Abstract: Many single or multispan arch bridges are
strengthened with the addition of some kind of structural support
between adjacent arches of multispan or beside the arch barrel of a
single span to increase the strength of the overall structure. It was
traditionally formed by either placing loose rubble masonry blocks
between the arches and beside the arches or using mortar or concrete
to construct a more substantial structural bond between the spans. On
the other hand backing materials are present in some existing bridges.
Existing arch assessment procedures generally ignore the effects of
backing materials. In this paper an investigation of the effects of
backing on ratings for masonry arch bridges is carried out. It is
observed that increasing the overall lateral stability of the arch
system through the inclusion of structural backing results in an
enhanced failure load by reducing the likelihood of any tension
occurring at the top of the arch.
Abstract: A robust wheel slip controller for electric vehicles is
introduced. The proposed wheel slip controller exploits the dynamics
of electric traction drives and conventional hydraulic brakes for
achieving maximum energy efficiency and driving safety. Due to
the control of single wheel traction motors in combination with a
hydraulic braking system, it can be shown, that energy recuperation
and vehicle stability control can be realized simultaneously. The
derivation of a sliding mode wheel slip controller accessing two
drivetrain actuators is outlined and a comparison to a conventionally
braked vehicle is shown by means of simulation.
Abstract: Many studies have focused on the nonlinear analysis
of electroencephalography (EEG) mainly for the characterization of
epileptic brain states. It is assumed that at least two states of the
epileptic brain are possible: the interictal state characterized by a
normal apparently random, steady-state EEG ongoing activity; and
the ictal state that is characterized by paroxysmal occurrence of
synchronous oscillations and is generally called in neurology, a
seizure.
The spatial and temporal dynamics of the epileptogenic process is
still not clear completely especially the most challenging aspects of
epileptology which is the anticipation of the seizure. Despite all the
efforts we still don-t know how and when and why the seizure
occurs. However actual studies bring strong evidence that the
interictal-ictal state transition is not an abrupt phenomena. Findings
also indicate that it is possible to detect a preseizure phase.
Our approach is to use the neural network tool to detect interictal
states and to predict from those states the upcoming seizure ( ictal
state). Analysis of the EEG signal based on neural networks is used
for the classification of EEG as either seizure or non-seizure. By
applying prediction methods it will be possible to predict the
upcoming seizure from non-seizure EEG.
We will study the patients admitted to the epilepsy monitoring
unit for the purpose of recording their seizures. Preictal, ictal, and
post ictal EEG recordings are available on such patients for analysis
The system will be induced by taking a body of samples then
validate it using another. Distinct from the two first ones a third body
of samples is taken to test the network for the achievement of
optimum prediction. Several methods will be tried 'Backpropagation
ANN' and 'RBF'.
Abstract: Petri Net (PN) has proven to be effective graphical, mathematical, simulation, and control tool for Discrete Event Systems (DES). But, with the growth in the complexity of modern industrial, and communication systems, PN found themselves inadequate to address the problems of uncertainty, and imprecision in data. This gave rise to amalgamation of Fuzzy logic with Petri nets and a new tool emerged with the name of Fuzzy Petri Nets (FPN). Although there had been a lot of research done on FPN and a number of their applications have been anticipated, but their basic types and structure are still ambiguous. Therefore, in this research, an effort is made to categorize FPN according to their structure and algorithms Further, literature review of the applications of FPN in the light of their classifications has been done.
Abstract: In a travelling wave thermoacoustic device, the
regenerator sandwiched between a pair of (hot and cold) heat
exchangers constitutes the so-called thermoacoustic core, where the
thermoacoustic energy conversion from heat to acoustic power takes
place. The temperature gradient along the regenerator caused by the
two heat exchangers excites and maintains the acoustic wave in the
resonator. The devices are called travelling wave thermoacoustic
systems because the phase angle difference between the pressure and
velocity oscillation is close to zero in the regenerator. This paper
presents the construction and testing of a thermoacoustic engine
equipped with a ceramic regenerator, made from a ceramic material
that is usually used as catalyst substrate in vehicles- exhaust systems,
with fine square channels (900 cells per square inch). The testing
includes the onset temperature difference (minimum temperature
difference required to start the acoustic oscillation in an engine), the
acoustic power output, thermal efficiency and the temperature profile
along the regenerator.
Abstract: The paper presents the potential for RES in Romania
and the results of the Romanian national research project “Romania
contribution to the European targets regarding the development of
renewable energy sources - PROMES". The objective of the project
is the development of energy generation from renewable energy
sources (RES) in Romania by drawing up scenarios and prognosis
harmonized with national and European targets, RES development
effects modeling (environmental, economic, social etc.), research of
the impact of the penetration of RES into the main, implementation
of an advanced software system tool for RES information recording
and communication, experimental research based on demonstrative
applications.
The expected results are briefly presented, as well as the social,
economic and environmental impact.
Abstract: The Long-range Energy and Alternatives Planning (LEAP) energy planning system has been developed for South Africa, for the 2005 base year and a limited number of plausible future scenarios that may have significant implications (negative or positive) in terms of environmental impacts. The system quantifies the national energy demand for the domestic, commercial, transport, industry and agriculture sectors, the supply of electricity and liquid fuels, and the resulting emissions. The South African National Energy Research Institute (SANERI) identified the need to develop an environmental assessment tool, based on the LEAP energy planning system, to provide decision-makers and stakeholders with the necessary understanding of the environmental impacts associated with different energy scenarios. A comprehensive analysis of indicators that are used internationally and in South Africa was done and the available data was accessed to select a reasonable number of indicators that could be utilized in energy planning. A consultative process was followed to determine the needs of different stakeholders on the required indicators and also the most suitable form of reporting. This paper demonstrates the application of Energy Environmental Sustainability Indicators (EESIs) as part of the developed tool, which assists with the identification of the environmental consequences of energy generation and use scenarios and thereby promotes sustainability, since environmental considerations can then be integrated into the preparation and adoption of policies, plans, programs and projects. Recommendations are made to refine the tool further for South Africa.
Abstract: This paper presents a integer frequency offset (IFO)
estimation scheme for the 3GPP long term evolution (LTE) downlink
system. Firstly, the conventional joint detection method for IFO and
sector cell index (CID) information is introduced. Secondly, an IFO
estimation without explicit sector CID information is proposed, which
can operate jointly with the proposed IFO estimation and reduce
the time delay in comparison with the conventional joint method.
Also, the proposed method is computationally efficient and has almost
similar performance in comparison with the conventional method over
the Pedestrian and Vehicular channel models.
Abstract: In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.
Abstract: In the numerical solution of the forward dynamics of a
multibody system, the positions and velocities of the bodies in the
system are obtained first. With the information of the system state
variables at each time step, the internal and external forces acting on
the system are obtained by appropriate contact force models if the
continuous contact method is used instead of a discrete contact
method. The local deformation of the bodies in contact, represented
by penetration, is used to compute the contact force. The ability and
suitability with current cylindrical contact force models to describe
the contact between bodies with cylindrical geometries with
particular focus on internal contacting geometries involving low
clearances and high loads simultaneously is discussed in this paper.
A comparative assessment of the performance of each model under
analysis for different contact conditions, in particular for very
different penetration and clearance values, is presented. It is
demonstrated that some models represent a rough approximation to
describe the conformal contact between cylindrical geometries
because contact forces are underestimated.
Abstract: Nowadays scientific data is inevitably digital and
stored in a wide variety of formats in heterogeneous systems.
Scientists need to access an integrated view of remote or local
heterogeneous data sources with advanced data accessing, analyzing,
and visualization tools. This research suggests the use of Service
Oriented Architecture (SOA) to integrate biological data from
different data sources. This work shows SOA will solve the problems
that facing integration process and if the biologist scientists can
access the biological data in easier way. There are several methods to
implement SOA but web service is the most popular method. The
Microsoft .Net Framework used to implement proposed architecture.
Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: Today, computer systems are more and more complex and support growing security risks. The security managers need to find effective security risk assessment methodologies that allow modeling well the increasing complexity of current computer systems but also maintaining low the complexity of the assessment procedure. This paper provides a brief analysis of common security risk assessment methodologies leading to the selection of a proper methodology to fulfill these requirements. Then, a detailed analysis of the most effective methodology is accomplished, presenting numerical examples to demonstrate how easy it is to use.
Abstract: This paper explores steady-state characteristics of
grid-connected doubly fed induction motor (DFIM) in case of unity
power factor operation. Based on the synchronized mathematical
model, analytic determination of the control laws is presented and
illustrated by various figures to understand the effect of the applied
rotor voltage on the speed and the active power. On other hand,
unlike previous works where the stator resistance was neglected, in
this work, stator resistance is included such that the equations can be
applied to small wind turbine generators which are becoming more
popular. Finally the work is crowned by integration of the studied
induction generator in a wind system where an open loop control is
proposed confers a remarkable simplicity of implementation
compared to the known methods.
Abstract: Supply Chain Management (SCM) is the integration
between manufacturer, transporter and customer in order to form one
seamless chain that allows smooth flow of raw materials, information
and products throughout the entire network that help in minimizing
all related efforts and costs. The main objective of this paper is to
develop a model that can accept a specified number of spare-parts
within the supply chain, simulating its inventory operations
throughout all stages in order to minimize the inventory holding
costs, base-stock, safety-stock, and to find the optimum quantity of
inventory levels, thereby suggesting a way forward to adapt some
factors of Just-In-Time to minimizing the inventory costs throughout
the entire supply chain. The model has been developed using Micro-
Soft Excel & Visual Basic in order to study inventory allocations in
any network of the supply chain. The application and reproducibility
of this model were tested by comparing the actual system that was
implemented in the case study with the results of the developed
model. The findings showed that the total inventory costs of the
developed model are about 50% less than the actual costs of the
inventory items within the case study.
Abstract: The promises of component-based technology can only be fully realized when the system contains in its design a necessary level of separation of concerns. The authors propose to focus on the concerns that emerge throughout the life cycle of the system and use them as an architectural foundation for the design of a component-based framework. The proposed model comprises a set of superimposed views of the system describing its functional and non-functional concerns. This approach is illustrated by the design of a specific framework for data analysis and data acquisition and supplemented with experiences from using the systems developed with this framework at the Fermi National Accelerator Laboratory.
Abstract: Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.
Abstract: This paper provides an introduction into the evolution
of information and communication technology and illustrates its
usage in the work domain. The paper is sub-divided into two parts.
The first part gives an overview over the different phases of
information processing in the work domain. It starts by charting the
past and present usage of computers in work environments and shows
current technological trends, which are likely to influence future
business applications. The second part starts by briefly describing,
how the usage of computers changed business processes in the past,
and presents first Ambient Intelligence applications based on
identification and localization information, which are already used in
the production and retail sector. Based on current systems and
prototype applications, the paper gives an outlook of how Ambient
Intelligence technologies could change business processes in the
future.
Abstract: Using spatial models as a shared common basis of
information about the environment for different kinds of contextaware
systems has been a heavily researched topic in the last years.
Thereby the research focused on how to create, to update, and to
merge spatial models so as to enable highly dynamic, consistent and
coherent spatial models at large scale. In this paper however, we
want to concentrate on how context-aware applications could use this
information so as to adapt their behavior according to the situation
they are in. The main idea is to provide the spatial model
infrastructure with a situation recognition component based on
generic situation templates. A situation template is – as part of a
much larger situation template library – an abstract, machinereadable
description of a certain basic situation type, which could be
used by different applications to evaluate their situation. In this
paper, different theoretical and practical issues – technical, ethical
and philosophical ones – are discussed important for understanding
and developing situation dependent systems based on situation
templates. A basic system design is presented which allows for the
reasoning with uncertain data using an improved version of a
learning algorithm for the automatic adaption of situation templates.
Finally, for supporting the development of adaptive applications, we
present a new situation-aware adaptation concept based on
workflows.