Abstract: The seismic risk mitigation from the perspective of
the old buildings stock is truly essential in Algerian urban areas,
particularly those located in seismic prone regions, such as Annaba
city, and which the old buildings present high levels of degradation
associated with no seismic strengthening and/or rehabilitation
concerns. In this sense, the present paper approaches the issue of the
seismic vulnerability assessment of old masonry building stocks
through the adaptation of a simplified methodology developed for a
European context area similar to that of Annaba city, Algeria.
Therefore, this method is used for the first level of seismic
vulnerability assessment of the masonry buildings stock of the old
city center of Annaba. This methodology is based on a vulnerability
index that is suitable for the evaluation of damage and for the
creation of large-scale loss scenarios. Over 380 buildings were
evaluated in accordance with the referred methodology and the
results obtained were then integrated into a Geographical Information
System (GIS) tool. Such results can be used by the Annaba city
council for supporting management decisions, based on a global view
of the site under analysis, which led to more accurate and faster
decisions for the risk mitigation strategies and rehabilitation plans.
Abstract: In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.
Abstract: The aim of this paper is to present the optimization
methodology developed in the frame of a Coastal Transport
Information System. The system will be used for the effective design
of coastal transportation lines and incorporates subsystems that
implement models, tools and techniques that may support the design
of improved networks. The role of the optimization and decision
subsystem is to provide the user with better and optimal scenarios
that will best fulfill any constrains, goals or requirements posed. The
complexity of the problem and the large number of parameters and
objectives involved led to the adoption of an evolutionary method
(Genetic Algorithms). The problem model and the subsystem
structure are presented in detail, and, its support for simulation is also
discussed.
Abstract: The feedbacks obtained regarding the sense of
presence from pilot users operating a Mobile Robotic presence
(MRP) system to visit a simulated museum are reported in this paper.
The aim is to investigate how much the perception of system’s
usefulness and ease of use is affected by operators’ sense of social
telepresence (presence) in the remote location. Therefore, scenarios
of visiting a museum are simulated and the user operators are
supposed to perform some regular tasks inside the remote
environment including interaction with local users, navigation and
visiting the artworks. Participants were divided into two groups,
those who had previous experience of operation and interaction with
a MRP system and those who never had experience. Based on the
results, both groups provided different feedbacks. Moreover, there
was a significant association between user’s sense of presence and
their perception of system usefulness and ease of use.
Abstract: The paper tackles the topic of determining the cost of
innovation in software development projects. Innovation can be
achieved either in a planned or unplanned manner. The paper
approaches the scenarios were innovation is planned for. As a starting
point an innovative software development project is analyzed. The
project is depicted step by step as it was implemented, from inception
to delivery. Costs that are proprietary to innovation in software
development are isolated based on the author’s personal experience
in managing the above mentioned project. Innovation costs
components identified by the author are then validated using open
discussions with software development professionals and projects
managers on LinkedIn groups. In order to receive relevant feedback
only groups that focus on software development and innovation
management are targeted. Additional innovation cost components
suggested by software development professionals and projects
managers are also considered. Based on the identified cost
components an indicator is built. The indicator is meant to formalize
the process of determining the cost of innovation in a software
development project. The indicator aggregates all the innovation cost
components that are identified in the research process. The process of
calculating each cost component is also described. Conclusions are
formulated and new related research topics are submitted for debate.
Abstract: The objective of countercyclical capital buffer is to
encourage banks to build up buffers in good times that can be drawn
down in bad times. The aim of the report is to assess such decisions
by banks derived from three approaches. The approaches are the
aggregate credit-to-GDP ratio, credit growth as well as banking
sector profits. The approaches are implemented for Estonia, Latvia
and Lithuania for the time period 2000-2012. The report compares
three approaches and analyses their relevance to the Baltic States by
testing the correlation between a growth in studied variables and a
growth of corresponding gaps. Methods used in the empirical part of
the report are econometric analysis as well as economic analysis,
development indicators, relative and absolute indicators and other
methods. The research outcome is a cross-Baltic comparison of two
alternative approaches to establish or release a countercyclical capital
buffer by banks and their implications for each Baltic country.
Abstract: The effects of hypertension are often lethal thus its
early detection and prevention is very important for everybody. In
this paper, a neural network (NN) model was developed and trained
based on a dataset of hypertension causative parameters in order to
forecast the likelihood of occurrence of hypertension in patients. Our
research goal was to analyze the potential of the presented NN to
predict, for a period of time, the risk of hypertension or the risk of
developing this disease for patients that are or not currently
hypertensive. The results of the analysis for a given patient can
support doctors in taking pro-active measures for averting the
occurrence of hypertension such as recommendations regarding the
patient behavior in order to lower his hypertension risk. Moreover,
the paper envisages a set of three example scenarios in order to
determine the age when the patient becomes hypertensive, i.e.
determine the threshold for hypertensive age, to analyze what
happens if the threshold hypertensive age is set to a certain age and
the weight of the patient if being varied, and, to set the ideal weight
for the patient and analyze what happens with the threshold of
hypertensive age.
Abstract: Despite the highly touted benefits, emerging
technologies have unleashed pervasive concerns regarding unintended
and unforeseen social impacts. Thus, those wishing to create safe and
socially acceptable products need to identify such side effects and
mitigate them prior to the market proliferation. Various methodologies
in the field of technology assessment (TA), namely Delphi, impact
assessment, and scenario planning, have been widely incorporated in
such a circumstance. However, literatures face a major limitation in
terms of sole reliance on participatory workshop activities. They
unfortunately missed out the availability of a massive untapped data
source of futuristic information flooding through the Internet. This
research thus seeks to gain insights into utilization of futuristic data,
future-oriented documents from the Internet, as a supplementary
method to generate social impact scenarios whilst capturing
perspectives of experts from a wide variety of disciplines. To this end,
network analysis is conducted based on the social keywords extracted
from the futuristic documents by text mining, which is then used as a
guide to produce a comprehensive set of detailed scenarios. Our
proposed approach facilitates harmonized depictions of possible
hazardous consequences of emerging technologies and thereby makes
decision makers more aware of, and responsive to, broad qualitative
uncertainties.
Abstract: Future mobile networks following 5th generation will
be characterized by one thousand times higher gains in capacity;
connections for at least one hundred billion devices; user experience
capable of extremely low latency and response times. To be close to
the capacity requirements and higher reliability, advanced
technologies have been studied, such as multiple connectivity, small
cell enhancement, heterogeneous networking, and advanced
interference and mobility management. This paper is focused on the
multiple connectivity in heterogeneous cellular networks. We
investigate the performance of coverage and user throughput in several
deployment scenarios. Using the stochastic geometry approach, the
SINR distributions and the coverage probabilities are derived in case
of dual connection. Also, to compare the user throughput enhancement
among the deployment scenarios, we calculate the spectral efficiency
and discuss our results.
Abstract: It is likely that robots will cross the boundaries of
industry into households over the next decades. With demographic
challenges worldwide, the future ageing populations will require the
introduction of assistive technologies capable of providing, care,
human dignity and quality of life through the aging process. Robotics
technology has a high potential for being used in the areas of social
and healthcare by promoting a wide range of activities such as
entertainment, companionship, supervision or cognitive and physical
assistance. However such close Human Robotics Interaction (HRI)
encompass a rich set of ethical scenarios that need to be addressed
before Socially Assistive Robots (SARs) reach the global markets.
Such interactions with robots may seem a worthy goal for many
technical/financial reasons but inevitably require close attention to
the ethical dimensions of such interactions. This article investigates
the current HRI benchmark of social success. It revises it according
to the ethical principles of beneficence, non-maleficence and justice
aligned with social care ethos. An extension of such benchmark is
proposed based on an empirical study of HRIs conducted with elderly
groups.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: This paper presents an efficient fusion algorithm for
iris images to generate stable feature for recognition in unconstrained
environment. Recently, iris recognition systems are focused on real
scenarios in our daily life without the subject’s cooperation. Under
large variation in the environment, the objective of this paper is to
combine information from multiple images of the same iris. The
result of image fusion is a new image which is more stable for further
iris recognition than each original noise iris image. A wavelet-based
approach for multi-resolution image fusion is applied in the fusion
process. The detection of the iris image is based on Adaboost
algorithm and then local binary pattern (LBP) histogram is then
applied to texture classification with the weighting scheme.
Experiment showed that the generated features from the proposed
fusion algorithm can improve the performance for verification system
through iris recognition.
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
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: 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: 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.