Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Abstract: This paper shows the potential system benefits of
simple tracking solar system using a stepper motor and light sensor.
This method is increasing power collection efficiency by developing
a device that tracks the sun to keep the panel at a right angle to its
rays. A solar tracking system is designed, implemented and
experimentally tested. The design details and the experimental results
are shown.
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: Hair is a non homogenous complex material which
can be associated with a polymer. It is made up 95% of Keratin.
Hair has a great social significance for human beings. In the High
Middle Ages, for example, long hairs have been reserved for kings
and nobles.
Most common interest in hair is focused on hair growth, hair types
and hair care, but hair is also an important biomaterial which can
vary depending on ethnic origin or on age, hair colour for example
can be a sign of ethnic ancestry or age (dark hair for Asiatic, blond
hair for Caucasian and white hair for old people in general).
In this context, different approaches have been conducted to
determine the differences in mechanical properties and characterize
the fracture topography at the surface of hair depending on its type
and its age.
A tensile testing machine was especially designed to achieve
tensile tests on hair. This device is composed of a microdisplacement
system and a force sensor whose peak load is limited to
3N. The curves and the values extracted from each experiment, allow
us to compare the evolution of the mechanical properties from one
hair to another.
Observations with a Scanning Electron Microscope (SEM) and
with an interferometer were made on different hairs. Thus, it is
possible to access the cuticle state and the fracture topography for
each category.
Abstract: A measurement system for pH array sensors is
introduced to increase accuracy, and decrease non-ideal effects
successfully. An array readout circuit reads eight potentiometric
signals at the same time, and obtains an average value. The deviation
value or the extreme value is counteracted and the output voltage is a
relatively stable value. The errors of measuring pH buffer solutions are
decreased obviously with this measurement system, and the non-ideal
effects, drift and hysteresis, are lowered to 1.638mV/hr and 1.118mV,
respectively. The efficiency and stability are better than single sensor.
The whole sensing characteristics are improved.
Abstract: Fundamental sensor-motor couplings form the backbone
of most mobile robot control tasks, and often need to be implemented
fast, efficiently and nevertheless reliably. Machine learning
techniques are therefore often used to obtain the desired sensor-motor
competences.
In this paper we present an alternative to established machine
learning methods such as artificial neural networks, that is very fast,
easy to implement, and has the distinct advantage that it generates
transparent, analysable sensor-motor couplings: system identification
through nonlinear polynomial mapping.
This work, which is part of the RobotMODIC project at the
universities of Essex and Sheffield, aims to develop a theoretical understanding
of the interaction between the robot and its environment.
One of the purposes of this research is to enable the principled design
of robot control programs.
As a first step towards this aim we model the behaviour of the
robot, as this emerges from its interaction with the environment, with
the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving
Average models with eXogenous inputs). This method produces
explicit polynomial functions that can be subsequently analysed using
established mathematical methods.
In this paper we demonstrate the fidelity of the obtained NARMAX
models in the challenging task of robot route learning; we present a
set of experiments in which a Magellan Pro mobile robot was taught
to follow four different routes, always using the same mechanism to
obtain the required control law.
Abstract: In this paper authors presented the research of textile electroconductive materials, which can be used to construction
sensory textronic shirt to breath frequency measurement.
The full paper also will present results of measurements carried
out on unique measurement stands.
Abstract: Lately, an interest has grown greatly in the usages of
RFID in an un-presidential applications. It is shown in the adaptation
of major software companies such as Microsoft, IBM, and Oracle
the RFID capabilities in their major software products. For example
Microsoft SharePoints 2010 workflow is now fully compatible with
RFID platform. In addition, Microsoft BizTalk server is also capable
of all RFID sensors data acquisition. This will lead to applications
that required high bit rate, long range and a multimedia content in
nature. Higher frequencies of operation have been designated for
RFID tags, among them are the 2.45 and 5.8 GHz. The higher the
frequency means higher range, and higher bit rate, but the drawback
is the greater cost. In this paper we present a single layer, low
profile patch antenna operates at 5.8 GHz with pure resistive input
impedance of 50 and close to directive radiation. Also, we propose
a modification to the design in order to improve the operation band
width from 8.7 to 13.8
Abstract: In this paper we propose an intelligent agent approach
to control the electric power grid at a smaller granularity in order to
give it self-healing capabilities. We develop a method using the
influence model to transform transmission substations into
information processing, analyzing and decision making (intelligent
behavior) units. We also develop a wireless communication method
to deliver real-time uncorrupted information to an intelligent
controller in a power system environment. A combined networking
and information theoretic approach is adopted in meeting both the
delay and error probability requirements. We use a mobile agent
approach in optimizing the achievable information rate vector and in
the distribution of rates to users (sensors). We developed the concept
and the quantitative tools require in the creation of cooperating semiautonomous
subsystems which puts the electric grid on the path
towards intelligent and self-healing system.
Abstract: We propose an enhanced key management scheme
based on Key Infection, which is lightweight scheme for tiny sensors.
The basic scheme, Key Infection, is perfectly secure against node
capture and eavesdropping if initial communications after node
deployment is secure. If, however, an attacker can eavesdrop on
the initial communications, they can take the session key. We use
common neighbors for each node to generate the session key. Each
node has own secret key and shares it with its neighbor nodes. Then
each node can establish the session key using common neighbors-
secret keys and a random number. Our scheme needs only a few
communications even if it uses neighbor nodes- information. Without
losing the lightness of basic scheme, it improves the resistance against
eavesdropping on the initial communications more than 30%.
Abstract: Task of object localization is one of the major
challenges in creating intelligent transportation. Unfortunately, in
densely built-up urban areas, localization based on GPS only
produces a large error, or simply becomes impossible. New
opportunities arise for the localization due to the rapidly emerging
concept of a wireless ad-hoc network. Such network, allows
estimating potential distance between these objects measuring
received signal level and construct a graph of distances in which
nodes are the localization objects, and edges - estimates of the
distances between pairs of nodes. Due to the known coordinates of
individual nodes (anchors), it is possible to determine the location of
all (or part) of the remaining nodes of the graph. Moreover, road
map, available in digital format can provide localization routines
with valuable additional information to narrow node location search.
However, despite abundance of well-known algorithms for solving
the problem of localization and significant research efforts, there are
still many issues that currently are addressed only partially. In this
paper, we propose localization approach based on the graph mapped
distances on the digital road map data basis. In fact, problem is
reduced to distance graph embedding into the graph representing area
geo location data. It makes possible to localize objects, in some cases
even if only one reference point is available. We propose simple
embedding algorithm and sample implementation as spatial queries
over sensor network data stored in spatial database, allowing
employing effectively spatial indexing, optimized spatial search
routines and geometry functions.
Abstract: We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Abstract: One of the most important applications of
wireless sensor networks is data collection. This paper
proposes as efficient approach for data collection in wireless
sensor networks by introducing Member Forward List. This list
includes the nodes with highest priority for forwarding the data.
When a node fails or dies, this list is used to select the next node
with higher priority. The benefit of this node is that it prevents
the algorithm from repeating when a node fails or dies. The
results show that Member Forward List decreases power
consumption and latency in wireless sensor networks.
Abstract: Existing ground movement surveillance technologies
at airports are subjected to limitations due to shadowing effects or
multiple reflections. Therefore, there is a strong demand for a new
sensing technology, which will be cost effective and will provide
detection of non-cooperative targets under any weather conditions.
This paper aims to present a new intelligent system, developed
within the framework of the EC-funded ISMAEL project, which is
based on a new magnetic sensing technology and provides detection,
tracking and automatic classification of targets moving on the airport
surface. The system is currently being installed at two European
airports. Initial experimental results under real airport traffic
demonstrate the great potential of the proposed system.
Abstract: Many Wireless Sensor Network (WSN) applications necessitate secure multicast services for the purpose of broadcasting delay sensitive data like video files and live telecast at fixed time-slot. This work provides a novel method to deal with end-to-end delay and drop rate of packets. Opportunistic Routing chooses a link based on the maximum probability of packet delivery ratio. Null Key Generation helps in authenticating packets to the receiver. Markov Decision Process based Adaptive Scheduling algorithm determines the time slot for packet transmission. Both theoretical analysis and simulation results show that the proposed protocol ensures better performance in terms of packet delivery ratio, average end-to-end delay and normalized routing overhead.
Abstract: This paper reports on a receding horizon filtering for
mobile robot systems with cross-correlated sensor noises and
uncertainties. Also, the effect of uncertain parameters in the state of
the tracking error model performance is considered. A distributed
fusion receding horizon filter is proposed. The distributed fusion
filtering algorithm represents the optimal linear combination of the
local filters under the minimum mean square error criterion. The
derivation of the error cross-covariances between the local receding
horizon filters is the key of this paper. Simulation results of the
tracking mobile robot-s motion demonstrate high accuracy and
computational efficiency of the distributed fusion receding horizon
filter.
Abstract: Wireless Sensor Networks (WSN) are emerging
because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure,
motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the
MAC protocols used in wireless Adhoc networks to WSN, simulation
experiments were conducted in Global Mobile Simulator
(GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy
spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.
Abstract: The aim of this study is to develop a cost-effective WBGT heat stress monitor which provides precise heat stress measurement. The proposed device employs SHT15 and DS18B20 as a temperature and humidity sensors, respectively, incorporating with ATmega328 microcontroller. The developed heat stress monitor was calibrated and adjusted to that of the standard temperature and humidity sensors in the laboratory. The results of this study illustrated that the mean percentage error and the standard deviation from the measurement of the globe temperature was 2.33 and 2.71 respectively, while 0.94 and 1.02 were those of the dry bulb temperature, 0.79 and 0.48 were of the wet bulb temperature, and 4.46 and 1.60 were of the relative humidity sensor. This device is relatively low-cost and the measurement error is acceptable.
Abstract: Yogurts are prepared by fermenting milk with bacterial cultures consisting of a mixture of Streptococcus ssp. thermophilus and Lactobacillus delbrueckii ssp. bulgaricus. The main aim of this investigation was to develop a majority goat yogurt, with the addition of sheep milk in order to have a final product with good physicochemical quality properties and sensorial attributes. Four types of yogurts were prepared presenting the following proportion of goat and sheep milk respectively: C100 – 100%; C80 – 80%/20%; C60 – 60%/40%; C50 – 50%/50%. The goat milk was from the Serrana Jarmelista breed and the sheep milk from the Serra da Estrela breed. The inclusion of sheep milk improved attractiveness to consumers, and it also improved the nutritional value of the product, mainly the fatty acid and mineral contents. The C50 yogurt was preferred by 28% of the panellists, followed by the C100 with 16% and the commercial cow yogurt was 40% of preferences.