Abstract: In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.
Abstract: Automotive designers have been trying to use dimples to reduce drag in vehicles. In this work, a car model has been applied with dimple surface with a parameter called dimple ratio DR, the ratio between the depths of the half dimple over the print diameter of the dimple, has been introduced and numerically simulated via k-ε turbulence model to study the aerodynamics performance with the increasing depth of the dimples The Ahmed body car model with 25 degree slant angle is simulated with the DR of 0.05, 0.2, 0.3 0.4 and 0.5 at Reynolds number of 176387 based on the frontal area of the car model. The geometry of dimple changes the kinematics and dynamics of flow. Complex interaction between the turbulent fluctuating flow and the mean flow escalates the turbulence quantities. The maximum level of turbulent kinetic energy occurs at DR = 0.4. It can be concluded that the dimples have generated extra turbulence energy at the surface and as a result, the application of dimples manages to reduce the drag coefficient of the car model compared to the model with smooth surface.
Abstract: Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.
Abstract: This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.
Abstract: Fermentation is well known as an essential process to
develop chocolate flavor in dried cocoa beans. Besides developing
the precursor of cocoa flavor, it also induces the color changes in the
beans. The fermentation process is influenced by various factors such
as planting material, preconditioning of cocoa pod and fermentation
technique. Therefore, this study was conducted to evaluate color of
Malaysian cocoa beans and how the duration of pods storage and
fermentation technique using shallow box will effect on its color
characteristics. There are two factors being studied i.e. duration of
cocoa pod storage (0, 2, 4 and 6 days) and duration of cocoa
fermentation (0, 1, 2, 3, 4 and 5 days). The experiment is arranged in
4 x 6 factorial designs with 24 treatments and arrangement is in a
Completely Randomised Design (CRD). The produced beans are
inspected for color changes under artificial light during cut test and
divided into four groups of color namely fully brown, purple brown,
fully purple and slaty. Cut tests indicated that cocoa beans which are
directly dried without undergone fermentation has the highest slaty
percentage. However, application of pods storage before fermentation
process is found to decrease the slaty percentage. In contrast, the
percentages of fully brown beans start to dominate after two days of
fermentation, especially from four and six days of pods storage batch.
Whereas, almost all batches of cocoa beans have a percentage of fully
purple less than 20%. Interestingly, the percentage of purple brown
beans are scattered in the entire beans batch regardless any specific
trend. Meanwhile, statistical analysis using General Linear Model
showed that the pods storage has a significant effect on the color
characteristic of the Malaysian dried beans compared to fermentation
duration.
Abstract: The Com-Poisson (CMP) model is one of the most
popular discrete generalized linear models (GLMS) that handles
both equi-, over- and under-dispersed data. In longitudinal context,
an integer-valued autoregressive (INAR(1)) process that incorporates
covariate specification has been developed to model longitudinal
CMP counts. However, the joint likelihood CMP function is
difficult to specify and thus restricts the likelihood-based estimating
methodology. The joint generalized quasi-likelihood approach
(GQL-I) was instead considered but is rather computationally
intensive and may not even estimate the regression effects due
to a complex and frequently ill-conditioned covariance structure.
This paper proposes a new GQL approach for estimating the
regression parameters (GQL-III) that is based on a single score vector
representation. The performance of GQL-III is compared with GQL-I
and separate marginal GQLs (GQL-II) through some simulation
experiments and is proved to yield equally efficient estimates as
GQL-I and is far more computationally stable.
Abstract: This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.
Abstract: An analytical 4-DOF nonlinear model of a de Laval
rotor-stator system based on Energy Principles has been used
theoretically and experimentally to investigate fault symptoms in a
rotating system. The faults, namely rotor-stator-rub, crack and
unbalance are modeled as excitations on the rotor shaft. Mayes
steering function is used to simulate the breathing behaviour of the
crack. The fault analysis technique is based on waveform signal,
orbits and Fast Fourier Transform (FFT) derived from simulated and
real measured signals. Simulated and experimental results manifest
considerable mutual resemblance of elliptic-shaped orbits and FFT
for a same range of test data.
Abstract: This paper proposes a linear model for optimizing
domestic energy consumption in Romania. The particularity of the
model is that it is putting in competition both tangible technologies
and thermal insulation projects with different financing modes.
The model is optimizing the energy system by minimizing the
global discounted cost in household sector, by integrating residential
lighting, space heating, hot water, combined space heating – hot
water, as well as space cooling, in a monolithic model. Another
demand sector included is the passenger transport.
This paper focuses on space heating part, analyzing technical and
economic issues related to investment decisions to envelope and
insulate buildings, in order to minimize energy consumption.
Abstract: The paper develops a Non-Linear Model Predictive
Control (NMPC) of water quality in Drinking Water Distribution
Systems (DWDS) based on the advanced non-linear quality dynamics
model including disinfections by-products (DBPs). A special attention
is paid to the analysis of an impact of the flow trajectories prescribed
by an upper control level of the recently developed two-time scale
architecture of an integrated quality and quantity control in DWDS.
The new quality controller is to operate within this architecture in the
fast time scale as the lower level quality controller. The controller
performance is validated by a comprehensive simulation study based
on an example case study DWDS.
Abstract: In statistics parameter theory, usually the
parameter estimations have two kinds, one is the least-square
estimation (LSE), and the other is the best linear unbiased
estimation (BLUE). Due to the determining theorem of
minimum variance unbiased estimator (MVUE), the parameter
estimation of BLUE in linear model is most ideal. But since
the calculations are complicated or the covariance is not
given, people are hardly to get the solution. Therefore, people
prefer to use LSE rather than BLUE. And this substitution
will take some losses. To quantize the losses, many scholars
have presented many kinds of different relative efficiencies in
different views. For the linear weighted regression model, this
paper discusses the relative efficiencies of LSE of β to BLUE
of β. It also defines two new relative efficiencies and gives
their lower bounds.
Abstract: Polymer Electrolyte Membrane Fuel Cell (PEMFC) is
such a time-vary nonlinear dynamic system. The traditional linear
modeling approach is hard to estimate structure correctly of PEMFC
system. From this reason, this paper presents a nonlinear modeling of
the PEMFC using Neural Network Auto-regressive model with
eXogenous inputs (NNARX) approach. The multilayer perception
(MLP) network is applied to evaluate the structure of the NNARX
model of PEMFC. The validity and accuracy of NNARX model are
tested by one step ahead relating output voltage to input current from
measured experimental of PEMFC. The results show that the obtained
nonlinear NNARX model can efficiently approximate the dynamic
mode of the PEMFC and model output and system measured output
consistently.
Abstract: The main objective of this paper is to provide a new
methodology for road safety assessment in Oman through the
development of suitable accident prediction models. GLM technique
with Poisson or NBR using SAS package was carried out to develop
these models. The paper utilized the accidents data of 31 un-signalized
T-intersections during three years. Five goodness-of-fit
measures were used to assess the overall quality of the developed
models. Two types of models were developed separately; the flow-based
models including only traffic exposure functions, and the full
models containing both exposure functions and other significant
geometry and traffic variables.
The results show that, traffic exposure functions produced much
better fit to the accident data. The most effective geometric variables
were major-road mean speed, minor-road 85th percentile speed,
major-road lane width, distance to the nearest junction, and right-turn
curb radius.
The developed models can be used for intersection treatment or
upgrading and specify the appropriate design parameters of T-intersections.
Finally, the models presented in this thesis reflect the intersection
conditions in Oman and could represent the typical conditions in
several countries in the middle east area, especially gulf countries.
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: Unmanned aircraft systems (UAS) are playing
increasingly prominent roles in defense programs and defense
strategies around the world. Technology advancements have
enabled the development of it to do many excellent jobs as
reconnaissance, surveillance, battle fighters, and communications
relays. Simulating a small unmanned aerial vehicle (SUAV)
dynamics and analyzing its behavior at the preflight stage is too
important and more efficient. The first step in the UAV design is
the mathematical modeling of the nonlinear equations of motion. .
In this paper, a survey with a standard method to obtain the full
non-linear equations of motion is utilized, and then the
linearization of the equations according to a steady state flight
condition (trimming) is derived. This modeling technique is
applied to an Ultrastick-25e fixed wing UAV to obtain the valued
linear longitudinal and lateral models. At the end the model is
checked by matching between the behavior of the states of the nonlinear
UAV and the resulted linear model with doublet at the
control surfaces.
Abstract: For a bluff body, dimples behave like roughness
elements in stimulating a turbulent boundary layer, leading to delayed
flow separation, a smaller wake and lower form drag. This is very
different in principle from the application of dimples to streamlined
body, where any reduction in drag would be predominantly due to a
reduction in skin friction. In the present work, a car model with
different dimple geometry is simulated using k-ε turbulence modeling
to determine its effect to the aerodynamics performance. Overall, the
results show that the application of dimples manages to reduce the
drag coefficient of the car model.
Abstract: The implementation of e-assessment as tool to support
the process of teaching and learning in university has become a
popular technological means in universities. E-Assessment provides
many advantages to the users especially the flexibility in teaching and
learning. The e-assessment system has the capability to improve its
quality of delivering education. However, there still exists a
drawback in terms of security which limits the user acceptance of the
online learning system. Even though there are studies providing
solutions for identified security threats in e-learning usage, there is no
particular model which addresses the factors that influences the
acceptance of e-assessment system by lecturers from security
perspective. The aim of this study is to explore security aspects of eassessment
in regard to the acceptance of the technology. As a result
a conceptual model of secure acceptance of e-assessment is proposed.
Both human and security factors are considered in formulation of this
conceptual model. In order to increase understanding of critical issues
related to the subject of this study, interpretive approach involving
convergent mixed method research method is proposed to be used to
execute the research. This study will be useful in providing more
insightful understanding regarding the factors that influence the user
acceptance of e-assessment system from security perspective.
Abstract: The wear measuring and wear modelling are
fundamental issues in the industrial field, mainly correlated to the
economy and safety. Therefore, there is a need to study the wear
measurements and wear estimation. Pin-on-disc test is the most
common test which is used to study the wear behaviour. In this paper,
the pin-on-disc (AEROTECH UNIDEX 11) is used for the
investigation of the effects of normal load and hardness of material on
the wear under dry and sliding conditions. In the pin-on-disc rig, two
specimens were used; one, a pin is made of steel with a tip, positioned
perpendicular to the disc, where the disc is made of aluminium. The
pin wear and disc wear were measured by using the following
instruments: The Talysurf instrument, a digital microscope, and the
alicona instrument. The Talysurf profilometer was used to measure
the pin/disc wear scar depth, digital microscope was used to measure
the diameter and width of wear scar, and the alicona was used to
measure the pin wear and disc wear. After that, the Archard model,
American Society for Testing and Materials model (ASTM), and
neural network model were used for pin/disc wear modelling.
Simulation results were implemented by using the Matlab program.
This paper focuses on how the alicona can be used for wear
measurements and how the neural network can be used for wear
estimation.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: The aim of this study is to develop an anterior lumbar
interbody fusion (ALIF) PEEK cage suitable for Korean people. In this
study, CT images were obtained from Korean male (173cm, 71kg) and
3D Korean lumbar models were reconstructed based on the CT images
to investigate anatomical characteristics. Major design parameters of
anterior lumbar interbody fusion (ALIF) PEEK Cage were selected
using the morphological measurement information of the Korean
Lumbar models. Through finite element analysis and mechanical tests,
the developed ALIFPEEK Cage prototype was compared with the
Fidji Cage (Zimmer. Inc, USA) and it was found that the ALIF
prototype showed similar and/or superior mechanical performance
compared to the FidJi Cage. Also, clinical validation for the ALIF
PEEK Cage prototype was carried out to check predictable troubles in
surgical operations. Finally, it is considered that the convenience and
stability of the prototype was clinically verified.