Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: The effects of coatings based on sodium alginate (S.A) and carboxyl methyl cellulose (CMC) on the color and moisture characteristics of potato round slices were investigated. It is the first time that this combination of polysaccharides is used as edible coating which alone had the best performance as inhibitor of potato color discoloration during the storage of 15 days at 4oC. When ascorbic acid (AA) and green tea (GT) were added in the above edible coating its effects on potato round slices changed. The mixtures of sodium alginate and carboxyl methyl cellulose with ascorbic acid or with green tea behave as a potential moisture barrier, resulting to the extent of potato samples self–life. These data suggests that both GT and AA are potential inhibitors of dehydration in potatoes and not only natural antioxidants.
Abstract: In the time of globalisation, growing uncertainty, ambiguity and change, traditional way of doing business are no longer sufficient and it is important to consider non-conventional methods and approaches to release creativity and facilitate innovation and growth. Thus, creative industries, as a natural source of creativity and innovation, draw particular attention. This paper explores feasibility of building creative partnerships between creative industries and business and brings attention to mutual benefits derived from such partnerships. Design/approach - This paper is a theoretical exploration of projects, practices and research findings addressing collaboration between creative industries and business. Thus, it concerns creative industries, arts, business and its representatives in order to define requirements for creative partnerships to work and succeed. Findings – Current practices in engaging into arts-business partnerships are still very few, although most of creative partnerships proved to be highly valuable and mutually beneficial. Certain conditions shall be provided in order to benefit from arts-business creative synergy. Originality/value- By integrating different sources of literature, this article provides a base for conducting empirical research in several dimensions within arts-business partnerships.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.
Abstract: The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.
Abstract: The environment pollution with pesticides and heavy
metals is a recognized problem nowadays, with extension to the
global scale the tendency of amplification. Even with all the progress
in the environmental field, both in the emphasize of the effect of the
pollutants upon health, the linked studies environment-health are
insufficient, not only in Romania but all over the world also. We aim
to describe the particular situation in Romania regarding the
uncontrolled use of pesticides, to identify and evaluate the risk zones
for health and the environment in Romania, with the final goal of
designing adequate programs for reduction and control of the risk
sources. An exploratory study was conducted to determine the
magnitude of the pesticide use problem in a population living in
Saliste, a rural setting in Transylvania, Romania. The significant
stakeholders in Saliste region were interviewed and a sample from
the population living in Saliste area was selected to fill in a designed
questionnaire. All the selected participants declared that they used
pesticides in their activities for more than one purpose. They
declared they annually applied pesticides for a period of time
between 11 and 30 years, from 5 to 9 days per year on average,
mainly on crops situated at some distance from the houses but high
risk behavior was identified as the volunteers declared the use of
pesticides in the backyard gardens, near their homes, where children
were playing. The pesticide applicators did not have the necessary
knowledge about safety and exposure. The health data must be
correlated with exposure biomarkers in attempt to identify the
possible health effects of the pesticides exposure. Future plans
include educational campaigns to raise the awareness of the
population on the danger of uncontrolled use of pesticides.
Abstract: Thirty six samples from each (aerobic and anoxic)
activated sludge were collected from two wastewater treatment plants
with MBRs in Berlin, Germany. The samples were prepared for count
and definition of fungal isolates; these isolates were purified by
conventional techniques and identified by microscopic examination.
Sixty tow species belonging to 28 genera were isolated from
activated sludge samples under aerobic conditions (28 genera and 58
species) and anoxic conditions (26 genera and 52 species). The
obtained data show that, Aspergillus was found at 94.4% followed by
Penicillium 61.1 %, Fusarium (61.1 %), Trichoderma (44.4 %) and
Geotrichum candidum (41.6 %) species were the most prevalent in all
activated sludge samples. The study confirmed that fungi can thrive
in activated sludge and sporulation, but isolated in different numbers
depending on the effect of aeration system. Some fungal species in
our study are saprophytic, and other a pathogenic to plants and
animals.
Abstract: This paper proposes an improved approach based on
conventional particle swarm optimization (PSO) for solving an
economic dispatch(ED) problem with considering the generator
constraints. The mutation operators of the differential evolution (DE)
are used for improving diversity exploration of PSO, which called
particle swarm optimization with mutation operators (PSOM). The
mutation operators are activated if velocity values of PSO nearly to
zero or violated from the boundaries. Four scenarios of mutation
operators are implemented for PSOM. The simulation results of all
scenarios of the PSOM outperform over the PSO and other existing
approaches which appeared in literatures.
Abstract: This paper presents a model for the characterization
and selection of beeswaxes for use as base substitute tissue for the
manufacture of objects suitable for external radiotherapy using
megavoltage photon beams. The model of characterization was
divided into three distinct stages: 1) verification of aspects related to
the origin of the beeswax, the bee species, the flora in the vicinity of
the beehives and procedures to detect adulterations; 2) evaluation of
physical and chemical properties; and 3) evaluation of beam
attenuation capacity. The chemical composition of the beeswax
evaluated in this study was similar to other simulators commonly
used in radiotherapy. The behavior of the mass attenuation coefficient
in the radiotherapy energy range was comparable to other simulators.
The proposed model is efficient and enables convenient assessment
of the use of any particular beeswax as a base substitute tissue for
radiotherapy.
Abstract: Text data mining is a process of exploratory data
analysis. Classification maps data into predefined groups or classes.
It is often referred to as supervised learning because the classes are
determined before examining the data. This paper describes proposed
radial basis function Classifier that performs comparative crossvalidation
for existing radial basis function Classifier. The feasibility
and the benefits of the proposed approach are demonstrated by means
of data mining problem: direct Marketing. Direct marketing has
become an important application field of data mining. Comparative
Cross-validation involves estimation of accuracy by either stratified
k-fold cross-validation or equivalent repeated random subsampling.
While the proposed method may have high bias; its performance
(accuracy estimation in our case) may be poor due to high variance.
Thus the accuracy with proposed radial basis function Classifier was
less than with the existing radial basis function Classifier. However
there is smaller the improvement in runtime and larger improvement
in precision and recall. In the proposed method Classification
accuracy and prediction accuracy are determined where the
prediction accuracy is comparatively high.
Abstract: Ground-level tropospheric ozone is one of the air
pollutants of most concern. It is mainly produced by photochemical
processes involving nitrogen oxides and volatile organic compounds
in the lower parts of the atmosphere. Ozone levels become
particularly high in regions close to high ozone precursor emissions
and during summer, when stagnant meteorological conditions with
high insolation and high temperatures are common.
In this work, some results of a study about urban ozone
distribution patterns in the city of Badajoz, which is the largest and
most industrialized city in Extremadura region (southwest Spain) are
shown. Fourteen sampling campaigns, at least one per month, were
carried out to measure ambient air ozone concentrations, during
periods that were selected according to favourable conditions to
ozone production, using an automatic portable analyzer.
Later, to evaluate the ozone distribution at the city, the measured
ozone data were analyzed using geostatistical techniques. Thus, first,
during the exploratory analysis of data, it was revealed that they were
distributed normally, which is a desirable property for the subsequent
stages of the geostatistical study. Secondly, during the structural
analysis of data, theoretical spherical models provided the best fit for
all monthly experimental variograms. The parameters of these
variograms (sill, range and nugget) revealed that the maximum
distance of spatial dependence is between 302-790 m and the
variable, air ozone concentration, is not evenly distributed in reduced
distances. Finally, predictive ozone maps were derived for all points
of the experimental study area, by use of geostatistical algorithms
(kriging). High prediction accuracy was obtained in all cases as
cross-validation showed. Useful information for hazard assessment
was also provided when probability maps, based on kriging
interpolation and kriging standard deviation, were produced.
Abstract: The increasing popularity of wireless technologies
and mobile computing devices has enabled new application areas and
research. One of these new areas is pervasive systems in urban
environments, because urban environments are characterized by high
concentration of these technologies and devices. In this paper we will
show the process of pervasive system design in urban environments,
using as use case a local zoo in Cali, Colombia. Based on an
ethnographic studio, we present the design of a pervasive system for
urban computing based on service oriented architecture to controlled
environment of Cali Zoo. In this paper, the reader will find a
methodological approach for the design of similar systems, using
data collection methods, conceptual frameworks for urban
environments and considerations of analysis and design of service
oriented systems.
Abstract: In this paper, a model for an information retrieval
system is proposed which takes into account that knowledge about
documents and information need of users are dynamic. Two
methods are combined, one qualitative or symbolic and the other
quantitative or numeric, which are deemed suitable for many
clustering contexts, data analysis, concept exploring and
knowledge discovery. These two methods may be classified as
inductive learning techniques. In this model, they are introduced to
build “long term" knowledge about past queries and concepts in a
collection of documents. The “long term" knowledge can guide
and assist the user to formulate an initial query and can be
exploited in the process of retrieving relevant information. The
different kinds of knowledge are organized in different points of
view. This may be considered an enrichment of the exploration
level which is coherent with the concept of document/query
structure.
Abstract: Traditionally, VLSI implementations of spiking
neural nets have featured large neuron counts for fixed computations
or small exploratory, configurable nets. This paper presents the
system architecture of a large configurable neural net system
employing a dedicated mapping algorithm for projecting the targeted
biology-analog nets and dynamics onto the hardware with its
attendant constraints.
Abstract: Support vector regression (SVR) has been regarded
as a state-of-the-art method for approximation and regression. The
importance of kernel function, which is so-called admissible support
vector kernel (SV kernel) in SVR, has motivated many studies
on its composition. The Gaussian kernel (RBF) is regarded as a
“best" choice of SV kernel used by non-expert in SVR, whereas
there is no evidence, except for its superior performance on some
practical applications, to prove the statement. Its well-known that
reproducing kernel (R.K) is also a SV kernel which possesses many
important properties, e.g. positive definiteness, reproducing property
and composing complex R.K by simpler ones. However, there are a
limited number of R.Ks with explicit forms and consequently few
quantitative comparison studies in practice. In this paper, two R.Ks,
i.e. SV kernels, composed by the sum and product of a translation
invariant kernel in a Sobolev space are proposed. An exploratory
study on the performance of SVR based general R.K is presented
through a systematic comparison to that of RBF using multiple
criteria and synthetic problems. The results show that the R.K is
an equivalent or even better SV kernel than RBF for the problems
with more input variables (more than 5, especially more than 10) and
higher nonlinearity.
Abstract: We present the results of a case study aiming to assess the reflection of the tourism community in the Web and its usability to propose new ways to communicate visually. The wealth of information contained in the Web and the clear facilities to communicate personals points of view makes of the social web a new space of exploration. In this way, social web allow the sharing of information between communities with similar interests. However, the tourism community remains unexplored as is the case of the information covered in travel stories. Along the Web, we find multiples sites allowing the users to communicate their experiences and personal points of view of a particular place of the world. This cultural heritage is found in multiple documents, usually very little supplemented with photos, so they are difficult to explore due to the lack of visual information. This paper explores the possibility of analyzing travel stories to display them visually on maps and generate new knowledge such as patterns of travel routes. This way, travel narratives published in electronic formats can be very important especially to the tourism community because of the great amount of knowledge that can be extracted. Our approach is based on the use of a Geoparsing Web Service to extract geographic coordinates from travel narratives in order to draw the geo-positions and link the documents into a map image.
Abstract: The study area receives a wide variety of wastes
generated by municipalities and the industries like paints and
pigments, metal processing industries, thermal power plants electroprocessing
industries etc. The Physico-chemical and structural
investigation of water from river Pandu indicated high level of
chlorides and calcium which made the water unsuitable for human
use. Algae like Cyclotella fumida, Asterionella Formosa,
Cladophora glomerata, Pediastrum simplex, Scenedesmus bijuga,
Cladophora glomerata were the dominant pollution tolerant species
recorded under these conditions. The sensitive and less abundant
species of algae included Spirogyra sps., Merismopedia sps. The
predominance colonies of Zygnema sps, Phormidium sps,
Mycrocystis aeruginosa, Merismopedia minima, Pandorina morum,
seems to correlate with high organic contents of Pandu river water.
This study assumes significance as some algae can be used as
bioindicators of water pollution and algal floral of a municipal drain
carrying waste effluents from industrial area Kanpur and discharge
them into the river Pandu flowing onto southern outskirts of Kanpur
city.
Abstract: This paper is an exploration of the conceptual
confusion between E-learning and M-learning particularly in Africa.
Section I provides a background to the development of E-learning
and M-learning. Section II focuses on the conceptual analysis as it
applies to Africa. It is with an investigative and expansive mind that
this paper is elaborated to respond to a profound question of the
suitability of the concepts in a particular era in Africa. The aim of this
paper is therefore to shed light on which concept best suits the unique
situation of Africa in the era of cloud computing.
Abstract: Polyurethane foams (PUF) were formed by a chemical
reaction of polyol and isocyanate. The polyol was manufactured by
ring-opening hydrolysis of epoxidized soybean oil in the presence of
phosphoric acid under varying experimental conditions. Other
factors in the foam formulation such as water content and surfactant
were kept constant. The effect of the amount of solvents, phosphoric
acid, and their derivates in the foam formulation on the properties of
polyurethane foams were studied. The properties of the material were
measured via a number of parameters, which are water content of
prepared polyol, polymer density and cellular structures.