of pepsin towards PuOC PI the kinetic parameters for
pepsin on PuOC PI were determined and then, the hydrolysis process
was studied using Response Surface Methodology (RSM). The
hydrolysis was carried out at temperature of 30°C and pH 3.00. Time
and initial enzyme/substrate ratio (E/S) at three levels were selected
as the independent parameters. The degree of hydrolysis, DH, was
mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3
mA/mg proteins. Since the proposed second-order polynomial model
showed good fit with the experimental data (R2 = 0.9822), the
obtained mathematical model could be used for monitoring the
hydrolysis of PuOC PI by pepsin, under studied experimental
conditions, varying the time and initial E/S. To achieve the highest
value of DH (39.13 %), the obtained optimum conditions for time
and initial E/S were 30 min and 1.024 mA/mg proteins.
Abstract: Numerical studies have been carried out using a
validated two-dimensional RNG k-epsilon turbulence model for the
design optimization of a thrust vector control system using shock
induced supersonic secondary jet. Parametric analytical studies have
been carried out with various secondary jets at different divergent
locations, jet interaction angles, jet pressures. The results from the
parametric studies of the case on hand reveal that the primary nozzle
with a small divergence angle, downstream injections with a distance
of 2.5 times the primary nozzle throat diameter from the primary
nozzle throat location warrant higher efficiency over a certain range
of jet pressures and jet angles. We observed that the supersonic
secondary jet opposing the core flow with jets interaction angle of
40o to the axis far downstream of the nozzle throat facilitates better
thrust vectoring than the secondary jet with same direction as that of
core flow with various interaction angles. We concluded that fixing
of the supersonic secondary jet nozzle pointing towards the throat
direction with suitable angle at a distance 2 to 4 times of the primary
nozzle throat diameter, as the case may be, from the primary nozzle
throat location could facilitate better thrust vectoring for the
supersonic aerospace vehicles.
Abstract: Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.
Abstract: This paper presents the application of an enhanced
Particle Swarm Optimization (EPSO) combined with Gaussian
Mutation (GM) for solving the Dynamic Economic Dispatch (DED)
problem considering the operating constraints of generators. The
EPSO consists of the standard PSO and a modified heuristic search
approaches. Namely, the ability of the traditional PSO is enhanced
by applying the modified heuristic search approach to prevent the
solutions from violating the constraints. In addition, Gaussian
Mutation is aimed at increasing the diversity of global search, whilst
it also prevents being trapped in suboptimal points during search. To
illustrate its efficiency and effectiveness, the developed EPSO-GM
approach is tested on the 3-unit and 10-unit 24-hour systems
considering valve-point effect. From the experimental results, it can
be concluded that the proposed EPSO-GM provides, the accurate
solution, the efficiency, and the feature of robust computation
compared with other algorithms under consideration.
Abstract: The explosive growth of World Wide Web has posed
a challenging problem in extracting relevant data. Traditional web
crawlers focus only on the surface web while the deep web keeps
expanding behind the scene. Deep web pages are created
dynamically as a result of queries posed to specific web databases.
The structure of the deep web pages makes it impossible for
traditional web crawlers to access deep web contents. This paper,
Deep iCrawl, gives a novel and vision-based approach for extracting
data from the deep web. Deep iCrawl splits the process into two
phases. The first phase includes Query analysis and Query translation
and the second covers vision-based extraction of data from the
dynamically created deep web pages. There are several established
approaches for the extraction of deep web pages but the proposed
method aims at overcoming the inherent limitations of the former.
This paper also aims at comparing the data items and presenting them
in the required order.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: This study is about an application of King Bhumibol
Adulyadej’s “Learn Wisely” (LW) concept in instructional design
and management process at the Faculty of Education, Suan Sunahdha
Rajabhat University. The concept suggests four strategies for true
learning. Related literature and significant LW methods in teaching
and learning are also reviewed and then applied in designing a
pedagogy learning module. The design has been implemented in
three classrooms with a total of 115 sophomore student teachers.
After one consecutive semester of managing and adjusting the
process by instructors and experts using collected data from minutes,
assessment of learning management, satisfaction and learning
achievement of the students, it is found that the effective SSRU
model of LW instructional method comprises of five steps.
Abstract: This paper provides the design steps of a robust Linear
Matrix Inequality (LMI) based iterative multivariable PID controller
whose duty is to drive a sample power system that comprises a
synchronous generator connected to a large network via a step-up
transformer and a transmission line. The generator is equipped with
two control-loops, namely, the speed/power (governor) and voltage
(exciter). Both loops are lumped in one where the error in the
terminal voltage and output active power represent the controller
inputs and the generator-exciter voltage and governor-valve position
represent its outputs. Multivariable PID is considered here because of
its wide use in the industry, simple structure and easy
implementation. It is also preferred in plants of higher order that
cannot be reduced to lower ones. To improve its robustness to
variation in the controlled variables, H∞-norm of the system transfer
function is used. To show the effectiveness of the controller, divers
tests, namely, step/tracking in the controlled variables, and variation
in plant parameters, are applied. A comparative study between the
proposed controller and a robust H∞ LMI-based output feedback is
given by its robustness to disturbance rejection. From the simulation
results, the iterative multivariable PID shows superiority.
Abstract: In this paper we discuss the effect of unbounded particle interaction operator on particle growth and we study how this can address the choice of appropriate time steps of the numerical simulation. We provide also rigorous mathematical proofs showing that large particles become dominating with increasing time while small particles contribute negligibly. Second, we discuss the efficiency of the algorithm by performing numerical simulations tests and by comparing the simulated solutions with some known analytic solutions to the Smoluchowski equation.
Abstract: This paper presents the determination of the proper
quality costs parameters which provide the optimum return. The
system dynamics simulation was applied. The simulation model was
constructed by the real data from a case of the electronic devices
manufacturer in Thailand. The Steepest Descent algorithm was
employed to optimise. The experimental results show that the
company should spend on prevention and appraisal activities for 850
and 10 Baht/day respectively. It provides minimum cumulative total
quality cost, which is 258,000 Baht in twelve months. The effect of
the step size in the stage of improving the variables to the optimum
was also investigated. It can be stated that the smaller step size
provided a better result with more experimental runs. However, the
different yield in this case is not significant in practice. Therefore, the
greater step size is recommended because the region of optima could
be reached more easily and rapidly.
Abstract: The functional response of an infective is the relationship
between an infected individual-s infection rate and the abundance
of the number of susceptibles that one can potentially be infected.
In this paper, we consider defensive attitudes for HIV prevention
(primary prevention) while at the same time emphasizing on offensive
attitudes that reduce infection for those infected (secondary prevention).
We look at how defenses can protect an uninfected individual
in the case where high risk groups such as commercial sex workers
and those who deliberately go out to look for partners. We propose
an infection cycle that begins with a search, then an encounter,
a proposal and contact. The infection cycle illustrates the various
steps an infected individual goes through to successfully infect a
susceptible. For heterogeneous transmission of HIV, there will be no
infection unless there is contact. The ability to avoid an encounter,
detection, proposal and contact constitute defense.
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: In this paper, we present a new learning algorithm for
anomaly based network intrusion detection using improved self
adaptive naïve Bayesian tree (NBTree), which induces a hybrid of
decision tree and naïve Bayesian classifier. The proposed approach
scales up the balance detections for different attack types and keeps
the false positives at acceptable level in intrusion detection. In
complex and dynamic large intrusion detection dataset, the detection
accuracy of naïve Bayesian classifier does not scale up as well as
decision tree. It has been successfully tested in other problem
domains that naïve Bayesian tree improves the classification rates in
large dataset. In naïve Bayesian tree nodes contain and split as
regular decision-trees, but the leaves contain naïve Bayesian
classifiers. The experimental results on KDD99 benchmark network
intrusion detection dataset demonstrate that this new approach scales
up the detection rates for different attack types and reduces false
positives in network intrusion detection.
Abstract: Numerous divergence measures (spectral distance, cepstral
distance, difference of the cepstral coefficients, Kullback-Leibler
divergence, distance given by the General Likelihood Ratio, distance
defined by the Recursive Bayesian Changepoint Detector and the
Mahalanobis measure) are compared in this study. The measures are
used for detection of abrupt spectral changes in synthetic AR signals
via the sliding window algorithm. Two experiments are performed;
the first is focused on detection of single boundary while the second
concentrates on detection of a couple of boundaries. Accuracy of
detection is judged for each method; the measures are compared
according to results of both experiments.
Abstract: Successful intelligence (SI) is the integrated set of the
ability needed to attain success in life, within individual-s sociocultural
context. People are successfully intelligent by recognizing
their strengths and weaknesses. They will find ways to strengthen
their weakness and maintain their strength or even improve it. SI
people can shape, select, and adapt to the environments by using
balance of higher-ordered thinking abilities including; critical,
creative, and applicative. Aims: The purposes of this study were to;
1) develop curriculum that promotes SI for nursing students, and 2)
study the effectiveness of the curriculum development. Method:
Research and Development was a method used for this study. The
design was divided into two phases; 1) the curriculum development
which composed of three steps (needs assessment, curriculum
development and curriculum field trail), and 2) the curriculum
implementation. In this phase, a pre-experimental research design
(one group pretest-posttest design) was conducted. The sample
composed of 49 sophomore nursing students of Boromarajonani
College of Nursing, Surin, Thailand who enrolled in Nursing care of
Health problem course I in 2011 academic year. Data were carefully
collected using 4 instruments; 1) Modified essay questions test
(MEQ) 2) Nursing Care Plan evaluation form 3) Group processing
observation form (α = 0.74) and 4) Satisfied evaluation form of
learning (α = 0.82). Data were analyzed using descriptive statistics
and content analysis. Results: The results revealed that the sample
had post-test average score of SI higher than pre-test average score
(mean difference was 5.03, S.D. = 2.84). Fifty seven percentages of
the sample passed the MEQ posttest at the criteria of 60 percentages.
Students demonstrated the strategies of how to develop nursing care
plan. Overall, students- satisfaction on teaching performance was at
high level (mean = 4.35, S.D. = 0.46). Conclusion: This curriculum
can promote the attribute of characteristic of SI person and was
highly required to be continued.
Abstract: Optimal selection of electrical insulations in electrical
machinery insures reliability during operation. From the insulation
studies of view for electrical machines, stator is the most important
part. This fact reveals the requirement for inspection of the electrical
machine insulation along with the electro-thermal stresses. In the
first step of the study, a part of the whole structure of machine in
which covers the general characteristics of the machine is chosen,
then based on the electromagnetic analysis (finite element method),
the machine operation is simulated. In the simulation results, the
temperature distribution of the total structure is presented
simultaneously by using electro-thermal analysis. The results of
electro-thermal analysis can be used for designing an optimal cooling
system. In order to design, review and comparing the cooling
systems, four wiring structures in the slots of Stator are presented.
The structures are compared to each other in terms of electrical,
thermal distribution and remaining life of insulation by using Finite
Element analysis. According to the steps of the study, an optimization
algorithm has been presented for selection of appropriate structure.
Abstract: Environmental impact assessment (EIA) is a procedure tool of environmental management for identifying, predicting, evaluating and mitigating the adverse effects of development proposals. EIA reports usually analyze how the amounts or concentrations of pollutants obey the relevant standards. Actually, many analytical tools can deepen the analysis of environmental impacts in EIA reports, such as life cycle assessment (LCA) and environmental risk assessment (ERA). Life cycle impact assessment (LCIA) is one of steps in LCA to introduce the causal relationships among environmental hazards and damage. Incorporating the LCIA concept into ERA as an integrated tool for EIA can extend the focus of the regulatory compliance of environmental impacts to determine of the significance of environmental impacts. Sometimes, when using integrated tools, it is necessary to consider fuzzy situations due to insufficient information; therefore, ERA should be generalized to fuzzy risk assessment (FRA). Finally, the use of the proposed methodology is demonstrated through the study case of the expansion plan of the world-s largest plastics processing factory.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.