Abstract: The present work describes the implementation of the
Enhanced Collaborative Optimization (ECO) multilevel architecture
with a gradient-based optimization algorithm with the aim of
performing a multidisciplinary design optimization of a generic
unmanned aerial vehicle with morphing technologies. The concepts
of weighting coefficient and dynamic compatibility parameter are
presented for the ECO architecture. A routine that calculates the
aircraft performance for the user defined mission profile and vehicle’s
performance requirements has been implemented using low fidelity
models for the aerodynamics, stability, propulsion, weight, balance
and flight performance. A benchmarking case study for evaluating
the advantage of using a variable span wing within the optimization
methodology developed is presented.
Abstract: This paper presents circuit models to analyze the
conducted susceptibility of multiconductor shielded cables in
frequency domains using Branin’s method, which is referred to as the
method of characteristics. These models, which can be used directly
in the time and frequency domains, take into account the presence of
both the transfer impedance and admittance. The conducted
susceptibility is studied by using an injection current on the cable
shield as the source. Two examples are studied; a coaxial shielded
cable and shielded cables with two parallel wires (i.e., twinax cables).
This shield has an asymmetry (one slot on the side). Results obtained
by these models are in good agreement with those obtained by other
methods.
Abstract: The Markov decision process (MDP) based
methodology is implemented in order to establish the optimal
schedule which minimizes the cost. Formulation of MDP problem
is presented using the information about the current state of pipe,
improvement cost, failure cost and pipe deterioration model. The
objective function and detailed algorithm of dynamic programming
(DP) are modified due to the difficulty of implementing the
conventional DP approaches. The optimal schedule derived from
suggested model is compared to several policies via Monte
Carlo simulation. Validity of the solution and improvement in
computational time are proved.
Abstract: This study introduces two types of self-oscillating
circuits that are frequently found in power electronics applications.
Special effort is made to relate the circuits to the analogous mechanical
systems of some important scientific inventions: Galileo’s pendulum
clock and Coulomb’s friction model. A little touch of related history
and philosophy of science will hopefully encourage curiosity, advance
the understanding of self-oscillating systems and satisfy the aspiration
of some students for scientific literacy. Finally, the two self-oscillating
circuits are applied to design a simple class-D audio amplifier.
Abstract: The article deals with modelling of the fire
pragmatism in the area of military management and its experimental
verification. Potential approaches are based on the synergy of
mathematical and theoretical ideas, operational and tactical
requirements and the military decision-making process. This issue
has taken on importance in recent times, particularly with the
increasing trend of digitized battlefield, the development of C4ISR
systems and intention to streamline the command and control process
at the lowest levels of command. From fundamental and
philosophical point of view, these new approaches seek to
significantly upgrade and enhance the decision-making process of the
tactical commanders.
Abstract: We are facing serious problems related to long-term
depopulation and an aging society with a falling birth rate in Japan. In
this situation, we are suffering from a shortfall in human resources as
well as a shortage of workforce in rural regions. In addition, we are
struggling with a protracted economic slump and excess concentration
of population in the Tokyo Metropolitan area. It is an urgent national
issue to consider how to live in this country and what kind of structure
of society and administration policy is needed. It is necessary to clarify
people’s desire for their way of living and social assistance to be
provided. The aim of this study is to clarify the characteristics of
regional issues and the degree of their seriousness in local
municipalities of Japan. We conducted a questionnaire survey about
regional agenda in all local municipalities in Japan. We obtained
responses concerning the degree of seriousness of regional issues and
degree of importance of policies. Based on the data gathered from the
survey, it is apparent that many local municipalities are facing an
aging population and declining population. We constructed a model to
analyze factors for declining population. Using the model, it was
clarified that a population’s age structure, job opportunities and
income level affect the decline of population. In addition, we showed
the way of the evaluation of state of local municipality.
Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: Cemented carbide balls are usually implemented in
industry under the environment of high speed, high temperature,
corrosiveness and strong collisions. However, its application is limited
due to high fabrication cost, processing efficiency and quality. A novel
eccentric lapping method with two rotatable lapping plates was
proposed in this paper. A mathematical model was constructed to
analyze the influence of each design parameter on this lapping method.
To validate this new lapping method, an orthogonal experiment was
conducted with cemented carbide balls (YG6). The simulation model
was verified and the optimal lapping parameters were derived. The
results show that the surface roundness of the balls reaches to 0.65um
from 2um in 1 hour using this lapping method. So, using this novel
lapping method, it can effectively improve the machining precision
and efficiency of cemented carbide balls.
Abstract: New physical insights into the nonlinear Lorenz
equations related to flow resistance is discussed in this work. The
chaotic dynamics related to Lorenz equations has been studied in
many papers, which is due to the sensitivity of Lorenz equations to
initial conditions and parameter uncertainties. However, the physical
implication arising from Lorenz equations about convectional motion
attracts little attention in the relevant literature. Therefore, as a first
step to understand the related fluid mechanics of convectional motion,
this paper derives the Lorenz equations again with different forced
conditions in the model. Simulation work of the modified Lorenz
equations without the viscosity or buoyancy force is discussed. The
time-domain simulation results may imply that the states of the
Lorenz equations are related to certain flow speed and flow resistance.
The flow speed of the underlying fluid system increases as the flow
resistance reduces. This observation would be helpful to analyze the
coupling effects of different fluid parameters in a convectional model
in future work.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.
Abstract: The Malaysian government had consistently revived
its campaign for “Buy Malaysian Goods” from time to time. The
purpose of the campaign is to remind consumers to be ethnocentric
and patriotic when purchasing product and services. This is necessary
to ensure high demand for local products and services compared to
foreign products. However, the decline of domestic investment in
2012 has triggered concern for the Malaysian economy. Hence, this
study attempts to determine the drivers of actual purchasing behavior,
intention to purchase domestic products and ethnocentrism. The
study employs the cross-sectional primary data, self-administered on
household, selected using stratified random sampling in four
Malaysian regions. A nine factor driver of actual domestic purchasing
behavior (culture openness, conservatism, collectivism, patriotism,
control belief, interest in foreign travel, attitude, ethnocentrism and
intention) were measured utilizing 60 items, using 7-point Likertscale.
From 1000 questionnaires distributed, a sample of 486 were
returned representing 48.6 percent response rate. From the fit
generated structural model (SEM analysis), it was found that the
drivers of actual purchase behavior are collectivism, cultural
openness and patriotism; the drivers of intention to purchase
domestic product are attitude, control belief, collectivism and
conservatism; and drivers of ethnocentrism are cultural openness,
control belief, foreign travel and patriotism. It also shows that
Malaysian consumers scored high in ethnocentrism and patriotism.
The findings are discussed in the perspective of its implication to
Malaysian National Agenda.
Abstract: This work deals with parameter identification of
permanent magnet motors, a class of ac motor which is particularly
important in industrial automation due to characteristics like
applications high performance, are very attractive for applications
with limited space and reducing the need to eliminate because they
have reduced size and volume and can operate in a wide speed range,
without independent ventilation. By using experimental data and
genetic algorithm we have been able to extract values for both the
motor inductance and the electromechanical coupling constant, which
are then compared to measured and/or expected values.
Abstract: The development of allometric models is crucial to
accurate forest biomass/carbon stock assessment. The aim of this
study was to develop a set of biomass prediction models that will
enable the determination of total tree aboveground biomass for
savannah woodland area in Niger State, Nigeria. Based on the data
collected through biometric measurements of 1816 trees and
destructive sampling of 36 trees, five species specific and one site
specific models were developed. The sample size was distributed
equally between the five most dominant species in the study site
(Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa,
Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the
equations were developed for five individual species. Secondly these
five species were mixed and were used to develop an allometric
equation of mixed species. Overall, there was a strong positive
relationship between total tree biomass and the stem diameter. The
coefficient of determination (R2 values) ranging from 0.93 to 0.99 P
< 0.001 were realised for the models; with considerable low standard
error of the estimates (SEE) which confirms that the total tree above
ground biomass has a significant relationship with the dbh. F-test
values for the biomass prediction models were also significant at p
Abstract: Robotic surgery is used to enhance minimally invasive
surgical procedure. It provides greater degree of freedom for surgical
tools but lacks of haptic feedback system to provide sense of touch to
the surgeon. Surgical robots work on master-slave operation, where
user is a master and robotic arms are the slaves. Current, surgical
robots provide precise control of the surgical tools, but heavily rely
on visual feedback, which sometimes cause damage to the inner
organs. The goal of this research was to design and develop a realtime
Simulink based robotic system to study force feedback
mechanism during instrument-object interaction. Setup includes three
VelmexXSlide assembly (XYZ Stage) for three dimensional
movement, an end effector assembly for forceps, electronic circuit for
four strain gages, two Novint Falcon 3D gaming controllers,
microcontroller board with linear actuators, MATLAB and Simulink
toolboxes. Strain gages were calibrated using Imada Digital Force
Gauge device and tested with a hard-core wire to measure
instrument-object interaction in the range of 0-35N. Designed
Simulink model successfully acquires 3D coordinates from two
Novint Falcon controllers and transfer coordinates to the XYZ stage
and forceps. Simulink model also reads strain gages signal through
10-bit analog to digital converter resolution of a microcontroller
assembly in real time, converts voltage into force and feedback the
output signals to the Novint Falcon controller for force feedback
mechanism. Experimental setup allows user to change forward
kinematics algorithms to achieve the best-desired movement of the
XYZ stage and forceps. This project combines haptic technology
with surgical robot to provide sense of touch to the user controlling
forceps through machine-computer interface.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: Meeting the growth in demand for digital services
such as social media, telecommunications, and business and cloud
services requires large scale data centres, which has led to an increase
in their end use energy demand. Generally, over 30% of data centre
power is consumed by the necessary cooling overhead. Thus energy
can be reduced by improving the cooling efficiency. Air and liquid
can both be used as cooling media for the data centre. Traditional
data centre cooling systems use air, however liquid is recognised as a
promising method that can handle the more densely packed data
centres. Liquid cooling can be classified into three methods; rack heat
exchanger, on-chip heat exchanger and full immersion of the
microelectronics. This study quantifies the improvements of heat
transfer specifically for the case of immersed microelectronics by
varying the CPU and heat sink location. Immersion of the server is
achieved by filling the gap between the microelectronics and a water
jacket with a dielectric liquid which convects the heat from the CPU
to the water jacket on the opposite side. Heat transfer is governed by
two physical mechanisms, which is natural convection for the fixed
enclosure filled with dielectric liquid and forced convection for the
water that is pumped through the water jacket. The model in this
study is validated with published numerical and experimental work
and shows good agreement with previous work. The results show that
the heat transfer performance and Nusselt number (Nu) is improved
by 89% by placing the CPU and heat sink on the bottom of the
microelectronics enclosure.
Abstract: Previous studies on financial distress prediction choose
the conventional failing and non-failing dichotomy; however, the
distressed extent differs substantially among different financial
distress events. To solve the problem, “non-distressed”, “slightlydistressed”
and “reorganization and bankruptcy” are used in our article
to approximate the continuum of corporate financial health. This paper
explains different financial distress events using the two-stage method.
First, this investigation adopts firm-specific financial ratios, corporate
governance and market factors to measure the probability of various
financial distress events based on multinomial logit models.
Specifically, the bootstrapping simulation is performed to examine the
difference of estimated misclassifying cost (EMC). Second, this work
further applies macroeconomic factors to establish the credit cycle
index and determines the distressed cut-off indicator of the two-stage
models using such index. Two different models, one-stage and
two-stage prediction models are developed to forecast financial
distress, and the results acquired from different models are compared
with each other, and with the collected data. The findings show that the
one-stage model has the lower misclassification error rate than the
two-stage model. The one-stage model is more accurate than the
two-stage model.
Abstract: In this paper, effects of using Alumina-water
nanofluid on the rate of heat transfer have been investigated
numerically. Physical model is a square enclosure with insulated top
and bottom horizontal walls, while the vertical walls are kept at
different constant temperatures. Two appropriate models are used to
evaluate the viscosity and thermal conductivity of nanofluid. The
governing stream-vorticity equations are solved using a second order
central finite difference scheme, coupled to the conservation of mass
and energy. The study has been carried out for the Richardson
number 0.1 to 10 and the solid volume fraction 0 to 0.04. Results are
presented by isotherms lines, average Nusselt number and normalized
Nusselt number in different range of φ and Ri for forced, combined
and natural convection dominated regime. It is found that higher heat
transfer rate is predicted when the effects of nanoparticle is taken into
account.
Abstract: Numerical studies were conducted using Lattice
Boltzmann Method (LBM) to study the natural convection in a square
cavity in the presence of roughness. An algorithm based on a single
relaxation time Bhatnagar-Gross-Krook (BGK) model of Lattice
Boltzmann Method (LBM) was developed. Roughness was
introduced on both the hot and cold walls in the form of sinusoidal
roughness elements. The study was conducted for a Newtonian fluid
of Prandtl number (Pr) 1.0. The range of Ra number was explored
from 10^3 to 10^6 in a laminar region. Thermal and hydrodynamic
behavior of fluid was analyzed using a differentially heated square
cavity with roughness elements present on both the hot and cold wall.
Neumann boundary conditions were introduced on horizontal walls
with vertical walls as isothermal. The roughness elements were at the
same boundary condition as corresponding walls. Computational
algorithm was validated against previous benchmark studies
performed with different numerical methods, and a good agreement
was found to exist. Results indicate that the maximum reduction in
the average heat transfer was 16.66 percent at Ra number 10^5.
Abstract: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.