Abstract: The present paper aims to present the significant role that the concept of governance can play in order to combine naturals resources as useful funding basis for the formation of a stable and effective welfare state model. The combination of those two different fields aims to represent the modern trends of our era as the means to solve the severe financial and economic issues caused mostly due to the malfunction of the welfare state and its public sector. European Union and Asian countries (especially China) are the main areas of interest since EU experiences a fiscal and economic crisis while China rules the area of the natural resources exploiting 97% of rare earths elements worldwide.
Abstract: Recently, grid computing has been widely focused on
the science, industry, and business fields, which are required a vast
amount of computing. Grid computing is to provide the environment
that many nodes (i.e., many computers) are connected with each
other through a local/global network and it is available for many
users. In the environment, to achieve data processing among nodes
for any applications, each node executes mutual authentication by
using certificates which published from the Certificate Authority
(for short, CA). However, if a failure or fault has occurred in the
CA, any new certificates cannot be published from the CA. As
a result, a new node cannot participate in the gird environment.
In this paper, an off-the-shelf scheme for dependable grid systems
using virtualization techniques is proposed and its implementation is
verified. The proposed approach using the virtualization techniques
is to restart an application, e.g., the CA, if it has failed. The system
can tolerate a failure or fault if it has occurred in the CA. Since
the proposed scheme is implemented at the application level easily,
the cost of its implementation by the system builder hardly takes
compared it with other methods. Simulation results show that the
CA in the system can recover from its failure or fault.
Abstract: The increasing interest in plant sterol enriched foods
is due to the fact that they reduce blood cholesterol concentrations
without adverse side effects. In this context, enriched foods with
phytosterols may be helpful in protecting population against
atherosclerosis and cardiovascular diseases. The aim of the present
work was to evaluate in a population of Viseu, Portugal, the
consumption habits low-fat, plant sterol-enriched yoghurt. For this
study, 577 inquiries were made and the sample was randomly
selected for people shopping in various supermarkets. The
preliminary results showed that the biggest consumers of these
products were women aged 45 to 65 years old. Most of the people
who claimed to buy these products consumed them once a day. Also,
most of the consumers under antidyslipidemic therapeutics noticed
positive effects on hypercholesterolemia.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: Current OCR technology does not allow to
accurately recognizing small text images, such as those found
in web images. Our goal is to investigate new approaches to
recognize very low resolution text images containing antialiased
character shapes.
This paper presents a preliminary study on the variability of
such characters and the feasibility to discriminate them by
using geometrical features. In a first stage we analyze the
distribution of these features. In a second stage we present a
study on the discriminative power for recognizing isolated
characters, using various rendering methods and font
properties. Finally we present interesting results of our
evaluation tests leading to our conclusion and future focus.
Abstract: Food safety is an important concern for holiday
makers in foreign and unfamiliar tourist destinations. In fact, risk
from food in these tourist destinations has an influence on tourist
perception. This risk can potentially affect physical health and lead to
an inability to pursue planned activities. The objective of this paper
was to compare foreign tourists- demographics including gender, age
and education level, with the level of perceived risk towards food
safety. A total of 222 foreign tourists during their stay at Khao San
Road in Bangkok were used as the sample. Independent- samples ttest,
analysis of variance, and Least Significant Difference or LSD
post hoc test were utilized. The findings revealed that there were few
demographic differences in level of perceived risk among the foreign
tourists. The post hoc test indicated a significant difference among
the old and the young tourists, and between the higher and lower
level of education. Ranks of tourists- perceived risk towards food
safety unveiled some interesting results. Tourists- perceived risk of
food safety in established restaurants can be ranked as i) cleanliness
of dining utensils, ii) sanitation of food preparation area, and iii)
cleanliness of food seasoning and ingredients. Whereas, the tourists-
perceived risk of food safety in street food and drink can be ranked
as i) cleanliness of stalls and pushcarts, ii) cleanliness of food sold,
and iii) personal hygiene of street food hawkers or vendors.
Abstract: Although face recognition seems as an easy task for
human, automatic face recognition is a much more challenging task
due to variations in time, illumination and pose. In this paper, the
influence of time-lapse on visible and thermal images is examined.
Orthogonal moment invariants are used as a feature extractor to
analyze the effect of time-lapse on thermal and visible images and the
results are compared with conventional Principal Component
Analysis (PCA). A new triangle square ratio criterion is employed
instead of Euclidean distance to enhance the performance of nearest
neighbor classifier. The results of this study indicate that the ideal
feature vectors can be represented with high discrimination power
due to the global characteristic of orthogonal moment invariants.
Moreover, the effect of time-lapse has been decreasing and enhancing
the accuracy of face recognition considerably in comparison with
PCA. Furthermore, our experimental results based on moment
invariant and triangle square ratio criterion show that the proposed
approach achieves on average 13.6% higher in recognition rate than
PCA.
Abstract: In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral domain which is presented in digital and sonic form as the output. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.
Abstract: In this paper, we investigate the appearance of the giant component in random subgraphs G(p) of a given large finite graph family Gn = (Vn, En) in which each edge is present independently with probability p. We show that if the graph Gn satisfies a weak isoperimetric inequality and has bounded degree, then the probability p under which G(p) has a giant component of linear order with some constant probability is bounded away from zero and one. In addition, we prove the probability of abnormally large order of the giant component decays exponentially. When a contact graph is modeled as Gn, our result is of special interest in the study of the spread of infectious diseases or the identification of community in various social networks.
Abstract: Rapid advancement in computing technology brings
computers and humans to be seamlessly integrated in future. The
emergence of smartphone has driven computing era towards
ubiquitous and pervasive computing. Recognizing human activity has
garnered a lot of interest and has raised significant researches-
concerns in identifying contextual information useful to human
activity recognition. Not only unobtrusive to users in daily life,
smartphone has embedded built-in sensors that capable to sense
contextual information of its users supported with wide range
capability of network connections. In this paper, we will discuss the
classification algorithms used in smartphone-based human activity.
Existing technologies pertaining to smartphone-based researches in
human activity recognition will be highlighted and discussed. Our
paper will also present our findings and opinions to formulate
improvement ideas in current researches- trends. Understanding
research trends will enable researchers to have clearer research
direction and common vision on latest smartphone-based human
activity recognition area.
Abstract: Information and Communication Technologies (ICT) in mathematical education is a very active field of research and innovation, where learning is understood to be meaningful and grasping multiple linked representation rather than rote memorization, a great amount of literature offering a wide range of theories, learning approaches, methodologies and interpretations, are generally stressing the potentialities for teaching and learning using ICT. Despite the utilization of new learning approaches with ICT, students experience difficulties in learning concepts relevant to understanding mathematics, much remains unclear about the relationship between the computer environment, the activities it might support, and the knowledge that might emerge from such activities. Many questions that might arise in this regard: to what extent does the use of ICT help students in the process of understanding and solving tasks or problems? Is it possible to identify what aspects or features of students' mathematical learning can be enhanced by the use of technology? This paper will highlight the interest of the integration of information and communication technologies (ICT) into the teaching and learning of mathematics (quadratic functions), it aims to investigate the effect of four instructional methods on students- mathematical understanding and problem solving. Quantitative and qualitative methods are used to report about 43 students in middle school. Results showed that mathematical thinking and problem solving evolves as students engage with ICT activities and learn cooperatively.
Abstract: The presence of toxic heavy metals in industrial
effluents is one of the serious threats to the environment. Heavy
metals such as Cadmium, Chromium, Lead, Nickel, Zinc, Mercury,
Copper, Arsenic are found in the effluents of industries such as
foundries, electroplating, petrochemical, battery manufacturing,
tanneries, fertilizer, dying, textiles, metallurgical and metal finishing.
Tremendous increase of industrial copper usage and its presence in
industrial effluents has lead to a growing concern about the fate and
effects of Copper in the environment. Percolation of industrial
effluents through soils leads to contamination of ground water and
soils. The transport of heavy metals and their diffusion into the soils
has therefore, drawn the attention of the researchers.
In this study, an attempt has been made to delineate the
mechanisms of transport and fate of copper in terrestrial
environment. Column studies were conducted using perplex glass
square column of dimension side 15 cm and 1.35 m long. The soil
samples were collected from a natural drain near Mohali (India). The
soil was characterized to be poorly graded sandy loam. The soil was
compacted to the field dry density level of about 1.6 g/cm3. Break
through curves for different depths of the column were plotted. The
results of the column study indicated that the copper has high
tendency to flow in the soils and fewer tendencies to get absorbed on
the soil particles. The t1/2 estimates obtained from the studies can be
used for design copper laden wastewater disposal systems.
Abstract: Residue Number System (RNS) is a modular representation and is proved to be an instrumental tool in many digital signal processing (DSP) applications which require high-speed computations. RNS is an integer and non weighted number system; it can support parallel, carry-free, high-speed and low power arithmetic. A very interesting correspondence exists between the concepts of Multiple Valued Logic (MVL) and Residue Number Arithmetic. If the number of levels used to represent MVL signals is chosen to be consistent with the moduli which create the finite rings in the RNS, MVL becomes a very natural representation for the RNS. There are two concerns related to the application of this Number System: reaching the most possible speed and the largest dynamic range. There is a conflict when one wants to resolve both these problem. That is augmenting the dynamic range results in reducing the speed in the same time. For achieving the most performance a method is considere named “One-Hot Residue Number System" in this implementation the propagation is only equal to one transistor delay. The problem with this method is the huge increase in the number of transistors they are increased in order m2 . In real application this is practically impossible. In this paper combining the Multiple Valued Logic and One-Hot Residue Number System we represent a new method to resolve both of these two problems. In this paper we represent a novel design of an OHRNS-based adder circuit. This circuit is useable for Multiple Valued Logic moduli, in comparison to other RNS design; this circuit has considerably improved the number of transistors and power consumption.
Abstract: Since the late 1980s, the new phenomena of 'employment subcentres' or 'polycentricity' has appeared in the metropolises of North American and Western Europe and it has been an interesting topic for academics and researchers. This paper specifically uses one case study-Guangzhou to explore the development and the mechanism of employment subcentres and polycentricity in Chinese metropolises by spatial analysis method on the basis of the first economic census data. In conclusion, the paper regards that the employment subcentres and polycentricity has existed in Chinese metropolises. And that, the mechanism of them is mainly from the secondary industry instead of the tertiary industry in North American and Western Europe
Abstract: Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques with classifiers such as random
forests, neural networks and support vector machines. The data sets
are from MAGIC, a Cherenkov telescope experiment. The task is to
classify gamma signals from overwhelmingly hadron and muon
signals representing a rare class classification problem. We compare
the individual classifiers with their ensemble counterparts and
discuss the results. WEKA a wonderful tool for machine learning has
been used for making the experiments.
Abstract: Dual phase steels (DPS)s have a microstructure
consisting of a hard second phase called Martensite in the soft Ferrite
matrix. In recent years, there has been interest in dual-phase steels,
because the application of these materials has made significant usage;
particularly in the automotive sector Composite microstructure of
(DPS)s exhibit interesting characteristic mechanical properties such
as continuous yielding, low yield stress to tensile strength
ratios(YS/UTS), and relatively high formability; which offer
advantages compared with conventional high strength low alloy
steels(HSLAS). The research dealt with the characterization of
damage in (DPS)s. In this study by review the mechanisms of failure
due to volume fraction of martensite second phase; a new method is
introduced to identifying the mechanisms of failure in the various
phases of these types of steels. In this method the acoustic emission
(AE) technique was used to detect damage progression. These failure
mechanisms consist of Ferrite-Martensite interface decohesion and/or
martensite phase fracture. For this aim, dual phase steels with
different volume fraction of martensite second phase has provided by
various heat treatment methods on a low carbon steel (0.1% C), and
then AE monitoring is used during tensile test of these DPSs. From
AE measurements and an energy ratio curve elaborated from the
value of AE energy (it was obtained as the ratio between the strain
energy to the acoustic energy), that allows detecting important
events, corresponding to the sudden drops. These AE signals events
associated with various failure mechanisms are classified for ferrite
and (DPS)s with various amount of Vm and different martensite
morphology. It is found that AE energy increase with increasing Vm.
This increasing of AE energy is because of more contribution of
martensite fracture in the failure of samples with higher Vm. Final
results show a good relationship between the AE signals and the
mechanisms of failure.
Abstract: The dental composites are preferably used as filling
materials due to their esthetic appearances. Nevertheless one of the
major problems, during the application of the dental composites, is
shape change named as “polymerisation shrinkage" affecting clinical
success of the dental restoration while photo-polymerisation.
Polymerisation shrinkage of composites arises basically from the
formation of a polymer due to the monomer transformation which
composes of an organic matrix phase. It was sought, throughout this
study, to detect and evaluate the structural polymerisation shrinkage
of prepared dental composites in order to optimize the effects of
various fillers included in hydroxyapatite (HA)-reinforced dental
composites and hence to find a means to modify the properties of
these dental composites prepared with defined parameters. As a
result, the shrinkage values of the experimental dental composites
were decreased by increasing the filler content of composites and the
composition of different fillers used had effect on the shrinkage of
the prepared composite systems.
Abstract: Although the World Wide Web is considered the
largest source of information there exists nowadays, due to its
inherent dynamic characteristics, the task of finding useful and
qualified information can become a very frustrating experience. This
study presents a research on the information mining systems in the
Web; and proposes an implementation of these systems by means of
components that can be built using the technology of Web services.
This implies that they can encompass features offered by a services
oriented architecture (SOA) and specific components may be used by
other tools, independent of platforms or programming languages.
Hence, the main objective of this work is to provide an architecture
to Web mining systems, divided into stages, where each step is a
component that will incorporate the characteristics of SOA. The
separation of these steps was designed based upon the existing
literature. Interesting results were obtained and are shown here.
Abstract: The modeling of inelastic behavior of plastic materials requires measurements providing information on material response to different multiaxial loading conditions. Different triaxiality conditions and values of Lode parameters have to be
covered for complex description of the material plastic behavior.
Samples geometries providing material plastic behavoiur over the range of interest are proposed with the use of FEM analysis. Round samples with 3 different notches and smooth surface are used
together with butterfly type of samples tested at angle ranging for 0 to
90°. Identification of ductile damage parameters is carried out on
the basis of obtained experimental data for austenitic stainless steel.
The obtained material plastic damage parameters are subsequently applied to FEM simulation of notched CT normally samples used for
fracture mechanics testing and results from the simulation are
compared with real tests.
Abstract: In order to alleviate the mental and physical problems
of persons with disabilities, animal-assisted therapy (AAT) is one of
the possible modalities that employs the merit of the human-animal
interaction. Nevertheless, to achieve the purpose of AAT for persons
with severe disabilities (e.g. spinal cord injury, stroke, and
amyotrophic lateral sclerosis), real-time animal language
interpretation is desirable. Since canine behaviors can be visually
notable from its tail, this paper proposes the automatic real-time
interpretation of canine tail language for human-canine interaction in
the case of persons with severe disabilities. Canine tail language is
captured via two 3-axis accelerometers. Directions and frequencies
are selected as our features of interests. The novel fuzzy rules based
on Gaussian-Trapezoidal model and center of gravity (COG)-based
defuzzification method are proposed in order to interpret the features
into four canine emotional behaviors, i.e., agitate, happy, scare and
neutral as well as its blended emotional behaviors. The emotional
behavior model is performed in the simulated dog and has also been
evaluated in the real dog with the perfect recognition rate.