Abstract: The tombolo of Giens is located in the town of Hyères
(France). We recall the history of coastal erosion, and prominent
factors affecting the evolution of the western tombolo. We then
discuss the possibility of stabilizing the western tombolo. Our
argumentation relies on a coupled model integrating swells, currents,
water levels and sediment transport. We present the conclusions of
the simulations of various scenarios, including pre-existing
propositions from coastal engineering offices. We conclude that
beach replenishment seems to be necessary but not sufficient for the
stabilization of the beach. Breakwaters reveal effective particularly in
the most exposed northern area. Some solutions fulfill conditions so
as to be elected as satisfactory. We give a comparative analysis of the
efficiency of 14 alternatives for the protection of the tombolo.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: The continuous decline of petroleum and natural gas
reserves and non linear rise of oil price has brought about a
realisation of the need for a change in our perpetual dependence on
the fossil fuel. A day to day increased consumption of crude and
petroleum products has made a considerable impact on our foreign
exchange reserves. Hence, an alternate resource for the conversion of
energy (both liquid and gas) is essential for the substitution of
conventional fuels. Biomass is the alternate solution for the present
scenario. Biomass can be converted into both liquid as well as
gaseous fuels and other feedstocks for the industries.
Abstract: Motion Tracking and Stereo Vision are complicated,
albeit well-understood problems in computer vision. Existing
softwares that combine the two approaches to perform stereo motion
tracking typically employ complicated and computationally expensive
procedures. The purpose of this study is to create a simple and
effective solution capable of combining the two approaches. The
study aims to explore a strategy to combine the two techniques
of two-dimensional motion tracking using Kalman Filter; and depth
detection of object using Stereo Vision. In conventional approaches
objects in the scene of interest are observed using a single camera.
However for Stereo Motion Tracking; the scene of interest is
observed using video feeds from two calibrated cameras. Using two
simultaneous measurements from the two cameras a calculation for
the depth of the object from the plane containing the cameras is made.
The approach attempts to capture the entire three-dimensional spatial
information of each object at the scene and represent it through a
software estimator object. In discrete intervals, the estimator tracks
object motion in the plane parallel to plane containing cameras and
updates the perpendicular distance value of the object from the plane
containing the cameras as depth. The ability to efficiently track
the motion of objects in three-dimensional space using a simplified
approach could prove to be an indispensable tool in a variety of
surveillance scenarios. The approach may find application from high
security surveillance scenes such as premises of bank vaults, prisons
or other detention facilities; to low cost applications in supermarkets
and car parking lots.
Abstract: Future flood can be predicted using the probable
maximum flood (PMF). PMF is calculated using the historical
discharge or rainfall data considering the other climatic parameters
remaining stationary. However climate is changing globally and the
key climatic variables are temperature, evaporation, rainfall and sea
level rise are likely to change. To develop scenarios to a basin or
catchment scale these important climatic variables should be
considered. Nowadays scenario based on climatic variables is more
suitable than PMF. Six scenarios were developed for a large Fitzroy
basin and presented in this paper.
Abstract: Environmental impacts of six 3D printers using
various materials were compared to determine if material choice
drove sustainability, or if other factors such as machine type, machine
size, or machine utilization dominate. Cradle-to-grave life-cycle
assessments were performed, comparing a commercial-scale FDM
machine printing in ABS plastic, a desktop FDM machine printing in
ABS, a desktop FDM machine printing in PET and PLA plastics, a
polyjet machine printing in its proprietary polymer, an SLA machine
printing in its polymer, and an inkjet machine hacked to print in salt
and dextrose. All scenarios were scored using ReCiPe Endpoint H
methodology to combine multiple impact categories, comparing
environmental impacts per part made for several scenarios per
machine. Results showed that most printers’ ecological impacts were
dominated by electricity use, not materials, and the changes in
electricity use due to different plastics was not significant compared
to variation from one machine to another. Variation in machine idle
time determined impacts per part most strongly. However, material
impacts were quite important for the inkjet printer hacked to print in
salt: In its optimal scenario, it had up to 1/38th the impacts coreper
part as the worst-performing machine in the same scenario. If salt
parts were infused with epoxy to make them more physically robust,
then much of this advantage disappeared, and material impacts
actually dominated or equaled electricity use. Future studies should
also measure DMLS and SLS processes / materials.
Abstract: The purpose of this study was to reduce patient
waiting times, improve system throughput and improve resources
utilization in radiology department. A discrete event simulation
model was developed using Arena simulation software to investigate
different alternatives to improve the overall system delivery based on
adding resource scenarios due to the linkage between patient waiting
times and resource availability. The study revealed that there is no
addition investment need to procure additional scanner but hospital
management deploy managerial tactics to enhance machine
utilization and reduce the long waiting time in the department.
Abstract: The continuous decline of petroleum and natural gas
reserves and non linear rise of oil price has brought about a
realisation of the need for a change in our perpetual dependence on
the fossil fuel. A day to day increased consumption of crude and
petroleum products has made a considerable impact on our foreign
exchange reserves. Hence, an alternate resource for the conversion of
energy (both liquid and gas) is essential for the substitution of
conventional fuels. Biomass is the alternate solution for the present
scenario. Biomass can be converted into both liquid as well as
gaseous fuels and other feedstocks for the industries.
Abstract: Femtocells are regarded as a milestone for next
generation cellular networks. As femtocells are deployed in an
unplanned manner, there is a chance of assigning same resource to
neighboring femtocells. This scenario may induce co-channel
interference and may seriously affect the service quality of
neighboring femtocells. In addition, the dominant transmit power of a
femtocell will induce co-tier interference to neighboring femtocells.
Thus to jointly handle co-tier and co-channel interference, we
propose an interference-free power and resource block allocation
(IFPRBA) algorithm for closely located, closed access femtocells.
Based on neighboring list, inter-femto-base station distance and
uplink noise power, the IFPRBA algorithm assigns non-interfering
power and resource to femtocells. The IFPRBA algorithm also
guarantees the quality of service to femtouser based on the
knowledge of resource requirement, connection type, and the
tolerable delay budget. Simulation result shows that the interference
power experienced in IFPRBA algorithm is below the tolerable
interference power and hence the overall service success ratio, PRB
efficiency and network throughput are maximum when compared to
conventional resource allocation framework for femtocell (RAFF)
algorithm.
Abstract: Software Architecture is the basic structure of
software that states the development and advancement of a software
system. Software architecture is also considered as a significant tool
for the construction of high quality software systems. A clean design
leads to the control, value and beauty of software resulting in its
longer life while a bad design is the cause of architectural erosion
where a software evolution completely fails. This paper discusses the
occurrence of software architecture erosion and presents a set of
methods for the detection, declaration and prevention of architecture
erosion. The causes and symptoms of architecture erosion are
observed with the examples of prescriptive and descriptive
architectures and the practices used to stop this erosion are also
discussed by considering different types of software erosion and their
affects. Consequently finding and devising the most suitable
approach for fighting software architecture erosion and in some way
reducing its affect is evaluated and tested on different scenarios.
Abstract: Electricity spot prices are highly volatile under
optimal generation capacity scenarios due to factors such as nonstorability
of electricity, peak demand at certain periods, generator
outages, fuel uncertainty for renewable energy generators, huge
investments and time needed for generation capacity expansion etc.
As a result market participants are exposed to price and volume risk,
which has led to the development of risk management practices. This
paper provides an overview of risk management practices by market
participants in electricity markets using financial derivatives.
Abstract: The Smart Help for persons with disability (PWD) is a
part of the project SMARTDISABLE which aims to develop relevant
solution for PWD that target to provide an adequate workplace
environment for them. It would support PWD needs smartly through
smart help to allow them access to relevant information and
communicate with other effectively and flexibly, and smart editor
that assist them in their daily work. It will assist PWD in knowledge
processing and creation as well as being able to be productive at the
work place. The technical work of the project involves design of a
technological scenario for the Ambient Intelligence (AmI) - based
assistive technologies at the workplace consisting of an integrated
universal smart solution that suits many different impairment
conditions and will be designed to empower the Physically disabled
persons (PDP) with the capability to access and effectively utilize the
ICTs in order to execute knowledge rich working tasks with
minimum efforts and with sufficient comfort level. The proposed
technology solution for PWD will support voice recognition along
with normal keyboard and mouse to control the smart help and smart
editor with dynamic auto display interface that satisfies the
requirements for different PWD group. In addition, a smart help will
provide intelligent intervention based on the behavior of PWD to
guide them and warn them about possible misbehavior. PWD can
communicate with others using Voice over IP controlled by voice
recognition. Moreover, Auto Emergency Help Response would be
supported to assist PWD in case of emergency. This proposed
technology solution intended to make PWD very effective at the
work environment and flexible using voice to conduct their tasks at
the work environment. The proposed solution aims to provide
favorable outcomes that assist PWD at the work place, with the
opportunity to participate in PWD assistive technology innovation
market which is still small and rapidly growing as well as upgrading
their quality of life to become similar to the normal people at the
workplace. Finally, the proposed smart help solution is applicable in
all workplace setting, including offices, manufacturing, hospital, etc.
Abstract: Time and cost are the main goals of the construction
project management. The first schedule developed may not be a
suitable schedule for beginning or completing the project to achieve
the target completion time at a minimum total cost. In general, there
are trade-offs between time and cost (TCT) to complete the activities
of a project. This research presents genetic algorithms (GAs) multiobjective
model for project scheduling considering different
scenarios such as least cost, least time, and target time.
Abstract: In this paper two approaches to joint signal detection,
time of arrival (ToA) and angle of arrival (AoA) estimation in
multi-element antenna array are investigated. Two scenarios were
considered: first one, when the waveform of the useful signal
is known a priori and, second one, when the waveform of the
desired signal is unknown. For first scenario, the antenna array
signal processing based on multi-element matched filtering (MF)
with the following non-coherent detection scheme and maximum
likelihood (ML) parameter estimation blocks is exploited. For second
scenario, the signal processing based on the antenna array elements
covariance matrix estimation with the following eigenvector analysis
and ML parameter estimation blocks is applied. The performance
characteristics of both signal processing schemes are thoroughly
investigated and compared for different useful signals and noise
parameters.
Abstract: This paper attempts to evaluate the effect of fire
damage on concrete by using nonlinear resonance vibration method,
one of the nonlinear nondestructive method. Concrete exhibits not
only nonlinear stress-strain relation but also hysteresis and discrete
memory effect which are contained in consolidated materials.
Hysteretic materials typically show the linear resonance frequency
shift. Also, the shift of resonance frequency is changed according to
the degree of micro damage. The degree of the shift can be obtained
through nonlinear resonance vibration method. Five exposure
scenarios were considered in order to make different internal micro
damage. Also, the effect of post-fire-curing on fire-damaged concrete
was taken into account to conform the change in internal damage.
Hysteretic nonlinearity parameter was obtained by amplitudedependent
resonance frequency shift after specific curing periods. In
addition, splitting tensile strength was measured on each sample to
characterize the variation of residual strength. Then, a correlation
between the hysteretic nonlinearity parameter and residual strength
was proposed from each test result.
Abstract: Load Forecasting plays a key role in making today's
and future's Smart Energy Grids sustainable and reliable. Accurate
power consumption prediction allows utilities to organize in advance
their resources or to execute Demand Response strategies more
effectively, which enables several features such as higher
sustainability, better quality of service, and affordable electricity
tariffs. It is easy yet effective to apply Load Forecasting at larger
geographic scale, i.e. Smart Micro Grids, wherein the lower available
grid flexibility makes accurate prediction more critical in Demand
Response applications. This paper analyses the application of
short-term load forecasting in a concrete scenario, proposed within the
EU-funded GreenCom project, which collect load data from single
loads and households belonging to a Smart Micro Grid. Three
short-term load forecasting techniques, i.e. linear regression, artificial
neural networks, and radial basis function network, are considered,
compared, and evaluated through absolute forecast errors and training
time. The influence of weather conditions in Load Forecasting is also
evaluated. A new definition of Gain is introduced in this paper, which
innovatively serves as an indicator of short-term prediction
capabilities of time spam consistency. Two models, 24- and
1-hour-ahead forecasting, are built to comprehensively compare these
three techniques.
Abstract: Access control is one of the most challenging issues
facing information security. Access control is defined as, the ability to
permit or deny access to a particular computational resource or digital
information by an unauthorized user or subject. The concept of usage
control (UCON) has been introduced as a unified approach to capture a
number of extensions for access control models and systems. In
UCON, an access decision is determined by three factors:
authorizations, obligations and conditions. Attribute mutability and
decision continuity are two distinct characteristics introduced by
UCON for the first time. An observation of UCON components
indicates that, the components are predefined and static. In this paper,
we propose a new and flexible model of usage control for the creation
and elimination of some of these components; for example new
objects, subjects, attributes and integrate these with the original
UCON model. We also propose a model for concurrent usage
scenarios in UCON.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: The Analytic Hierarchy Process is frequently used
approach for solving decision making problems. There exists wide
range of software programs utilizing that approach. Their main
disadvantage is that they are relatively expensive and missing
intermediate calculations. This work introduces a Microsoft Excel
add-in called DAME – Decision Analysis Module for Excel.
Comparing to other computer programs DAME is free, can work
with scenarios or multiple decision makers and displays intermediate
calculations. Users can structure their decision models into three
levels – scenarios/users, criteria and variants. Items on all levels can
be evaluated either by weights or pair-wise comparisons. There are
provided three different methods for the evaluation of the weights of
criteria, the variants as well as the scenarios – Saaty’s Method,
Geometric Mean Method and Fuller’s Triangle Method.
Multiplicative and additive syntheses are supported. The proposed
software package is demonstrated on couple of illustrating examples
of real life decision problems.
Abstract: Current transformers (CTs) are used to transform large primary currents to a small secondary current. Since most standard equipment’s are not designed to handle large primary currents the CTs have an important part in any electrical system for the purpose of Metering and Protection both of which are integral in Power system. Now a days due to advancement in solid state technology, the operation times of the protective relays have come to a few cycles from few seconds. Thus, in such a scenario it becomes important to study the transient response of the current transformers as it will play a vital role in the operating of the protective devices.
This paper shows the steady state and transient behavior of current transformers and how it changes with change in connected burden. The transient and steady state response will be captured using the data acquisition software LabVIEW. Analysis is done on the real time data gathered using LabVIEW. Variation of current transformer characteristics with changes in burden will be discussed.