Abstract: The Portuguese Constitution, in article 22, instituted
the general principle of tort liability of the State and other public law
entities.
Consequently, ordinary legislation established the tort liability of
the State into the Portuguese Legal Order, by means of Decree-Law
48051, of 1967.
This decree, which was criticised extensively, was amended by
virtue of Law 67/2007, of 31st December, establishing the regime for
tort liability arising from losses caused by third parties, due to the
acts of public management in relation to all the functions of the State,
i.e. i) administrative, ii) legislative, and iii) jurisdictional.
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: Based on Traub-s methods for solving nonlinear
equation f(x) = 0, we develop two families of third-order
methods for solving system of nonlinear equations F(x) = 0. The
families include well-known existing methods as special cases.
The stability is corroborated by numerical results. Comparison
with well-known methods shows that the present methods are
robust. These higher order methods may be very useful in the
numerical applications requiring high precision in their computations
because these methods yield a clear reduction in number of iterations.
Abstract: In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
Abstract: Ethanol has been known for a long time, being
perhaps the oldest product obtained through traditional biotechnology
fermentation. Agriculture waste as substrate in fermentation is vastly
discussed as alternative to replace edible food and utilization of
organic material. Pineapple peel, highly potential source as substrate
is a by-product of the pineapple processing industry. Bio-ethanol
from pineapple (Ananas comosus) peel extract was carried out by
controlling fermentation without any treatment. Saccharomyces
ellipsoides was used as inoculum in this fermentation process as it is
naturally found at the pineapple skin. In this study, the capability of
Response Surface Methodology (RSM) for optimization of ethanol
production from pineapple peel extract using Saccharomyces
ellipsoideus in batch fermentation process was investigated. Effect of
five test variables in a defined range of inoculum concentration 6-
14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix),
temperature (24-32°C) and time of incubation (30-54 hrs) on the
ethanol production were evaluated. Data obtained from experiment
were analyzed with RSM of MINITAB Software (Version 15)
whereby optimum ethanol concentration of 8.637% (v/v) was
determined. The optimum condition of 14% (v/v) inoculum
concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The
significant regression equation or model at the 5% level with
correlation value of 99.96% was also obtained.
Abstract: In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces
Abstract: The paper describes the evaluation of quality of
control for cases of controlled non-minimal phase plants. Control
circuits containing non-minimal phase plants have different
properties, they manifest reversed reaction at the beginning of unit
step response. For these types of plants are developed special
criterion of quality of control, which considers the difference and can
be helpful for synthesis of optimal controller tuning. All results are
clearly presented using Matlab/Simulink models.
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: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).
Abstract: Using the animations video of teaching materials is an
effective learning method. However, we thought that more effective learning method is to produce the teaching video by learners
themselves. The learners who act as the producer must learn and understand well to produce and present video of teaching materials to
others. The purpose of this study is to propose the project based learning (PBL) technique by co-producing video of IT (information
technology) teaching materials. We used the T2V player to produce
the video based on TVML a TV program description language. By
proposed method, we have assigned the learners to produce the
animations video for “National Examination for Information
Processing Technicians (IPA examination)" in Japan, in order to get
them learns various knowledge and skill on IT field. Experimental
result showed that learning effect has occurred at the video production
process that useful for IT personnel resources development.
Abstract: In a bi-fuel diesel engine, the carburetor plays a vital
role in switching from fuel gas to petrol mode operation and viceversa.
The carburetor is the most important part of the fuel system of
a diesel engine. All diesel engines carry variable venturi mixer
carburetors. The basic operation of the carburetor mainly depends on
the restriction barrel called the venturi. When air flows through the
venturi, its speed increases and its pressure decreases. The main
challenge focuses on designing a mixing device which mixes the
supplied gas is the incoming air at an optimum ratio. In order to
surmount the identified problems, the way fuel gas and air flow in
the mixer have to be analyzed. In this case, the Computational Fluid
Dynamics or CFD approach is applied in design of the prototype
mixer. The present work is aimed at further understanding of the air
and fuel flow structure by performing CFD studies using a software
code. In this study for mixing air and gas in the condition that has
been mentioned in continuance, some mixers have been designed.
Then using of computational fluid dynamics, the optimum mixer has
been selected. The results indicated that mixer with 12 holes can
produce a homogenous mixture than those of 8-holes and 6-holes
mixer. Also the result showed that if inlet convergency was smoother
than outlet divergency, the mixture get more homogenous, the reason
of that is in increasing turbulence in outlet divergency.
Abstract: Vapour recompression system has been used to
enhance reduction in energy consumption and improvement in
energy effectiveness of distillation columns. However, the effects of
certain parameters have not been taken into consideration. One of
such parameters is the column heat loss which has either been
assumed to be a certain percent of reboiler heat transfer or negligible.
The purpose of this study was to evaluate the heat loss from an
ethanol-water vapour recompression distillation column with
pressure increase across the compressor (VRCAS) and compare the
results obtained and its effect on some parameters in similar system
(VRCCS) where the column heat loss has been assumed or neglected.
Results show that the heat loss evaluated was higher when compared
with that obtained for the column VRCCS. The results also showed
that increase in heat loss could have significant effect on the total
energy consumption, reboiler heat transfer, the number of trays and
energy effectiveness of the column.
Abstract: The excessive consumption of fossil energies (electrical energy) during summer caused by the technological development involves more and more climate warming.
In order to reduce the worst impact of gas emissions produced from classical air conditioning, heat driven solar absorption chiller is pretty promising; it consists on using solar as motive energy which is clean and environmentally friendly to provide cold.
Solar absorption machine is composed by four components using Lithium Bromide /water as a refrigerating couple. LiBr- water is the most promising in chiller applications due to high safety, high volatility ratio, high affinity, high stability and its high latent heat. The lithium bromide solution is constitute by the salt lithium bromide which absorbs water under certain conditions of pressure and temperature however if the concentration of the solution is high in the absorption chillers; which exceed 70%, the solution will crystallize.
The main aim of this article is to study the phenomena of the crystallization and to evaluate how the dependence between the electric conductivity and the concentration which should be controlled.
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: Most paddy rice fields in East Asia are small parcels,
and the weather conditions during the growing season are usually
cloudy. FORMOSAT-2 multi-spectral images have an 8-meter
resolution and one-day recurrence, ideal for mapping paddy rice fields
in East Asia. To map rice fields, this study first determined the
transplanting and the most active tillering stages of paddy rice and
then used multi-temporal images to distinguish different growing
characteristics between paddy rice and other ground covers. The
unsupervised ISODATA (iterative self-organizing data analysis
techniques) and supervised maximum likelihood were both used to
discriminate paddy rice fields, with training areas automatically
derived from ten-year cultivation parcels in Taiwan. Besides original
bands in multi-spectral images, we also generated normalized
difference vegetation index and experimented with object-based
pre-classification and post-classification. This paper discusses results
of different image classification methods in an attempt to find a
precise and automatic solution to mapping paddy rice in Taiwan.
Abstract: The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.
Abstract: Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.
Abstract: Traffic density, an indicator of traffic
conditions, is one of the most critical characteristics to
Intelligent Transport Systems (ITS). This paper investigates
recursive traffic density estimation using the information
provided from inductive loop detectors. On the basis of the
phenomenological relationship between speed and density, the
existing studies incorporate a state space model and update the
density estimate using vehicular speed observations via the
extended Kalman filter, where an approximation is made
because of the linearization of the nonlinear observation
equation. In practice, this may lead to substantial estimation
errors. This paper incorporates a suitable transformation to
deal with the nonlinear observation equation so that the
approximation is avoided when using Kalman filter to
estimate the traffic density. A numerical study is conducted. It
is shown that the developed method outperforms the existing
methods for traffic density estimation.
Abstract: An electronic portal image device (EPID) has become
a method of patient-specific IMRT dose verification for radiotherapy.
Research studies have focused on pre and post-treatment verification,
however, there are currently no interventional procedures using EPID
dosimetry that measure the dose in real time as a mechanism to
ensure that overdoses do not occur and underdoses are detected as
soon as is practically possible. As a result, an EPID-based real time
dose verification system for dynamic IMRT was developed and was
implemented with MATLAB/Simulink. The EPID image acquisition
was set to continuous acquisition mode at 1.4 images per second. The
system defined the time constraint gap, or execution gap at the image
acquisition time, so that every calculation must be completed before
the next image capture is completed. In addition, the