Abstract: The density estimates considered in this paper comprise
a base density and an adjustment component consisting of a linear
combination of orthogonal polynomials. It is shown that, in the
context of density approximation, the coefficients of the linear combination
can be determined either from a moment-matching technique
or a weighted least-squares approach. A kernel representation of
the corresponding density estimates is obtained. Additionally, two
refinements of the Kronmal-Tarter stopping criterion are proposed
for determining the degree of the polynomial adjustment. By way of
illustration, the density estimation methodology advocated herein is
applied to two data sets.
Abstract: One of the approaches to democratization is the fostering of civil society organizations. In Africa, civil society organizations did not fully play their role in the continent-s democratization process due to many factors including the repressive regulations imposed on them by governing parties. In Ethiopia, for the first time in the country-s political history, the civil society played a very active role in the 2005 multi-party election. The involvement of the civil society in this election has far-reaching consequences. One of the objectives of this paper is to assess the consequences of such involvement for both the civil society and the political society in the country. The paper also examines the peculiarities of civil society formation in Africa in general, and in Ethiopia in particular by assessing both the “traditional" and “modern" civil society organizations.
Abstract: Nowadays, offshore's complicated facilities need their
own communications requirements. Nevertheless, developing and
real-world applications of new communications technology are faced
with tremendous problems for new technology users, developers and
implementers. Traditional systems engineering cannot be capable to
develop a new technology effectively because it does not consider
the dynamics of the process. This paper focuses on the design of a
holistic model that represents the dynamics of new communication
technology development within offshore industry. The model shows
the behavior of technology development efforts. Furthermore,
implementing this model, results in new and useful insights about the
policy option analysis for developing a new communications
technology in offshore industry.
Abstract: This paper considers a robust recovery of sparse frequencies
from partial phase-only measurements. With the proposed
method, sparse frequencies can be reconstructed, which makes full
use of the sparse distribution in the Fourier representation of the
complex-valued time signal. Simulation experiments illustrate the
proposed method-s advantages over conventional methods in both
noiseless and additive white Gaussian noise cases.
Abstract: The estrus female Etawah cross bred goats were
synchronized estrus by controlled internal drug release (CIDR)
implants for 10 days combined with PGF2α injection, and continued
by artificial insemination (AI) within the hours of 24 period. Vaginal
epithelium was taken to determine estrus cycle of the goats without
estrus synchronization. The estrus responds (the puffy of vulva and
vaginal pH) and percentage of pregnancy were investigated. The data
were analyzed descriptively and Independent Sample T-Test. The
results showed that the puffy of vulva and vaginal pH were
significantly different in synchronized estrus goats and control goats
(2.18 ± 0.33 cm vs. 1.20 ± 0.16 cm and 8.55 ± 0.63 vs. 8.22 ± 0.22).
Percentage of pregnancy was higher in synchronized estrus goats
(73.33%) than in control (53.3%). Estrus synchronization by using
CIDR implants and PGF2, continued by AI was effective to improve
reproduction performance of Etawah cross bred goats.
Abstract: As the world changes more rapidly, the demand for update information for resource management, environment monitoring, planning are increasing exponentially. Integration of Remote Sensing with GIS technology will significantly promote the ability for addressing these concerns. This paper presents an alternative way of update GIS applications using image processing and high resolution images. We show a method of high-resolution image segmentation using graphs and morphological operations, where a preprocessing step (watershed operation) is required. A morphological process is then applied using the opening and closing operations. After this segmentation we can extract significant cartographic elements such as urban areas, streets or green areas. The result of this segmentation and this extraction is then used to update GIS applications. Some examples are shown using aerial photography.
Abstract: Current practice of indigenous Mapping production based on GIS, are mostly produced by professional GIS personnel. Given such persons maintain control over data collection and authoring, it is possible to conceive errors due to misrepresentation or cognitive misunderstanding, causing map production inconsistencies. In order to avoid such issues, this research into tribal GIS interface focuses not on customizing interfaces for individual tribes, but rather generalizing the interface and features based on indigenous tribal user needs. The methods employed differs from the traditional expert top-down approach, and instead gaining deeper understanding into indigenous Mappings and user needs, prior to applying mapping techniques and feature development.
Abstract: Computer worm detection is commonly performed by
antivirus software tools that rely on prior explicit knowledge of the
worm-s code (detection based on code signatures). We present an
approach for detection of the presence of computer worms based on
Artificial Neural Networks (ANN) using the computer's behavioral
measures. Identification of significant features, which describe the
activity of a worm within a host, is commonly acquired from security
experts. We suggest acquiring these features by applying feature
selection methods. We compare three different feature selection
techniques for the dimensionality reduction and identification of the
most prominent features to capture efficiently the computer behavior
in the context of worm activity. Additionally, we explore three
different temporal representation techniques for the most prominent
features. In order to evaluate the different techniques, several
computers were infected with five different worms and 323 different
features of the infected computers were measured. We evaluated
each technique by preprocessing the dataset according to each one
and training the ANN model with the preprocessed data. We then
evaluated the ability of the model to detect the presence of a new
computer worm, in particular, during heavy user activity on the
infected computers.
Abstract: The role of the pollen grain, with to the reproductive
process of higher plants, is to deliver the spermatic cells to the
embryo sac for egg fertilization. The aim of this project was study
the effect of electromagnetic fields on structure and pollen grains
development in Chenopodium album. Anthers of Chenopodium
album L. were collected at different stages of development from
control (without electromagnetic field) and plants grown at 10m from
the field sources. Structure and development of pollen grains were
studied and compared. The studying pollen structure by Light and
Scanning electron microscopy showed that electromagnetic fields
reduction of pollen grains number and male sterility, thus , in some
anthers, pollen grains were attached together and deformed compared
to control ones. The data presented suggest that prolonged exposures
of plants to magnetic field may cause different biological effects at
the cellular tissue and organ levels.
Abstract: In this paper, we present a novel objective nonreference
performance assessment algorithm for image fusion. It takes
into account local measurements to estimate how well the important
information in the source images is represented by the fused image.
The metric is based on the Universal Image Quality Index and uses
the similarity between blocks of pixels in the input images and the
fused image as the weighting factors for the metrics. Experimental
results confirm that the values of the proposed metrics correlate well
with the subjective quality of the fused images, giving a significant
improvement over standard measures based on mean squared error
and mutual information.
Abstract: This paper proposes a method for speckle reduction in
medical ultrasound imaging while preserving the edges with the
added advantages of adaptive noise filtering and speed. A nonlinear
image diffusion method that incorporates local image parameter,
namely, scatterer density in addition to gradient, to weight the
nonlinear diffusion process, is proposed. The method was tested for
the isotropic case with a contrast detail phantom and varieties of
clinical ultrasound images, and then compared to linear and some
other diffusion enhancement methods. Different diffusion parameters
were tested and tuned to best reduce speckle noise and preserve
edges. The method showed superior performance measured both
quantitatively and qualitatively when incorporating scatterer density
into the diffusivity function. The proposed filter can be used as a
preprocessing step for ultrasound image enhancement before
applying automatic segmentation, automatic volumetric calculations,
or 3D ultrasound volume rendering.
Abstract: Information Retrieval has the objective of studying
models and the realization of systems allowing a user to find the
relevant documents adapted to his need of information. The
information search is a problem which remains difficult because the
difficulty in the representing and to treat the natural languages such
as polysemia. Intentional Structures promise to be a new paradigm to
extend the existing documents structures and to enhance the different
phases of documents process such as creation, editing, search and
retrieval. The intention recognition of the author-s of texts can reduce
the largeness of this problem. In this article, we present intentions
recognition system is based on a semi-automatic method of
extraction the intentional information starting from a corpus of text.
This system is also able to update the ontology of intentions for the
enrichment of the knowledge base containing all possible intentions
of a domain. This approach uses the construction of a semi-formal
ontology which considered as the conceptualization of the intentional
information contained in a text. An experiments on scientific
publications in the field of computer science was considered to
validate this approach.
Abstract: With getting older in the whole population, the
prevalence of stroke and its residual disability is getting higher and
higher recently in Taiwan. The functional electrical stimulation
cycling system (FESCS) is useful for hemiplegic patients. Because
that the muscle of stroke patients is under hybrid activation. The raw
electromyography (EMG) represents the residual muscle force of
stroke subject whereas the peak-to-peak of stimulus EMG indicates the
force enhancement benefiting from ES. It seems that EMG signals
could be used for a parameter of feedback control mechanism. So, we
design the feedback control protocol of FESCS, it includes
physiological signal recorder, FPGA biomedical module, DAC and
electrical stimulation circuit. Using the intensity of real-time EMG
signal obtained from patients, as a feedback control method for the
output voltage of FES-cycling system.
Abstract: Cognitive Science appeared about 40 years ago,
subsequent to the challenge of the Artificial Intelligence, as common
territory for several scientific disciplines such as: IT, mathematics,
psychology, neurology, philosophy, sociology, and linguistics. The
new born science was justified by the complexity of the problems
related to the human knowledge on one hand, and on the other by the
fact that none of the above mentioned sciences could explain alone
the mental phenomena. Based on the data supplied by the
experimental sciences such as psychology or neurology, models of
the human mind operation are built in the cognition science. These
models are implemented in computer programs and/or electronic
circuits (specific to the artificial intelligence) – cognitive systems –
whose competences and performances are compared to the human
ones, leading to the psychology and neurology data reinterpretation,
respectively to the construction of new models. During these
processes if psychology provides the experimental basis, philosophy
and mathematics provides the abstraction level utterly necessary for
the intermission of the mentioned sciences.
The ongoing general problematic of the cognitive approach
provides two important types of approach: the computational one,
starting from the idea that the mental phenomenon can be reduced to
1 and 0 type calculus operations, and the connection one that
considers the thinking products as being a result of the interaction
between all the composing (included) systems. In the field of
psychology measurements in the computational register use classical
inquiries and psychometrical tests, generally based on calculus
methods. Deeming things from both sides that are representing the
cognitive science, we can notice a gap in psychological product
measurement possibilities, regarded from the connectionist
perspective, that requires the unitary understanding of the quality –
quantity whole. In such approach measurement by calculus proves to
be inefficient. Our researches, deployed for longer than 20 years,
lead to the conclusion that measuring by forms properly fits to the
connectionism laws and principles.
Abstract: The ever-growing usage of aspect-oriented
development methodology in the field of software engineering
requires tool support for both research environments and industry. So
far, tool support for many activities in aspect-oriented software
development has been proposed, to automate and facilitate their
development. For instance, the AJaTS provides a transformation
system to support aspect-oriented development and refactoring. In
particular, it is well established that the abstract interpretation of
programs, in any paradigm, pursued in static analysis is best served
by a high-level programs representation, such as Control Flow Graph
(CFG). This is why such analysis can more easily locate common
programmatic idioms for which helpful transformation are already
known as well as, association between the input program and
intermediate representation can be more closely maintained.
However, although the current researches define the good concepts
and foundations, to some extent, for control flow analysis of aspectoriented
programs but they do not provide a concrete tool that can
solely construct the CFG of these programs. Furthermore, most of
these works focus on addressing the other issues regarding Aspect-
Oriented Software Development (AOSD) such as testing or data flow
analysis rather than CFG itself. Therefore, this study is dedicated to
build an aspect-oriented control flow graph construction tool called
AJcFgraph Builder. The given tool can be applied in many software
engineering tasks in the context of AOSD such as, software testing,
software metrics, and so forth.
Abstract: Ant Colony Algorithms have been applied to difficult
combinatorial optimization problems such as the travelling salesman
problem and the quadratic assignment problem. In this paper gridbased
and random-based ant colony algorithms are proposed for
automatic 3D hose routing and their pros and cons are discussed. The
algorithm uses the tessellated format for the obstacles and the
generated hoses in order to detect collisions. The representation of
obstacles and hoses in the tessellated format greatly helps the
algorithm towards handling free-form objects and speeds up
computation. The performance of algorithm has been tested on a
number of 3D models.
Abstract: A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Abstract: In this research, effort was made to identify and
evaluate barriers to the development of entrepreneurship among
Iranian entrepreneur women who were graduated from universities.
In this study, perspectives of thirty-seven available entrepreneur
women were examined. In order to prepare questionnaires and
receive knowledge about barriers among these women, seven cases of
entrepreneur women took part in in-depth interviews. Then, to
evaluate the importance of barriers, the researchers made a
questionnaire with closed questions in which the barriers were
classified into the following categories: personal-familial barriers;
socio-cultural barriers; economic-financial-commercial barriers; and
structural barriers. Entrepreneur women were requested to rate the
importance of each item. The results indicated that there were
different obstacles among entrepreneur women. The order of the
important barriers was as fallow: economic-financial-commercial,
structural, socio-cultural, and personal-familial.
Abstract: Data mining incorporates a group of statistical
methods used to analyze a set of information, or a data set. It operates
with models and algorithms, which are powerful tools with the great
potential. They can help people to understand the patterns in certain
chunk of information so it is obvious that the data mining tools have
a wide area of applications. For example in the theoretical chemistry
data mining tools can be used to predict moleculeproperties or
improve computer-assisted drug design. Classification analysis is one
of the major data mining methodologies. The aim of thecontribution
is to create a classification model, which would be able to deal with a
huge data set with high accuracy. For this purpose logistic regression,
Bayesian logistic regression and random forest models were built
using R software. TheBayesian logistic regression in Latent GOLD
software was created as well. These classification methods belong to
supervised learning methods.
It was necessary to reduce data matrix dimension before construct
models and thus the factor analysis (FA) was used. Those models
were applied to predict the biological activity of molecules, potential
new drug candidates.
Abstract: Evolutionary Programming (EP) represents a
methodology of Evolutionary Algorithms (EA) in which mutation is
considered as a main reproduction operator. This paper presents a
novel EP approach for Artificial Neural Networks (ANN) learning.
The proposed strategy consists of two components: the self-adaptive,
which contains phenotype information and the dynamic, which is
described by genotype. Self-adaptation is achieved by the addition of
a value, called the network weight, which depends on a total number
of hidden layers and an average number of neurons in hidden layers.
The dynamic component changes its value depending on the fitness
of a chromosome, exposed to mutation. Thus, the mutation step size
is controlled by two components, encapsulated in the algorithm,
which adjust it according to the characteristics of a predefined ANN
architecture and the fitness of a particular chromosome. The
comparative analysis of the proposed approach and the classical EP
(Gaussian mutation) showed, that that the significant acceleration of
the evolution process is achieved by using both phenotype and
genotype information in the mutation strategy.