Abstract: Microarray data profiles gene expression on a whole
genome scale, therefore, it provides a good way to study associations
between gene expression and occurrence or progression of cancer.
More and more researchers realized that microarray data is helpful
to predict cancer sample. However, the high dimension of gene
expressions is much larger than the sample size, which makes this
task very difficult. Therefore, how to identify the significant genes
causing cancer becomes emergency and also a hot and hard research
topic. Many feature selection algorithms have been proposed in
the past focusing on improving cancer predictive accuracy at the
expense of ignoring the correlations between the features. In this
work, a novel framework (named by SGS) is presented for stable gene
selection and efficient cancer prediction . The proposed framework
first performs clustering algorithm to find the gene groups where
genes in each group have higher correlation coefficient, and then
selects the significant genes in each group with Bayesian Lasso and
important gene groups with group Lasso, and finally builds prediction
model based on the shrinkage gene space with efficient classification
algorithm (such as, SVM, 1NN, Regression and etc.). Experiment
results on real world data show that the proposed framework often
outperforms the existing feature selection and prediction methods,
say SAM, IG and Lasso-type prediction model.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: In order to increase in chickpea quality and
agroecosystem sustainability, field experiments were carried out in
2007 and 2008 growing seasons. In this research the effects of
different organic, chemical and biological fertilizers were
investigated on grain yield and quality of chickpea. Experimental
units were arranged in split-split plots based on randomized complete
blocks with three replications. The highest amounts of yield and yield
components were obtained in G1×N5 interaction. Significant
increasing of N, P, K, Fe and Mg content in leaves and grains
emphasized on superiority of mentioned treatment because each one
of these nutrients has an approved role in chlorophyll synthesis and
photosynthesis ability of the crop. The combined application of
compost, farmyard manure and chemical phosphorus (N5) had the
best grain quality due to high protein, starch and total sugar contents,
low crude fiber and reduced cooking time.
Abstract: In this study, Li4SiO4 powder was successfully
synthesized via sol gel method followed by drying at 150oC. Lithium
oxide, Li2O and silicon oxide, SiO2 were used as the starting
materials with citric acid as the chelating agent. The obtained powder
was then sintered at various temperatures. Crystallographic phase
analysis, morphology and ionic conductivity were investigated
systematically employing X-ray diffraction, Fourier Transform
Infrared, Scanning Electron Microscopy and AC impedance
spectroscopy. XRD result showed the formation of pure monoclinic
Li4SiO4 crystal structure with lattice parameters a = 5.140 Å, b =
6.094 Å, c = 5.293 Å, β = 90o in the sample sintered at 750oC. This
observation was confirmed by FTIR analysis. The bulk conductivity
of this sample at room temperature was 3.35 × 10-6 S cm-1 and the
highest bulk conductivity of 1.16 × 10-4 S cm-1 was obtained at
100°C. The results indicated that, the Li4SiO4 compound has
potential to be used as host for LISICON structured solid electrolyte
for low temperature application.
Abstract: The possibility of radionuclides-related contamination
of lands at agricultural holdings defines the necessity to apply special
protective measures in plant growing. The aim of researches is to
elucidate the influence of polymers applying on biological migration
of man-made anthropogenic radionuclides 90Sr and 137Cs in the
system water - soil – plant. The tests are being carried out under field
conditions with and without application of polymers in root-inhabited
media in more radioecological tension zone (with the radius of 7 km
from the Armenian Nuclear Power Plant). The polymers on the base
of K+, Caµ, KµCaµ ions were tested. Productivity of pepper
depending on the presence and type of polymer material, content of
artificial radionuclides in waters, soil and plant material has been
determined. The character of different polymers influence on the
artificial radionuclides migration and accumulation in the system
water-soil-plant and accumulation in the plants has been cleared up.
Abstract: Knowledge modelling, a main activity for the development of Knowledge Based Systems, have no set standards and are mostly done in an ad hoc way. There is a lack of support for the transition from abstract level to implementation. In this paper, a methodology for the development of the knowledge model, which is inspired by both Software and Knowledge Engineering, is proposed. Use of UML which is the de-facto standard for modelling in the software engineering arena is explored for knowledge modelling. The methodology proposed, is used to develop a knowledge model of a knowledge based system for recommending suitable hotels for tourists visiting Mauritius.
Abstract: This paper examines the link between gender equality
and climate change policies in Australia. It critically analyses the
extent to which gender mainstreaming and gender dimensions have
been taken into account in the national policy processes for climate
change in Australia. The paper argues that climate change adaptation
and mitigation policies in Australia neglect gender dimensions. This
endangers the advances made in gender equality and works against
socially equitable and effective climate change strategies.
Abstract: Academia-industry relationship is not like that of
technology donator-acceptor, but is of interactive and collaborative
nature, acknowledging and ensuring mutual respect for each other-s
role and contributions with an eye to attaining the true purpose of
such relationships, namely, bringing about research-outcome
synergy. Indeed, academia-industry interactions are a system that
requires active and collaborative participations of all the
stakeholders.
This paper examines various issues associated with academic
institutions and industry collaboration with special attention to the
nature of resources and potentialities of stakeholders in the context of
knowledge management. This paper also explores the barriers of
academia-industry interaction. It identifies potential areas where
industry-s participation with academia would be most effective for
synergism. Lastly, this paper proposes an integrated model of several
new collaborative approaches that are possible, mainly in the Indian
scenario to strengthen academia-industry interface.
Abstract: The objective of this research was to find the diffusion properties of vehicles on the road by using the V-Sphere Code. The diffusion coefficient and the size of the height of the wake were estimated with the LES option and the third order MUSCL scheme. We evaluated the code with the changes in the moments of Reynolds Stress along the mean streamline. The results show that at the leading part of a bluff body the LES has some advantages over the RNS since the changes in the strain rates are larger for the leading part. We estimated that the diffusion coefficient with the computed Reynolds stress (non-dimensional) was about 0.96 times the mean velocity.
Abstract: The introduction of sowing technologies into minimum- or no-tillage soil has a number of economical and environmental virtues, such as improving soil properties, decreasing soil erosion and degradation, and saving working time and fuel. However, the main disadvantage of these technologies is that plant residues on the soil surface reduce the quality of the planted crop seeds, thus requiring plant residues to be removed or cut. This paper presents a analysis of disc coulter parameters and an experimental investigation of cutting spring barley straw containing various amounts of moisture with different disc coulters (smooth and notched).
Abstract: In the literature of information theory, there is
necessity for comparing the different measures of fuzzy entropy and
this consequently, gives rise to the need for normalizing measures of
fuzzy entropy. In this paper, we have discussed this need and hence
developed some normalized measures of fuzzy entropy. It is also
desirable to maximize entropy and to minimize directed divergence
or distance. Keeping in mind this idea, we have explained the method
of optimizing different measures of fuzzy entropy.
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: Tensile armour wires provide a flexible pipe's
resistance to longitudinal stresses. Flexible pipe manufacturers need
to know the effect of defects such as scratches and cracks, with
dimensions less than 0.2mm which is the limit of the current nondestructive
detection technology, on the fracture stress and fracture
strain of the wire for quality assurance purposes. Recent research
involving the determination of the fracture strength of cracked wires
employed laboratory testing and classical fracture mechanics
approach using non-standardised fracture mechanics specimens
because standard test specimens could not be manufactured from the
wires owing to their sizes. In this work, the effect of miniature
cracks on the fracture properties of tensile armour wires was
investigated using laboratory and finite element tensile testing
simulations with the phenomenological shear fracture model. The
investigation revealed that the presence of cracks shallower than
0.2mm is worse on the fracture strain of the wire.
Abstract: Inter-organizational Workflow (IOW) is commonly
used to support the collaboration between heterogeneous and
distributed business processes of different autonomous organizations
in order to achieve a common goal. E-government is considered as an
application field of IOW. The coordination of the different
organizations is the fundamental problem in IOW and remains the
major cause of failure in e-government projects. In this paper, we
introduce a new coordination model for IOW that improves the
collaboration between government administrations and that respects
IOW requirements applied to e-government. For this purpose, we
adopt a Multi-Agent approach, which deals more easily with interorganizational
digital government characteristics: distribution,
heterogeneity and autonomy. Our model integrates also different
technologies to deal with the semantic and technologic
interoperability. Moreover, it conserves the existing systems of
government administrations by offering a distributed coordination
based on interfaces communication. This is especially applied in
developing countries, where administrations are not necessary
equipped with workflow systems. The use of our coordination
techniques allows an easier migration for an e-government solution
and with a lower cost. To illustrate the applicability of the proposed
model, we present a case study of an identity card creation in Tunisia.
Abstract: Not with standing the importance of foreign highly
skilled professionals for host economies, there is a paucity of
research studies investigating the role of the corporate social context
during the integration process. This research aims to address this
paucity by exploring the role of social capital in the integration of
foreign health professionals. It does so by using a qualitative research
approach. In this pilot study the hospital sector forms this study-s
sample and interviews were conducted with HR managers, foreign
health professionals and external HR consultants. It was found that
most of the participating hospitals had not established specific HR
practices and had only partly linked the development of
organisational social capital with a successful integration process.
This research contributes, for example, to the HR literature on the
integration of self-initiated expatriates by analysing the role of HRM
in generating organisational social capital needed for a successful
integration process.
Abstract: This paper presents the applicability of artificial
neural networks for 24 hour ahead solar power generation forecasting
of a 20 kW photovoltaic system, the developed forecasting is suitable
for a reliable Microgrid energy management. In total four neural
networks were proposed, namely: multi-layred perceptron, radial
basis function, recurrent and a neural network ensemble consisting in
ensemble of bagged networks. Forecasting reliability of the proposed
neural networks was carried out in terms forecasting error
performance basing on statistical and graphical methods. The
experimental results showed that all the proposed networks achieved
an acceptable forecasting accuracy. In term of comparison the neural
network ensemble gives the highest precision forecasting comparing
to the conventional networks. In fact, each network of the ensemble
over-fits to some extent and leads to a diversity which enhances the
noise tolerance and the forecasting generalization performance
comparing to the conventional networks.
Abstract: The building sector is the largest energy consumer and
CO2 emitter in the European Union (EU) and therefore the active
reduction of energy consumption and elimination of energy wastage
are among the main goals in it. Healthy housing and energy
efficiency are affected by many factors which set challenges to
monitoring, control and research of indoor air quality (IAQ) and
energy consumption, especially in old buildings. These challenges
include measurement and equipment costs, for example.
Additionally, the measurement results are difficult to interpret and
their usage in the ventilation control is also limited when taking into
account the energy efficiency of housing at the same time. The main
goal of this study is to develop a cost-effective building monitoring
and control system especially for old buildings. The starting point or
keyword of the development process is a wireless system; otherwise
the installation costs become too high. As the main result, this paper
describes an idea of a wireless building monitoring and control
system. The first prototype of the system has been installed in 10
residential buildings and in 10 school buildings located in the City of
Kuopio, Finland.
Abstract: Article devoted to the development of technologies
for medicine and agroecology by using plant organelle – spherosome.
Technological method of purification and isolation of this organelle
by using novel nanostructured carbon sorbent – “nanocarbosorb"
ARK type are presented. Also the methods of preparation of
nanocontainers based on using of spherosome with loaded isosorbide
dinitrate, piroxicam or diclofenak are exhibited. We found that the
spherosome could be applied for ecological aims as bioregulator and
also as biosensor for determination of ammonia ions in water
reservoirs at concentration range 1mM to 100mM.
Abstract: Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.
Abstract: In this paper we introduce a novel kernel classifier
based on a iterative shrinkage algorithm developed for compressive
sensing. We have adopted Bregman iteration with soft and hard
shrinkage functions and generalized hinge loss for solving l1 norm
minimization problem for classification. Our experimental results
with face recognition and digit classification using SVM as the
benchmark have shown that our method has a close error rate
compared to SVM but do not perform better than SVM. We have
found that the soft shrinkage method give more accuracy and in some
situations more sparseness than hard shrinkage methods.