Abstract: Microscopic emission and fuel consumption models
have been widely recognized as an effective method to quantify real
traffic emission and energy consumption when they are applied with
microscopic traffic simulation models. This paper presents a
framework for developing the Microscopic Emission (HC, CO, NOx,
and CO2) and Fuel consumption (MEF) models for light-duty
vehicles. The variable of composite acceleration is introduced into
the MEF model with the purpose of capturing the effects of historical
accelerations interacting with current speed on emission and fuel
consumption. The MEF model is calibrated by multivariate
least-squares method for two types of light-duty vehicle using
on-board data collected in Beijing, China by a Portable Emission
Measurement System (PEMS). The instantaneous validation results
shows the MEF model performs better with lower Mean Absolute
Percentage Error (MAPE) compared to other two models. Moreover,
the aggregate validation results tells the MEF model produces
reasonable estimations compared to actual measurements with
prediction errors within 12%, 10%, 19%, and 9% for HC, CO, NOx
emissions and fuel consumption, respectively.
Abstract: Reliable water level forecasts are particularly
important for warning against dangerous flood and inundation. The
current study aims at investigating the suitability of the adaptive
network based fuzzy inference system for continuous water level
modeling. A hybrid learning algorithm, which combines the least
square method and the back propagation algorithm, is used to
identify the parameters of the network. For this study, water levels
data are available for a hydrological year of 2002 with a sampling
interval of 1-hour. The number of antecedent water level that should
be included in the input variables is determined by two statistical
methods, i.e. autocorrelation function and partial autocorrelation
function between the variables. Forecasting was done for 1-hour until
12-hour ahead in order to compare the models generalization at
higher horizons. The results demonstrate that the adaptive networkbased
fuzzy inference system model can be applied successfully and
provide high accuracy and reliability for river water level estimation.
In general, the adaptive network-based fuzzy inference system
provides accurate and reliable water level prediction for 1-hour ahead
where the MAPE=1.15% and correlation=0.98 was achieved. Up to
12-hour ahead prediction, the model still shows relatively good
performance where the error of prediction resulted was less than
9.65%. The information gathered from the preliminary results
provide a useful guidance or reference for flood early warning
system design in which the magnitude and the timing of a potential
extreme flood are indicated.
Abstract: Diesel Engines emit complex mixtures of inorganic
and organic compounds in the form of both solid and vapour phase
particles. Most of the particulates released are ultrafine nanoparticles
which are detrimental to human health and can easily enter the body
by respiration. The emissions standards on particulate matter release
from diesel engines are constantly upgraded within the European
Union and with future regulations based on the particles numbers
released instead of merely mass, the need for effective aftertreatment
devices will increase. Standard particulate filters in the form of wall
flow filters can have problems with high soot accumulation,
producing a large exhaust backpressure. A potential solution would
be to combine the standard filter with a flow through filter to reduce
the load on the wall flow filter. In this paper soot particle trapping has
been simulated in different continuous flow filters of monolithic
structure including the use of promoters, at laminar flow conditions.
An Euler Lagrange model, the discrete phase model in Ansys used
with user defined functions for forces acting on particles. A method
to quickly screen trapping of 5 nm and 10 nm particles in different
catalysts designs with tracers was also developed.
Simulations of square duct monoliths with promoters show that the
strength of the vortices produced are not enough to give a high
amount of particle deposition on the catalyst walls. The smallest
particles in the simulations, 5 and 10 nm particles were trapped to a
higher extent, than larger particles up to 1000 nm, in all studied
geometries with the predominant deposition mechanism being
Brownian diffusion. The comparison of the different filters designed
with a wall flow filter does show that the options for altering a design
of a flow through filter, without imposing a too large pressure drop
penalty are good.
Abstract: Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed
Abstract: Severe heart failure is a common problem that has a significant effect on health expenditures in industrialized countries; moreover it reduces patient-s quality of life. However, current research usually focuses either on detailed modeling of the heart or on detailed modeling of the cardiovascular system. Thus, this paper aims to present a sophisticated model of the heart enhanced with an extensive model of the cardiovascular system. Special interest is on the pressure and flow values close to the heart since these values are critical to accurately diagnose causes of heart failure. The model is implemented in Dymola an object-oriented, physical modeling language. Results achieved with the novel model show overall feasibility of the approach. Moreover, results are illustrated and compared to other models. The novel model shows significant improvements.
Abstract: This paper presents an analysis result of relationship
between business and information technology (IT) in business process
reengineering (BPR). 258 Japanese firm-level data collected have been
analyzed using structural equation modeling. This analysis was aimed
to illuminating success factors of achieve effective BPR. Analysis was
focused on management factors (including organizational factors) and
implementing management method (e.g. balanced score card, internal
control, etc.).These results would contribute for achieving effective
BPR by showing effective tasks and environment to be focused.
Abstract: The objective of this paper is to review and assess the
methodological issues and problems in marketing research, data and
knowledge mining in Turkey. As a summary, academic marketing
research publications in Turkey have significant problems. The most
vital problem seems to be related with modeling. Most of the
publications had major weaknesses in modeling. There were also,
serious problems regarding measurement and scaling, sampling and
analyses. Analyses myopia seems to be the most important problem
for young academia in Turkey. Another very important finding is the
lack of publications on data and knowledge mining in the academic
world.
Abstract: Neural networks are well known for their ability to
model non linear functions, but as statistical methods usually does,
they use a no parametric approach thus, a priori knowledge is not
obvious to be taken into account no more than the a posteriori
knowledge. In order to deal with these problematics, an original way
to encode the knowledge inside the architecture is proposed. This
method is applied to the problem of the evapotranspiration inside
karstic aquifer which is a problem of huge utility in order to deal
with water resource.
Abstract: In this paper we propose and examine an Adaptive
Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition
Autoregressive (STAR) modeling. Because STAR models follow
fuzzy logic approach, in the non-linear part fuzzy rules can be
incorporated or other training or computational methods can be
applied as the error backpropagation algorithm instead to nonlinear
squares. Furthermore, additional fuzzy membership functions can be
examined, beside the logistic and exponential, like the triangle,
Gaussian and Generalized Bell functions among others. We examine
two macroeconomic variables of US economy, the inflation rate and
the 6-monthly treasury bills interest rates.
Abstract: The effect of autofrettage process in strain hardened
thick-walled pressure vessels has been investigated theoretically by
finite element modeling. Equivalent von Mises stress is used as yield
criterion to evaluate the optimum autofrettage pressure and the
optimum radius of elastic-plastic junction. It has been observed that
the optimum autofrettage pressure increases along with the working
pressure. For two different working pressures, the effect of the ratio
of outer to inner radius (b/a=k) value on the optimum autofrettage
pressure is also noticed. The Optimum autofrettage pressure solely
depends on K value rather than on the inner or outer radius.
Furthermore, percentage reduction of von Mises stresses is compared
for different working pressures and different k values. Maximum von
Mises stress developed at different autofrettage pressure is equated
for elastic perfectly plastic and elastic-plastic material with different
slope of strain hardening segment. Cylinder material having higher
slope of strain hardening segment provides better benedictions in the
autofrettage process.
Abstract: Electro-hydraulic power steering (EHPS) system for
the fuel rate reduction and steering feel improvement is comprised of
ECU including the logic which controls the steering system and BL
DC motor and produces the best suited cornering force, BLDC motor,
high pressure pump integrated module and basic oil-hydraulic circuit
of the commercial HPS system.
Electro-hydraulic system can be studied in two ways such as
experimental and computer simulation. To get accurate results in
experimental study of EHPS system, the real boundary management is
necessary which is difficult task. And the accuracy of the experimental
results depends on the preparation of the experimental setup and
accuracy of the data collection. The computer simulation gives
accurate and reliable results if the simulation is carried out considering
proper boundary conditions. So, in this paper, each component of
EHPS was modeled, and the model-based analysis and control logic
was designed by using AMESim
Abstract: Scale defects are common surface defects in hot steel rolling. The modelling of such defects is problematic and their causes are not straightforward. In this study, we investigated genetic algorithms in search for a mathematical solution to scale formation. For this research, a high-dimensional data set from hot steel rolling process was gathered. The synchronisation of the variables as well as the allocation of the measurements made on the steel strip were solved before the modelling phase.
Abstract: Mitochondria are dynamic organelles, capable to
interact with each other. While the number of mitochondria in a cell
varies, their quality and functionality depends on the operation of
fusion, fission, motility and mitophagy. Nowadays, several
researches declare as an important factor in neurogenerative diseases
the disruptions in the regulation of mitochondrial dynamics. In this
paper a stochastic model in BioAmbients calculus is presented,
concerning mitochondrial fusion and its distribution in the renewal of
mitochondrial population in a cell. This model describes the
successive and dependent stages of protein synthesis, protein-s
activation and merging of two independent mitochondria.
Abstract: This paper focuses on operational risk measurement
techniques and on economic capital estimation methods. A data
sample of operational losses provided by an anonymous Central
European bank is analyzed using several approaches. Loss
Distribution Approach and scenario analysis method are considered.
Custom plausible loss events defined in a particular scenario are
merged with the original data sample and their impact on capital
estimates and on the financial institution is evaluated. Two main
questions are assessed – What is the most appropriate statistical
method to measure and model operational loss data distribution? and
What is the impact of hypothetical plausible events on the financial
institution? The g&h distribution was evaluated to be the most
suitable one for operational risk modeling. The method based on the
combination of historical loss events modeling and scenario analysis
provides reasonable capital estimates and allows for the measurement
of the impact of extreme events on banking operations.
Abstract: The Indian subcontinent is facing a massive challenge with regards to the energy security in member countries, i.e. providing a reliable source of electricity to facilitate development across various sectors of the economy and thereby achieve the developmental targets it has set for itself. A highly precarious situation exists in the subcontinent which is observed in the series of system failures which most of the times leads to system collapses-blackouts. To mitigate the issues related with energy security as well as keep in check the increasing supply demand gap, a possible solution that stands in front of the subcontinent is the deployment of an interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the sub continent as well as provide the infra structure for RES integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on VSC HVDC converters for the Supergrid modeling.
Abstract: In this article, biomechanical aspects of hen-s eggshell as a natural ceramic structure are studied. The images, taken by a scanning electron microscope (SEM), are used to investigate the microscopic aspects of the egg. It is observed that eggshell has a three-layered microstructure with different morphological and structural characteristics. Studies on the eggshell membrane (ESM) as a prosperous tissue suggest that it is placed to prevent the penetration of microorganisms into the egg. Finally, numerical models of the egg are presented to study the stress distribution and its deformation under different loading conditions. The effects of two different types of loading (hydrostatic and point loadings) on two different shell models (with constant and variable thicknesses) are investigated in detail.
Abstract: This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.
Abstract: A mathematical model based on a mass and energy
balance for the combustion in a cement rotary kiln was developed.
The model was used to investigate the impact of replacing about
45 % of the primary coal energy by different alternative fuels.
Refuse derived fuel, waste wood, solid hazardous waste and liquid
hazardous waste were used in the modeling. The results showed that
in order to keep the kiln temperature unchanged, and thereby
maintain the required clinker quality, the production capacity had to
be reduced by 1-15 %, depending on the fuel type. The reason for the
reduction is increased exhaust gas flow rates caused by the fuel
characteristics. The model, which has been successfully validated in a
full-scale experiment, was also used to show that the negative impact
on the production capacity can be avoided if a relatively small part of
the combustion air is replaced by pure oxygen.
Abstract: Identifying parameters in an epidemic model is one
of the important aspect of modeling. In this paper, we suggest a
method to identify the transmission rate by using the multistage
Adomian decomposition method. As a case study, we use the data of
the reported dengue fever cases in the city of Shah Alam, Malaysia.
The result obtained fairly represents the actual situation. However, in
the SIR model, this method serves as an alternative in parameter
identification and enables us to make necessary analysis for a smaller
interval.
Abstract: This paper discusses a systematic design of a Σ-Δ fractional-N Phase-Locked Loop based on HDL behavioral modeling. The proposed design consists in describing the mixed behavior of this PLL architecture starting from the specifications of each building block. The HDL models of critical PLL blocks have been described in VHDL-AMS to predict the different specifications of the PLL. The effect of different noise sources has been efficiently introduced to study the PLL system performances. The obtained results are compared with transistor-level simulations to validate the effectiveness of the proposed models for wireless applications in the frequency range around 2.45 GHz.