Abstract: A novel biologically inspired controller for the autonomous
navigation of a mobile robot in an evasion task is
proposed. The controller takes advantage of the environment by
calculating a measure of danger and subsequently choosing the
parameters of a reinforcement learning based decision process.
Two different reinforcement learning algorithms were used: Qlearning
and Sarsa (λ). Simulations show that selecting dynamic
parameters reduce the time while executing the decision making
process, so the robot can obtain a policy to succeed in an escaping
task in a realistic time.
Abstract: This paper deals with automatic sentence modality
recognition in French. In this work, only prosodic features are
considered. The sentences are recognized according to the three
following modalities: declarative, interrogative and exclamatory
sentences. This information will be used to animate a talking head for
deaf and hearing-impaired children. We first statistically study a real
radio corpus in order to assess the feasibility of the automatic
modeling of sentence types. Then, we test two sets of prosodic
features as well as two different classifiers and their combination. We
further focus our attention on questions recognition, as this modality
is certainly the most important one for the target application.
Abstract: This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
Abstract: This article is focused on the calculation of heat
radiation intensity and its optimization on an aluminum mould
surface. The inside of the mould is sprinkled with a special powder
and its outside is heated by infra heaters located above the mould
surface, up to a temperature of 250°C. By this way artificial leathers
in the car industry are produced (e. g. the artificial leather on a car
dashboard). A mathematical model of heat radiation of infra heaters
on a mould surface is described in this paper. This model allows us to
calculate a heat-intensity radiation on the mould surface for the
concrete location of infra heaters above the mould surface. It is
necessary to ensure approximately the same heat intensity radiation
on the mould surface by finding a suitable location for the infra
heaters, and in this way the same material structure and color of
artificial leather. In the model we have used a genetic algorithm to
optimize the radiation intensity on the mould surface. Experimental
measured values for the heat radiation intensity by a sensor in the
surroundings of an infra heater are used for the calculation
procedures. A computational procedure was programmed in language
Matlab.
Abstract: Artificial Neural Network (ANN)s can be modeled for
High Energy Particle analysis with special emphasis on shower core
location. The work describes the use of an ANN based system which
has been configured to predict locations of cores of showers in the
range 1010.5 to 1020.5 eV. The system receives density values as
inputs and generates coordinates of shower events recorded for values
captured by 20 core positions and 80 detectors in an area of 100
meters. Twenty ANNs are trained for the purpose and the positions
of shower events optimized by using cooperative ANN learning. The
results derived with variations of input upto 50% show success rates
in the range of 90s.
Abstract: To maximise furnace production it-s necessary to
optimise furnace control, with the objectives of achieving maximum
power input into the melting process, minimum network distortion
and power-off time, without compromise on quality and safety. This
can be achieved with on the one hand by an appropriate electrode
control and on the other hand by a minimum of AC transformer
switching.
Electrical arc is a stochastic process; witch is the principal cause
of power quality problems, including voltages dips, harmonic
distortion, unbalance loads and flicker. So it is difficult to make an
appropriate model for an Electrical Arc Furnace (EAF). The factors
that effect EAF operation are the melting or refining materials,
melting stage, electrode position (arc length), electrode arm control
and short circuit power of the feeder. So arc voltages, current and
power are defined as a nonlinear function of the arc length. In this
article we propose our own empirical function of the EAF and model,
for the mean stages of the melting process, thanks to the
measurements in the steel factory.
Abstract: Environmental impact assessment (EIA) is a procedure tool of environmental management for identifying, predicting, evaluating and mitigating the adverse effects of development proposals. EIA reports usually analyze how the amounts or concentrations of pollutants obey the relevant standards. Actually, many analytical tools can deepen the analysis of environmental impacts in EIA reports, such as life cycle assessment (LCA) and environmental risk assessment (ERA). Life cycle impact assessment (LCIA) is one of steps in LCA to introduce the causal relationships among environmental hazards and damage. Incorporating the LCIA concept into ERA as an integrated tool for EIA can extend the focus of the regulatory compliance of environmental impacts to determine of the significance of environmental impacts. Sometimes, when using integrated tools, it is necessary to consider fuzzy situations due to insufficient information; therefore, ERA should be generalized to fuzzy risk assessment (FRA). Finally, the use of the proposed methodology is demonstrated through the study case of the expansion plan of the world-s largest plastics processing factory.
Abstract: This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial
Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water
flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by
sensors to construct an empirical model for time series prediction and
classification of events. These two components have been installed,
tested and verified in an experimental site in a UK water distribution
system. Verification of the system has been achieved from a series of
simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network
management.
Abstract: The Learning Management Systems present learning
environment which offers a collection of e-learning tools in a
package that allows a common interface and information sharing
among the tools. South East European University initial experience
in LMS was with the usage of the commercial LMS-ANGEL. After a
three year experience on ANGEL usage because of expenses that
were very high it was decided to develop our own software. As part
of the research project team for the in-house design and development
of the new LMS, we primarily had to select the features that would
cover our needs and also comply with the actual trends in the area of
software development, and then design and develop the system. In
this paper we present the process of LMS in-house development for
South East European University, its architecture, conception and
strengths with a special accent on the process of migration and
integration with other enterprise applications.
Abstract: The present study has been taken to explore the
screening of in vitro antimicrobial activities of D-galactose-binding
sponge lectin (HOL-30). HOL-30 was purified from the marine
demosponge Halichondria okadai by affinity chromatography. The
molecular mass of the lectin was determined to be 30 kDa with a
single polypeptide by SDS-PAGE under non-reducing and reducing
conditions. HOL-30 agglutinated trypsinized and glutaraldehydefixed
rabbit and human erythrocytes with preference for type O
erythrocytes. The lectin was subjected to evaluation for inhibition of
microbial growth by the disc diffusion method against eleven human
pathogenic gram-positive and gram-negative bacteria. The lectin
exhibited strong antibacterial activity against gram-positive bacteria,
such as Bacillus megaterium and Bacillus subtilis. However, it did
not affect against gram-negative bacteria such as Salmonella typhi
and Escherichia coli. The largest zone of inhibition was recorded of
Bacillus megaterium (12 in diameter) and Bacillus subtilis (10 mm in
diameter) at a concentration of the lectin (250 μg/disc). On the other
hand, the antifungal activity of the lectin was investigated against six
phytopathogenic fungi based on food poisoning technique. The lectin
has shown maximum inhibition (22.83%) of mycelial growth of
Botrydiplodia theobromae at a concentration of 100 μg/mL media.
These findings indicate that the lectin may be of importance to
clinical microbiology and have therapeutic applications.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.
Abstract: Video Mosaicing is the stitching of selected frames of
a video by estimating the camera motion between the frames and
thereby registering successive frames of the video to arrive at the
mosaic. Different techniques have been proposed in the literature for
video mosaicing. Despite of the large number of papers dealing with
techniques to generate mosaic, only a few authors have investigated
conditions under which these techniques generate good estimate of
motion parameters. In this paper, these techniques are studied under
different videos, and the reasons for failures are found. We propose
algorithms with incorporation of outlier removal algorithms for better
estimation of motion parameters.
Abstract: Positron emission particle tracking (PEPT) is a
technique in which a single radioactive tracer particle can be
accurately tracked as it moves. A limitation of PET is that in order to
reconstruct a tomographic image it is necessary to acquire a large
volume of data (millions of events), so it is difficult to study rapidly
changing systems. By considering this fact, PEPT is a very fast
process compared with PET.
In PEPT detecting both photons defines a line and the annihilation
is assumed to have occurred somewhere along this line. The location
of the tracer can be determined to within a few mm from coincident
detection of a small number of pairs of back-to-back gamma rays and
using triangulation. This can be achieved many times per second and
the track of a moving particle can be reliably followed. This
technique was invented at the University of Birmingham [1].
The attempt in PEPT is not to form an image of the tracer particle
but simply to determine its location with time. If this tracer is
followed for a long enough period within a closed, circulating system
it explores all possible types of motion.
The application of PEPT to industrial process systems carried out
at the University of Birmingham is categorized in two subjects: the
behaviour of granular materials and viscous fluids. Granular
materials are processed in industry for example in the manufacture of
pharmaceuticals, ceramics, food, polymers and PEPT has been used
in a number of ways to study the behaviour of these systems [2].
PEPT allows the possibility of tracking a single particle within the
bed [3]. Also PEPT has been used for studying systems such as: fluid
flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer
particle [5].
Abstract: Vision based tracking problem is solved through a
combination of optical flow, MACH filter and log r-θ mapping.
Optical flow is used for detecting regions of movement in video
frames acquired under variable lighting conditions. The region of
movement is segmented and then searched for the target. A template
is used for target recognition on the segmented regions for detecting
the region of interest. The template is trained offline on a sequence of
target images that are created using the MACH filter and log r-θ
mapping. The template is applied on areas of movement in
successive frames and strong correlation is seen for in-class targets.
Correlation peaks above a certain threshold indicate the presence of
target and the target is tracked over successive frames.
Abstract: Characterized as rich mineral substances, low
temperature, few bacteria, and stability with numerous implementation
aspects on aquaculture, food, drinking, and leisure, the deep sea water
(DSW) development has become a new industry in the world. It has
been report that marine algae contain various biologically active
compounds. This research focued on the affections in cultivating
Sagrassum cristaefolium with different concentration of deep sea
water(DSW) and surface sea water(SSW). After two and four weeks,
the total phenolic contents were compared in Sagrassum cristaefolium
culturing with different ways, and the reductive activity of them was
also be tried with potassium ferricyanide. Those fresh seaweeds were
dried with oven and were ground to powder. Progressively, the marine
algae we cultured was extracted by water under the condition with
heating them at 90Ôäâ for 1hr.The total phenolic contents were be
executed using Folin–Ciocalteu method. The results were explaining
as follows: the highest total phenolic contents and the best reductive
ability of all could be observed on the 1/4 proportion of DSW to SSW
culturing in two weeks. Furthermore, the 1/2 proportion of DSW to
SSW also showed good reductive ability and plentiful phenolic
compositions. Finally, we confirmed that difference proportion of
DSW and SSW is the major point relating to ether the total phenolic
components or the reductive ability in the Sagrassum cristaefolium. In
the future, we will use this way to mass production the marine algae or
other micro algae on industry applications.
Abstract: The curves, of which the square of the distance
between the two points equal to zero, are called minimal or isotropic
curves [4]. In this work, first, necessary and sufficient conditions to
be a Pseudo Helix, which is a special case of such curves, are
presented. Thereafter, it is proven that an isotropic curve-s position
vector and pseudo curvature satisfy a vector differential equation of
fourth order. Additionally, In view of solution of mentioned
equation, position vector of pseudo helices is obtained.
Abstract: Mobile Ad hoc Networks is an autonomous system of
mobile nodes connected by multi-hop wireless links without
centralized infrastructure support. As mobile communication gains
popularity, the need for suitable ad hoc routing protocols will
continue to grow. Efficient dynamic routing is an important research
challenge in such a network. Bandwidth constrained mobile devices
use on-demand approach in their routing protocols because of its
effectiveness and efficiency. Many researchers have conducted
numerous simulations for comparing the performance of these
protocols under varying conditions and constraints. Most of them are
not aware of MAC Protocols, which will impact the relative
performance of routing protocols considered in different network
scenarios. In this paper we investigate the choice of MAC protocols
affects the relative performance of ad hoc routing protocols under
different scenarios. We have evaluated the performance of these
protocols using NS2 simulations. Our results show that the
performance of routing protocols of ad hoc networks will suffer when
run over different MAC Layer protocols.
Abstract: This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.
Abstract: The goal of this work is to describe a new algorithm for finding the optimal variable order, number of nodes for any order and other ROBDD parameters, based on a tabular method. The tabular method makes use of a pre-built backend database table that stores the ROBDD size for selected combinations of min-terms. The user uses the backend table and the proposed algorithm to find the necessary ROBDD parameters, such as best variable order, number of nodes etc. Experimental results on benchmarks are given for this technique.
Abstract: This paper describes the designs of a first and second
generation autonomous gas monitoring system and the successful
field trial of the final system (2nd generation). Infrared sensing
technology is used to detect and measure the greenhouse gases
methane (CH4) and carbon dioxide (CO2) at point sources. The
ability to monitor real-time events is further enhanced through the
implementation of both GSM and Bluetooth technologies to
communicate these data in real-time. These systems are robust,
reliable and a necessary tool where the monitoring of gas events in
real-time are needed.