Abstract: A renewable energy system discussed in this paper is
a stand-alone wind-hydrogen system for a remote island in Australia.
The analysis of an existing wind-diesel power system was performed.
Simulation technique was used to model the power system currently
employed on the island, and simulated different configurations of
additional hydrogen energy system. This study aims to determine the
suitable hydrogen integrated configuration to setting up the prototype
system for the island, which helps to reduce the diesel consumption
on the island. A set of configurations for the hydrogen system and
associated parameters that consists of wind turbines, electrolysers,
hydrogen internal combustion engines, and storage tanks has been
purposed. The simulation analyses various configurations that
perfectly balances the system to meet the demand on the island.
Abstract: During last decades, worldwide researchers dedicated
efforts to develop machine-based seismic Early Warning systems,
aiming at reducing the huge human losses and economic damages.
The elaboration time of seismic waveforms is to be reduced in order
to increase the time interval available for the activation of safety
measures. This paper suggests a Data Mining model able to correctly
and quickly estimate dangerousness of the running seismic event.
Several thousand seismic recordings of Japanese and Italian
earthquakes were analyzed and a model was obtained by means of a
Bayesian Network (BN), which was tested just over the first
recordings of seismic events in order to reduce the decision time and
the test results were very satisfactory.
The model was integrated within an Early Warning System
prototype able to collect and elaborate data from a seismic sensor
network, estimate the dangerousness of the running earthquake and
take the decision of activating the warning promptly.
Abstract: Grid scheduling is the process of mapping grid jobs to resources over multiple administrative domains. Traditionally, application-level schedulers have been tightly integrated with the application itself and were not easily applied to other applications. This design is generic that decouples the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. In this decoupled approach the application details are not revealed completely to broker, but customer will give the application to resource provider for execution. In a decoupled approach, apart from scheduling, the resource selection can be performed independently in order to achieve scalability.
Abstract: This research presents the development of simulation
modeling for WIP management in semiconductor fabrication.
Manufacturing simulation modeling is needed for productivity
optimization analysis due to the complex process flows involved
more than 35 percent re-entrance processing steps more than 15 times
at same equipment. Furthermore, semiconductor fabrication required
to produce high product mixed with total processing steps varies from
300 to 800 steps and cycle time between 30 to 70 days. Besides the
complexity, expansive wafer cost that potentially impact the
company profits margin once miss due date is another motivation to
explore options to experiment any analysis using simulation
modeling. In this paper, the simulation model is developed using
existing commercial software platform AutoSched AP, with
customized integration with Manufacturing Execution Systems
(MES) and Advanced Productivity Family (APF) for data collections
used to configure the model parameters and data source. Model
parameters such as processing steps cycle time, equipment
performance, handling time, efficiency of operator are collected
through this customization. Once the parameters are validated, few
customizations are made to ensure the prior model is executed. The
accuracy for the simulation model is validated with the actual output
per day for all equipments. The comparison analysis from result of
the simulation model compared to actual for achieved 95 percent
accuracy for 30 days. This model later was used to perform various
what if analysis to understand impacts on cycle time and overall
output. By using this simulation model, complex manufacturing
environment like semiconductor fabrication (fab) now have
alternative source of validation for any new requirements impact
analysis.
Abstract: The after–sales activities are nowadays acknowledged
as a relevant source of revenue, profit and competitive advantage in
most manufacturing industries. Top and middle management,
therefore, should focus on the definition of a structured business
performance measurement system for the after-sales business. The
paper aims at filling this gap, and presents an integrated methodology
for the after-sales network performance measurement, and provides
an empirical application to automotive case companies and their
official service network. This is the first study that presents an
integrated multivariate approach for total assessment and
improvement of after-sale services.
Abstract: Ant colony optimization (ACO) and its variants are
applied extensively to resolve various continuous optimization
problems. As per the various diversification and intensification
schemes of ACO for continuous function optimization, researchers
generally consider components of multidimensional state space to
generate the new search point(s). However, diversifying to a new
search space by updating only components of the multidimensional
vector may not ensure that the new point is at a significant distance
from the current solution. If a minimum distance is not ensured
during diversification, then there is always a possibility that the
search will end up with reaching only local optimum. Therefore, to
overcome such situations, a Mahalanobis distance-based
diversification with Nelder-Mead simplex-based search scheme for
each ant is proposed for the ACO strategy. A comparative
computational run results, based on nine nonlinear standard test
problems, confirms that the performance of ACO is improved
significantly with the integration of the proposed schemes in the
ACO.
Abstract: Fractional Fourier Transform, which is a
generalization of the classical Fourier Transform, is a powerful tool
for the analysis of transient signals. The discrete Fractional Fourier
Transform Hamiltonians have been proposed in the past with varying
degrees of correlation between their eigenvectors and Hermite
Gaussian functions. In this paper, we propose a new Hamiltonian for
the discrete Fractional Fourier Transform and show that the
eigenvectors of the proposed matrix has a higher degree of
correlation with the Hermite Gaussian functions. Also, the proposed
matrix is shown to give better Fractional Fourier responses with
various transform orders for different signals.
Abstract: In two studies we challenged the well consolidated
position in regret literature according to which the necessary
condition for the emergence of regret is a bad outcome ensuing from
free decisions. Without free choice, and, consequently, personal
responsibility, other emotions, such as disappointment, but not regret,
are supposed to be elicited. In our opinion, a main source of regret is
being obliged by circumstance out of our control to chose an
undesired option. We tested the hypothesis that regret resulting from
a forced choice is more intense than regret derived from a free choice
and that the outcome affects the latter, not the former. Besides, we
investigated whether two other variables – the perception of the level
of freedom of the choice and the choice justifiability – mediated the
relationships between choice and regret, as well as the other four
emotions we examined: satisfaction, anger toward oneself,
disappointment, anger towards circumstances. The two studies were
based on the scenario methodology and implied a 2 x 2 (choice x
outcome) between design. In the first study the foreseen short-term
effects of the choice were assessed; in the second study the
experienced long-term effects of the choice were assessed. In each
study 160 students of the Second University of Naples participated.
Results largely corroborated our hypotheses. They were discussed in
the light of the main theories on regret and decision making.
Abstract: Corporate social responsibility (CSR) viewpoint have challenged the traditional perception to understand corporations position. Production- and managerial-centred views are expanding towards reference group-centred policies. Consequently, the significance of new kind of knowledge has emerged. In addition to management of the organisation, the idea of CSR emphasises the importance to recognise the value-expectations of operational environment. It is know that management is often well-aware of corporate social responsibilities, but it is less clear how well these high level goals are understood in practical product design and development work. In this study, the apprehension above proved to be real to some degree. While management was very aware of CSR it was less familiar to designers. The outcome shows that it is essential to raise ethical values and issues higher in corporate communication, if it is wished that they materialize also in products.
Abstract: Landfill gas, particularly methane is one of the
greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from
simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy
soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor
followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at
acidification stage as indicated by the leachate quality with COD as
high as 55,511 mg/L and pH as low as 5.1. However, methanogenic
environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation.
Leachate degradation took place as the leachate moved through the
sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas
production from landfill by an in-situ degradation of leachate in the
sand at the bottom of the landfill.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents and evolutionary
computation techniques in legacy e-learning environments. It
introduces the design and development of a scalable and
interoperable integration platform supporting:
I) various assessment agents for e-learning environments,
II) a specific resource retrieval agent for the provision of
additional information from Internet sources matching the
needs and profile of the specific user and
III) a genetic algorithm designed to extract efficient information
(classifying rules) based on the students- answering input
data.
The agents are implemented in order to provide intelligent
assessment services based on computational intelligence techniques
such as Bayesian Networks and Genetic Algorithms.
The proposed Genetic Algorithm (GA) is used in order to extract
efficient information (classifying rules) based on the students-
answering input data. The idea of using a GA in order to fulfil this
difficult task came from the fact that GAs have been widely used in
applications including classification of unknown data.
The utilization of new and emerging technologies like web
services allows integrating the provided services to any web based
legacy e-learning environment.
Abstract: The Master-s of Public Health (MPH) degree is
growing in popularity among a number of higher education
institutions throughout the world as a distance education graduate
program. This paper offers an overview of program design and
development strategies that promote successful distance delivery of
MPH programs. Design and development challenges are discussed in
terms of type of distance delivery, accreditation, student demand,
faculty development, user needs, course content, and marketing
strategies. The ongoing development of a distance education MPH
program at Utah State University will be used to highlight and
consider various aspects of this important but challenging process.
Abstract: In our recent study, we have used ZnO nanoparticles assisted with UV light irradiation to investigate the photocatalytic degradation of Phenol Red (PR). The ZnO photocatalyst was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area analysis (BET) and UVvisible spectroscopy. X-ray diffractometry result for the ZnO nanoparticles exhibit normal crystalline phase features. All observed peaks can be indexed to the pure hexagonal wurtzite crystal structures, with the space group of P63mc. There are no other impurities in the diffraction peak. In addition, TEM measurement shows that most of the nanoparticles are rod-like and spherical in shape and fairly monodispersed. A significant degradation of the PR was observed when the catalyst was added into the solution even without the UV light exposure. In addition, the photodegradation increases with the photocatalyst loading. The surface area of the ZnO nanomaterials from the BET measurement was 11.9 m2/g. Besides the photocatalyst loading, the effect of some parameters on the photodegradation efficiency such as initial PR concentration and pH were also studied.
Abstract: A dual-reciprocity boundary element method is presented
for the numerical solution of a class of axisymmetric elastodynamic
problems. The domain integrals that arise in the integrodifferential
formulation are converted to line integrals by using the
dual-reciprocity method together suitably constructed interpolating
functions. The second order time derivatives of the displacement
in the governing partial differential equations are suppressed by
using Laplace transformation. In the Laplace transform domain, the
problem under consideration is eventually reduced to solving a system
of linear algebraic equations. Once the linear algebraic equations are
solved, the displacement and stress fields in the physical domain can
be recovered by using a numerical technique for inverting Laplace
transforms.
Abstract: In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.
Abstract: Scene interpretation systems need to match (often ambiguous)
low-level input data to concepts from a high-level ontology.
In many domains, these decisions are uncertain and benefit greatly
from proper context. This paper demonstrates the use of decision
trees for estimating class probabilities for regions described by feature
vectors, and shows how context can be introduced in order to improve
the matching performance.
Abstract: In this paper, the construction of a detailed spine
model is presented using the LifeMOD Biomechanics Modeler. The
detailed spine model is obtained by refining spine segments in
cervical, thoracic and lumbar regions into individual vertebra
segments, using bushing elements representing the intervertebral
discs, and building various ligamentous soft tissues between
vertebrae. In the sagittal plane of the spine, constant force will be
applied from the posterior to anterior during simulation to determine
dynamic characteristics of the spine. The force magnitude is
gradually increased in subsequent simulations. Based on these
recorded dynamic properties, graphs of displacement-force
relationships will be established in terms of polynomial functions by
using the least-squares method and imported into a haptic integrated
graphic environment. A thoracolumbar spine model with complex
geometry of vertebrae, which is digitized from a resin spine
prototype, will be utilized in this environment. By using the haptic
technique, surgeons can touch as well as apply forces to the spine
model through haptic devices to observe the locomotion of the spine
which is computed from the displacement-force relationship graphs.
This current study provides a preliminary picture of our ongoing
work towards building and simulating bio-fidelity scoliotic spine
models in a haptic integrated graphic environment whose dynamic
properties are obtained from LifeMOD. These models can be helpful
for surgeons to examine kinematic behaviors of scoliotic spines and
to propose possible surgical plans before spine correction operations.
Abstract: The Emergency Department of a medical center in
Taiwan cooperated to conduct the research. A predictive model of
triage system is contracted from the contract procedure, selection of
parameters to sample screening. 2,000 pieces of data needed for the
patients is chosen randomly by the computer. After three
categorizations of data mining (Multi-group Discriminant Analysis,
Multinomial Logistic Regression, Back-propagation Neural
Networks), it is found that Back-propagation Neural Networks can
best distinguish the patients- extent of emergency, and the accuracy
rate can reach to as high as 95.1%. The Back-propagation Neural
Networks that has the highest accuracy rate is simulated into the triage
acuity expert system in this research. Data mining applied to the
predictive model of the triage acuity expert system can be updated
regularly for both the improvement of the system and for education
training, and will not be affected by subjective factors.
Abstract: In this study, effects of EGR on CO and HC emissions
of a dual fuel HCCI-DI engine are investigated. Tests were
conducted on a single-cylinder variable compression ratio (VCR)
diesel engine with compression ratio of 17.5. Premixed gasoline is
provided by a carburetor connected to intake manifold and equipped
with a screw to adjust premixed air-fuel ratio, and diesel fuel is
injected directly into the cylinder through an injector at pressure of
250 bars. A heater placed at inlet manifold is used to control the
intake charge temperature. Optimal intake charge temperature was
110-115ºC due to better formation of a homogeneous mixture
causing HCCI combustion. Timing of diesel fuel injection has a great
effect on stratification of in-cylinder charge in HCCI combustion.
Experiments indicated 35 BTDC as the optimum injection timing.
Coolant temperature was maintained 50ºC during the tests. Results
show that increasing engine speed at a constant EGR rate leads to
increase in CO and UHC emissions due to the incomplete
combustion caused by shorter combustion duration and less
homogeneous mixture. Results also show that increasing EGR
reduces the amount of oxygen and leads to incomplete combustion
and therefore increases CO emission due to lower combustion
temperature. HC emission also increases as a result of lower
combustion temperatures.
Abstract: Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.