Abstract: A climate dependent model is proposed to simulate
the population of Aedes aegypti mosquito. In developing the model,
average temperature of Shah Alam, Malaysia was used to determine
the development rate of each stage of the life cycle of mosquito.
Rainfall dependent function was proposed to simulate the hatching
rate of the eggs under several assumptions. The proposed transition
matrix was obtained and used to simulate the population of eggs,
larvae, pupae and adults mosquito. It was found that the peak of
mosquito abundance comes during a relatively dry period following a
heavy rainfall. In addition, lag time between the peaks of mosquito
abundance and dengue fever cases in Shah Alam was estimated.
Abstract: In this paper the complete rotor system including
elastic shaft with distributed mass, allowing for the effects of oil film
in bearings. Also, flexibility of foundation is modeled. As a whole
this article is a relatively complete research in modeling and
vibration analysis of rotor considering gyroscopic effect, damping,
dependency of stiffness and damping coefficients on frequency and
solving the vibration equations including these parameters. On the
basis of finite element method and utilizing four element types
including element of shaft, disk, bearing and foundation and using
MATLAB, a computer program is written. So the responses in
several cases and considering different effects are obtained. Then the
results are compared with each other, with exact solutions and results
of other papers.
Abstract: In this investigation, anatase TiO2 thin films were
grown by radio frequency magnetron sputtering on glass substrates at
a high sputtering pressure and room temperature. The anatase films
were then annealed at 300-600 °C in air for a period of 1 hour. To
examine the structure and morphology of the films, X-ray diffraction
(XRD) and atomic force microscopy (AFM) methods were used
respectively. From X-ray diffraction patterns of the TiO2 films, it was
found that the as-deposited film showed some differences compared
with the annealed films and the intensities of the peaks of the
crystalline phase increased with the increase of annealing
temperature. From AFM images, the distinct variations in the
morphology of the thin films were also observed. The optical
constants were characterized using the transmission spectra of the
films obtained by UV-VIS-IR spectrophotometer. Besides, optical
thickness of the film deposited at room temperature was calculated
and cross-checked by taking a cross-sectional image through SEM.
The optical band gaps were evaluated through Tauc model. It was
observed that TiO2 films produced at room temperatures exhibited
high visible transmittance and transmittance decreased slightly with
the increase of annealing temperatures. The films were found to be
crystalline having anatase phase. The refractive index of the films
was found from 2.31-2.35 in the visible range. The extinction
coefficient was nearly zero in the visible range and was found to
increase with annealing temperature. The allowed indirect optical
band gap of the films was estimated to be in the range from 3.39 to
3.42 eV which showed a small variation. The allowed direct band
gap was found to increase from 3.67 to 3.72 eV. The porosity was
also found to decrease at a higher annealing temperature making the
film compact and dense.
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: Because of the global warming and the rising sea level, residents living in southwestern coastland, Taiwan are faced with the submerged land and may move to higher elevation area. It is desirable to discuss the key consideration factor for selecting the migration location under five dimensions of ಯ security”, “health”, “convenience”, “comfort” and “socio-economic” based on the document reviews. This paper uses the Structural Equation Modeling (SEM) and the questionnaire survey. The analysis results show that the convenience is the most key factor for residents in Taiwan.
Abstract: This study experimentally and numerically investigates
motor cooling performance. The motor consists of a centrifugal fan,
two axial fans, a shaft, a stator, a rotor and a heat exchanger with 637
cooling tubes. The pressure rise-flow rate (P-Q) performance curves of
the cooling fans at 1800 rpm are tested using a test apparatus
complying with the Chinese National Standard (CNS) 2726.
Compared with the experimental measurements, the numerical
analysis results show that the P-Q performance curves of the axial fan
and centrifugal fan can be estimated within about 2% and 6%,
respectively. By using the simplified model, setting up the heat
exchanger and stator as porous media, the flow field in the motor is
calculated. By using the results of the flow field near the rotor and
stator, and subjecting the heat generation rate as a boundary condition,
the temperature distributions of the stator and rotor are also calculated.
The simulation results show that the calculated temperature of the
stator winding near the axial fans is lower by about 5% than the
measured value, and the calculated temperature of the stator core
located at the center of the stator is about 1% higher than the measured
value. Besides, discussion is made to improve the motor cooling
performance.
Abstract: In this study the mixed mode fracture mechanics
parameters were investigated for high tensile steel butt welded joint
based on modified Arcan test and finite element analysis was used to
evaluate the effect of crack length on fracture criterion. The nondimensional
stress intensity factors, strain energy release rates and Jintegral
energy on crack tip were obtained for various in-plane
loading combinations on Arcan specimen starting from pure mode-I
to pure mode-II loading conditions. The specimen and apparatus were
modeled by finite element method and analyzed under various
loading angles (between 0 to 90 degrees with 15 degree interval) to
simulate the pure mode-I, II and mixed mode fracture. Since the
analytical results are independent from elasticity modules for
isotropic materials, therefore the results in elastic fields can be used
for Arcan specimens. The main objective of this study was to
evaluate the geometric calibration factors for modified Arcan test
specimen in order to obtain fracture toughness under mixed mode
loading conditions.
Abstract: In this paper, in order to categorize ORL database face
pictures, principle Component Analysis (PCA) and Kernel Principal
Component Analysis (KPCA) methods by using Elman neural
network and Support Vector Machine (SVM) categorization methods
are used. Elman network as a recurrent neural network is proposed
for modeling storage systems and also it is used for reviewing the
effect of using PCA numbers on system categorization precision rate
and database pictures categorization time. Categorization stages are
conducted with various components numbers and the obtained results
of both Elman neural network categorization and support vector
machine are compared. In optimum manner 97.41% recognition
accuracy is obtained.
Abstract: The paper deals with the most important changes that have occurred in business because of social media and its impact on organisations and leadership in recent years. It seeks to synthesize existing research, theories and concepts, in order to understand "social destinations", and to provide a bridge from past research to future success. Becoming a "social destination" is a strategic and tactical leadership and management issue and the paper will present the importance of destination leadership in choosing the way towards a social destination and some organisational models. It also presents some social media tools that can be used in transforming a destination into a social one. Adapting organisations to the twentyfirst century means adopting social media as a way of life and a way of business.
Abstract: This paper discusses the design characteristics management accounting systems should have to be useful for strategic planning and control and provides brief introductions to strategic variance analysis, profit-linked performance measurement models and balanced scorecard. It shows two multi-period, multiproduct models are specified, can be related to Porter's strategy framework and cost and revenue drivers, and can be used to support strategic planning, control and cost management.
Abstract: Warranty is a powerful marketing tool for the
manufacturer and a good protection for both the manufacturer and the
customer. However, warranty always involves additional costs to the
manufacturer, which depend on product reliability characteristics and
warranty parameters. This paper presents an approach to optimisation
of warranty parameters for known product failure distribution to
reduce the warranty costs to the manufacturer while retaining the
promotional function of the warranty. Combination free replacement
and pro-rata warranty policy is chosen as a model and the length of
free replacement period and pro-rata policy period are varied, as well
as the coefficients that define the pro-rata cost function. Multiparametric
warranty optimisation is done by using genetic algorithm.
Obtained results are guideline for the manufacturer to choose the
warranty policy that minimises the costs and maximises the profit.
Abstract: The paper considers the effect of feed plate location
on the interactions in a seven plate binary distillation column. The
mathematical model of the distillation column is deduced based on
the equations of mass and energy balances for each stage, detailed
model for both reboiler and condenser, and heat transfer equations.
The Dynamic Relative Magnitude Criterion, DRMC is used to assess
the interactions in different feed plate locations for a seven plate
(Benzene-Toluene) binary distillation column ( the feed plate is
originally at stage 4). The results show that whenever we go far from
the optimum feed plate position, the level of interaction augments.
Abstract: Automatic control of the robotic manipulator involves
study of kinematics and dynamics as a major issue. This paper
involves the forward and inverse kinematics of 2-DOF robotic
manipulator with revolute joints. In this study the Denavit-
Hartenberg (D-H) model is used to model robot links and joints. Also
forward and inverse kinematics solution has been achieved using
Artificial Neural Networks for 2-DOF robotic manipulator. It shows
that by using artificial neural network the solution we get is faster,
acceptable and has zero error.
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.
Abstract: Data Envelopment Analysis (DEA) is a methodology
that computes efficiency values for decision making units (DMU) in a
given period by comparing the outputs with the inputs. In many cases,
there are some time lag between the consumption of inputs and the
production of outputs. For a long-term research project, it is hard to
avoid the production lead time phenomenon. This time lag effect
should be considered in evaluating the performance of organizations.
This paper suggests a model to calculate efficiency values for the
performance evaluation problem with time lag. In the experimental
part, the proposed methods are compared with the CCR and an
existing time lag model using the data set of the 21st century frontier
R&D program which is a long-term national R&D program of Korea.
Abstract: Different problems may causes distortion of the rotor,
and hence vibration, which is the most severe damage of the turbine
rotors. In many years different techniques have been developed for
the straightening of bent rotors. The method for straightening can be
selected according to initial information from preliminary inspections
and tests such as nondestructive tests, chemical analysis, run out tests
and also a knowledge of the shaft material. This article covers the
various causes of excessive bends and then some applicable common
straightening methods are reviewed. Finally, hot spotting is opted for
a particular bent rotor. A 325 MW steam turbine rotor is modeled and
finite element analyses are arranged to investigate this straightening
process. Results of experimental data show that performing the exact
hot spot straightening process reduced the bending of the rotor
significantly.
Abstract: This paper presents a Particle Swarm Optimization
(PSO) method for determining the optimal parameters of a first-order
controller for TCP/AQM system. The model TCP/AQM is described
by a second-order system with time delay. First, the analytical
approach, based on the D-decomposition method and Lemma of
Kharitonov, is used to determine the stabilizing regions of a firstorder
controller. Second, the optimal parameters of the controller are
obtained by the PSO algorithm. Finally, the proposed method is
implemented in the Network Simulator NS-2 and compared with the
PI controller.
Abstract: A complex valued neural network is a neural network
which consists of complex valued input and/or weights and/or thresholds
and/or activation functions. Complex-valued neural networks
have been widening the scope of applications not only in electronics
and informatics, but also in social systems. One of the most important
applications of the complex valued neural network is in signal
processing. In Neural networks, generalized mean neuron model
(GMN) is often discussed and studied. The GMN includes a new
aggregation function based on the concept of generalized mean of all
the inputs to the neuron. This paper aims to present exhaustive results
of using Generalized Mean Neuron model in a complex-valued neural
network model that uses the back-propagation algorithm (called
-Complex-BP-) for learning. Our experiments results demonstrate the
effectiveness of a Generalized Mean Neuron Model in a complex
plane for signal processing over a real valued neural network. We
have studied and stated various observations like effect of learning
rates, ranges of the initial weights randomly selected, error functions
used and number of iterations for the convergence of error required on
a Generalized Mean neural network model. Some inherent properties
of this complex back propagation algorithm are also studied and
discussed.