Abstract: The lifelong learning is a crucial element in the
modernization of European education and training systems. The most
important actors in the development process of the lifelong learning
are the trainers, whose professional characteristics need new
competences and skills in the current labour market. The main
objective of this paper is to establish an importance ranking of the
new competences, capabilities and skills that the lifelong learning
Spanish trainers must possess nowadays. A wide study of secondary
sources has allowed the design of a questionnaire that organizes the
trainer-s skills and competences. The e-Delphi method is used for
realizing a creative, individual and anonymous evaluation by experts
on the importance ranking that presents the criteria, sub-criteria and
indicators of the e-Delphi questionnaire. Twenty Spanish experts in
the lifelong learning have participated in two rounds of the e-
DELPHI method. In the first round, the analysis of the experts-
evaluation has allowed to establish the ranking of the most
importance criteria, sub-criteria and indicators and to eliminate the
least valued. The minimum level necessary to reach the consensus
among experts has been achieved in the second round.
Abstract: In this paper, a new K-means clustering based
approach for identification of voltage control areas is developed.
Voltage control areas are important for efficient reactive power
management in power systems operating under deregulated
environment. Although, voltage control areas are formed using
conventional hierarchical clustering based method, but the present
paper investigate the capability of K-means clustering for the
purpose of forming voltage control areas. The proposed method is
tested and compared for IEEE 14 bus and IEEE 30 bus systems. The
results show that this K-means based method is competing with
conventional hierarchical approach
Abstract: Multi-agent system is composed by several agents
capable of reaching the goal cooperatively. The system needs an agent
platform for efficient and stable interaction between intelligent agents.
In this paper we propose a flexible and scalable agent platform by
composing the containers with multiple hierarchical agent groups. It
also allows efficient implementation of multiple domain presentations
of the agents unlike JADE. The proposed platform provides both
group management and individual management of agents for
efficiency. The platform has been implemented and tested, and it can
be used as a flexible foundation of the dynamic multi-agent system
targeting seamless delivery of ubiquitous services.
Abstract: Hepatitis C is an infectious disease transmitted by
blood and due to hepatitis C virus (HCV), which attacks the liver.
The infection is characterized by liver inflammation (hepatitis) that is
often asymptomatic but can progress to chronic hepatitis and later
cirrhosis and liver cancer. Our problem tends to highlight on the one
hand the prevalence of infectious disease in the population of the
region of Batna and on other hand the biological characteristics of
this disease by a screening and a specific diagnosis based on
serological tests, liver checkup (measurement of haematological and
biochemical parameters).
The results showed:
The serology of hepatitis C establishes the diagnosis of infection
with hepatitis C. In this study and with the serological test, 24 cases
of the disease of hepatitis C were found in 1000 suspected cases (7
cases with normal transaminases and 17 cases with elevated
transaminases). The prevalence of this disease in this study
population was 2.4%.
The presence of hepatitis C disrupts liver function including the
onset of cytolysis, cholestasis, jaundice, thrombocytopenia, and
coagulation disorders.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: The mineral having chemical compositional formula MgAl2O4 is called “spinel". The ferrites crystallize in spinel structure are known as spinel-ferrites or ferro-spinels. The spinel structure has a fcc cage of oxygen ions and the metallic cations are distributed among tetrahedral (A) and octahedral (B) interstitial voids (sites). The X-ray diffraction (XRD) intensity of each Bragg plane is sensitive to the distribution of cations in the interstitial voids of the spinel lattice. This leads to the method of determination of distribution of cations in the spinel oxides through XRD intensity analysis. The computer program for XRD intensity analysis has been developed in C language and also tested for the real experimental situation by synthesizing the spinel ferrite materials Mg0.6Zn0.4AlxFe2- xO4 and characterized them by X-ray diffractometry. The compositions of Mg0.6Zn0.4AlxFe2-xO4(x = 0.0 to 0.6) ferrites have been prepared by ceramic method and powder X-ray diffraction patterns were recorded. Thus, the authenticity of the program is checked by comparing the theoretically calculated data using computer simulation with the experimental ones. Further, the deduced cation distributions were used to fit the magnetization data using Localized canting of spins approach to explain the “recovery" of collinear spin structure due to Al3+ - substitution in Mg-Zn ferrites which is the case if A-site magnetic dilution and non-collinear spin structure. Since the distribution of cations in the spinel ferrites plays a very important role with regard to their electrical and magnetic properties, it is essential to determine the cation distribution in spinel lattice.
Abstract: A microchannel with two inlets and two outlets was tested as a potential reactor to carry out two-phase catalytic phase transfer reaction with phase separation at the exit of the microchannel. The catalytic phase transfer reaction between benzyl chloride and sodium sulfide was chosen as a model reaction. The effect of operational time on the conversion was studied. By utilizing a multiphase parallel flow inside the microchannel reactor with the aid of a guideline structure, the catalytic phase reaction followed by phase separation could be ensured. The organic phase could be separated completely from one exit and part of the aqueous phase was separated purely and could be reused with slightly affecting the catalytic phase transfer reaction.
Abstract: Efficient preprocessing is very essential for automatic
recognition of handwritten documents. In this paper, techniques on
segmenting words in handwritten Arabic text are presented. Firstly,
connected components (ccs) are extracted, and distances among
different components are analyzed. The statistical distribution of this
distance is then obtained to determine an optimal threshold for words
segmentation. Meanwhile, an improved projection based method is
also employed for baseline detection. The proposed method has been
successfully tested on IFN/ENIT database consisting of 26459
Arabic words handwritten by 411 different writers, and the results
were promising and very encouraging in more accurate detection of
the baseline and segmentation of words for further recognition.
Abstract: The aim of this paper is to investigate the influence of
market share and diversification on the nonlife insurers- performance.
The underlying relationships have been investigated in different
industries and different disciplines (economics, management...), still,
no consistency exists either in the magnitude or statistical
significance of the relationship between market share (and
diversification as well) on one side and companies- performance on
the other side. Moreover, the direction of the relationship is also
somewhat questionable. While some authors find this relationship to
be positive, the others reveal its negative association. In order to test
the influence of market share and diversification on companies-
performance in Croatian nonlife insurance industry for the period
from 1999 to 2009, we designed an empirical model in which we
included the following independent variables: firms- profitability
from previous years, market share, diversification and control
variables (i.e. ownership, industrial concentration, GDP per capita,
inflation). Using the two-step generalized method of moments
(GMM) estimator we found evidence of a positive and statistically
significant influence of both, market share and diversification, on
insurers- profitability.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of ANN is used. The designed neural network can predict the natural gas viscosity using pseudo-reduced pressure and pseudo-reduced temperature with AARD% of 0.221. The accuracy of designed ANN has been compared to other published empirical models. The comparison indicates that the proposed method can provide accurate results.
Abstract: In this paper discrete choice models, Logit and Probit
are examined in order to predict the economic recession or expansion
periods in USA. Additionally we propose an adaptive neuro-fuzzy
inference system with triangular membership function. We examine
the in-sample period 1947-2005 and we test the models in the out-of
sample period 2006-2009. The forecasting results indicate that the
Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms
significant the Logit and Probit models in the out-of sample period.
This indicates that neuro-fuzzy model provides a better and more
reliable signal on whether or not a financial crisis will take place.
Abstract: A spectrophotometric method was developed for simultaneous quantification of pseudoephedrine hydrochloride (PSE) triprolidine hydrochloride (TRI) using second derivative method (zero-crossing technique). The second derivative amplitudes of PSE and TRI were measured at 271 and 321 nm, respectively. The calibration curves were linear in the range of 200 to 1,000 g/ml for PSE and 10 to 50 g/ml for TRI. The method was validated for specificity, accuracy, precision, limit of detection and limit of quantitation. The proposed method was applied to the assaying and dissolution of PSE and TRI in commercial tablets without any chemical separation. The results were compared with those obtained by the official USP31 method and statistical tests showed that there is no significant between the methods at 95% confidence level. The proposed method is simple, rapid and suitable for the routine quality control application. KeywordsTriprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.
Abstract: In this paper delamination phenomenon in
Carbon-Epoxy laminated composite material is investigated
numerically. Arcan apparatus and specimen is modeled in ABAQUS
finite element software for different loading conditions and crack
geometries. The influence of variation of crack geometry on
interlaminar fracture stress intensity factor and energy release rate for
various mixed mode ratios and pure mode I and II was studied. Also,
correction factors for this specimen for different crack length ratios
were calculated. The finite element results indicate that for loading
angles close to pure mode-II loading, a high ratio of mode-II to
mode-I fracture is dominant and there is an opposite trend for loading
angles close to pure mode-I loading. It confirms that by varying the
loading angle of Arcan specimen pure mode-I, pure mode-II and a
wide range of mixed-mode loading conditions can be created and
tested. Also, numerical results confirm that the increase of the mode-
II loading contribution leads to an increase of fracture resistance in
the CF/PEI composite (i.e., a reduction in the total strain energy
release rate) and the increase of the crack length leads to a reduction
of interlaminar fracture resistance in the CF/PEI composite (i.e., an
increase in the total interlaminar strain energy release rate).
Abstract: This paper proposes a hybrid method for eyes localization
in facial images. The novelty is in combining techniques
that utilise colour, edge and illumination cues to improve accuracy.
The method is based on the observation that eye regions have dark
colour, high density of edges and low illumination as compared
to other parts of face. The first step in the method is to extract
connected regions from facial images using colour, edge density and
illumination cues separately. Some of the regions are then removed
by applying rules that are based on the general geometry and shape
of eyes. The remaining connected regions obtained through these
three cues are then combined in a systematic way to enhance the
identification of the candidate regions for the eyes. The geometry
and shape based rules are then applied again to further remove the
false eye regions. The proposed method was tested using images from
the PICS facial images database. The proposed method has 93.7%
and 87% accuracies for initial blobs extraction and final eye detection
respectively.
Abstract: The paper gives the pilot results of the project that is
oriented on the use of data mining techniques and knowledge
discoveries from production systems through them. They have been
used in the management of these systems. The simulation models of
manufacturing systems have been developed to obtain the necessary
data about production. The authors have developed the way of
storing data obtained from the simulation models in the data
warehouse. Data mining model has been created by using specific
methods and selected techniques for defined problems of production
system management. The new knowledge has been applied to
production management system. Gained knowledge has been tested
on simulation models of the production system. An important benefit
of the project has been proposal of the new methodology. This
methodology is focused on data mining from the databases that store
operational data about the production process.
Abstract: Process capability index Cpk is the most widely
used index in making managerial decisions since it provides bounds
on the process yield for normally distributed processes. However,
existent methods for assessing process performance which
constructed by statistical inference may unfortunately lead to fine
results, because uncertainties exist in most real-world applications.
Thus, this study adopts fuzzy inference to deal with testing of Cpk .
A brief score is obtained for assessing a supplier’s process instead of
a severe evaluation.
Abstract: A mammography image is composed of low contrast area where the breast tissues and the breast abnormalities such as microcalcification can hardly be differentiated by the medical practitioner. This paper presents the application of active contour models (Snakes) for the segmentation of microcalcification in mammography images. Comparison on the microcalcifiation areas segmented by the Balloon Snake, Gradient Vector Flow (GVF) Snake, and Distance Snake is done against the true value of the microcalcification area. The true area value is the average microcalcification area in the original mammography image traced by the expert radiologists. From fifty images tested, the result obtained shows that the accuracy of the Balloon Snake, GVF Snake, and Distance Snake in segmenting boundaries of microcalcification are 96.01%, 95.74%, and 95.70% accuracy respectively. This implies that the Balloon Snake is a better segmentation method to locate the exact boundary of a microcalcification region.
Abstract: A total of fourteen slab-edge beam-column connection specimens were tested gradually to failure under the effect of simultaneous action of shear force and moment. The objective was to investigate the influence of some parameters thought to be important on the behavior and strength of slab-column connections with edge beams encountered in flat slab flooring and roofing systems. The parameters included the existence and strength of edge beam, depth and width of edge beam, steel reinforcement ratio of slab, ratio of moment to shear force, and the existence of openings in the region next to the column.
Results obtained demonstrated the importance of the studied parameters on the strength and behavior of slab-column connections with edge beams.
Abstract: This paper describes the design of a programmable
FSK-modulator based on VCO and its implementation in 0.35m
CMOS process. The circuit is used to transmit digital data at
100Kbps rate in the frequency range of 400-600MHz. The design
and operation of the modulator is discussed briefly. Further the
characteristics of PLL, frequency synthesizer, VCO and the whole
design are elaborated. The variation among the proposed and tested
specifications is presented. Finally, the layout of sub-modules, pin
configurations, final chip and test results are presented.