Abstract: Feature selection has been used in many fields such as
classification, data mining and object recognition and proven to be
effective for removing irrelevant and redundant features from the
original dataset. In this paper, a new design of distributed intrusion
detection system using a combination feature selection model based
on bees and decision tree. Bees algorithm is used as the search
strategy to find the optimal subset of features, whereas decision tree
is used as a judgment for the selected features. Both the produced
features and the generated rules are used by Decision Making Mobile
Agent to decide whether there is an attack or not in the networks.
Decision Making Mobile Agent will migrate through the networks,
moving from node to another, if it found that there is an attack on one
of the nodes, it then alerts the user through User Interface Agent or
takes some action through Action Mobile Agent. The KDD Cup 99
dataset is used to test the effectiveness of the proposed system. The
results show that even if only four features are used, the proposed
system gives a better performance when it is compared with the
obtained results using all 41 features.
Abstract: The purpose of this study is the discrimination of 28
postmenopausal with osteoporotic femoral fractures from an agematched
control group of 28 women using texture analysis based on
fractals. Two pre-processing approaches are applied on radiographic
images; these techniques are compared to highlight the choice of the
pre-processing method. Furthermore, the values of the fractal
dimension are compared to those of the fractal signature in terms of
the classification of the two populations. In a second analysis, the
BMD measure at proximal femur was compared to the fractal
analysis, the latter, which is a non-invasive technique, allowed a
better discrimination; the results confirm that the fractal analysis of
texture on calcaneus radiographs is able to discriminate osteoporotic
patients with femoral fracture from controls. This discrimination was
efficient compared to that obtained by BMD alone. It was also
present in comparing subgroups with overlapping values of BMD.
Abstract: Method of combined teaching laws of classical
mechanics and hydrostatics in non-inertial reference frames for
undergraduate students is proposed. Pressure distribution in a liquid
(or gas) moving with acceleration is considered. Combined effect of
hydrostatic force and force of inertia on a body immersed in a liquid
can lead to paradoxical results, in a motion of pendulum in particular.
The body motion under Stokes force influence and forces in rotating
reference frames are investigated as well. Problems and difficulties in
student perceptions are analyzed.
Abstract: Tool, Die and Mould-making (TDM) firms have been
known to play a pivotal role in the growth and development of the
manufacturing sectors in most economies. Their output contributes
significantly to the quality, cost and delivery speed of final
manufactured parts. Unfortunately, the South African Tool, Die and
Mould-making manufacturers have not been competing on the local
or global market in a significant way. This reality has hampered the
productivity and growth of the sector thus attracting intervention. The
paper explores the shortcomings South African toolmakers have to
overcome to restore their competitive position globally. Results from
a global benchmarking survey on the tooling sector are used to
establish a roadmap of what South African toolmakers can do to
become a productive, World Class force on the global market.
Abstract: Bloom’s Taxonomy has been changed during the
years. The idea of this writing is about the revision that has happened
in both facts and terms. It also contains case studies of using
cognitive Bloom’s taxonomy in teaching geometric solids to the
secondary school students, affective objectives in a creative
workshop for adults and psychomotor objectives in fixing a
malfunctioned refrigerator lamp. There is also pointed to the
important role of classification objectives in adult education as a way
to prevent memory loss.
Abstract: Mobile Adhoc Networks (MANETs) are
infrastructure-less, dynamic network of collections of wireless mobile
nodes communicating with each other without any centralized
authority. A MANET is a mobile device of interconnections through
wireless links, forming a dynamic topology. Routing protocols have a
big role in data transmission across a network. Routing protocols,
two major classifications are unipath and multipath. This study
evaluates performance of an on-demand multipath routing protocol
named Adhoc On-demand Multipath Distance Vector routing
(AOMDV). This study proposes Energy Aware AOMDV (EAAOMDV)
an extension of AOMDV which decreases energy
consumed on a route.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: High Order Thinking Skills (HOTS) are suggested
today as essential for the cognitive development of students and as
preparing them for real life skills. Teachers are encouraged to use
HOTS activities in the classroom to help their students develop
higher order skills and deep thinking. So it is essential to prepare preservice
teachers to write and use HOTS activities for their students.
This paper describes a model for integrating HOTS activities with
GeoGebra in pre-service teachers’ preparation. This model describes
four aspects of HOTS activities and working with them: activity
components, preparation procedure, strategies and processes used in
writing a HOTS activity and types of the HOTS activities. In
addition, the paper describes the pre-service teachers' difficulties in
preparing and working with HOTS activities, as well as their
perceptions regarding the use of these activities and GeoGebra in the
mathematics classroom. The paper also describes the contribution of
a HOTS activity to pupils' learning of mathematics, where this HOTS
activity was prepared and taught by one pre-service teacher.
Abstract: Typical load-bearing biological materials like bone,
mineralized tendon and shell, are biocomposites made from both
organic (collagen) and inorganic (biomineral) materials. This
amazing class of materials with intrinsic internally designed
hierarchical structures show superior mechanical properties with
regard to their weak components from which they are formed.
Extensive investigations concentrating on static loading conditions
have been done to study the biological materials failure. However,
most of the damage and failure mechanisms in load-bearing
biological materials will occur whenever their structures are exposed
to dynamic loading conditions. The main question needed to be
answered here is: What is the relation between the layout and
architecture of the load-bearing biological materials and their
dynamic behavior? In this work, a staggered model has been
developed based on the structure of natural materials at nanoscale and
Finite Element Analysis (FEA) has been used to study the dynamic
behavior of the structure of load-bearing biological materials to
answer why the staggered arrangement has been selected by nature to
make the nanocomposite structure of most of the biological materials.
The results showed that the staggered structures will efficiently
attenuate the stress wave rather than the layered structure.
Furthermore, such staggered architecture is effectively in charge of
utilizing the capacity of the biostructure to resist both normal and
shear loads. In this work, the geometrical parameters of the model
like the thickness and aspect ratio of the mineral inclusions selected
from the typical range of the experimentally observed feature sizes
and layout dimensions of the biological materials such as bone and
mineralized tendon. Furthermore, the numerical results validated with
existing theoretical solutions. Findings of the present work emphasize
on the significant effects of dynamic behavior on the natural
evolution of load-bearing biological materials and can help scientists
to design bioinspired materials in the laboratories.
Abstract: This research aims to identify traditional Mon cuisines
as well as gather and classify traditional cuisines of Mon
communities in Bangkok. The studying of this research is used by
methodology of the quantitative research. Using the questionnaire as
the method in collecting information from sampling totally amount of
450 persons analyzed via frequency, percentage and mean value. The
results showed that a variety of traditional Mon cuisines of Bangkok
could split into 6 categories of meat diet with 54 items and 6
categories of desserts with 19 items.
Abstract: Taiwanese composer Kuo Chih-Yuan (1921-2013)
studied composition at Tokyo University of the Arts and was
influenced by the musical nationalism prevailing in Japan at the time.
Determined to create world-class contemporary works to represent
Taiwan, he created music with elements of traditional Taiwanese
music in ways that had not been done before. The aims of this study
were to examine the traditional elements used in Kuo Chih-Yuan’s
Variations and Fugue on an Ancient Taiwanese Music (1972), and
how an understanding of these elements might guide pianists to
interpret a more proper performance of his work was also presented
in this study.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: The lifetime of a wireless sensor network can be
effectively increased by using scheduling operations. Once the
sensors are randomly deployed, the task at hand is to find the largest
number of disjoint sets of sensors such that every sensor set provides
complete coverage of the target area. At any instant, only one of these
disjoint sets is switched on, while all other are switched off. This
paper proposes a heuristic search method to find the maximum
number of disjoint sets that completely cover the region. A
population of randomly initialized members is made to explore the
solution space. A set of heuristics has been applied to guide the
members to a possible solution in their neighborhood. The heuristics
escalate the convergence of the algorithm. The best solution explored
by the population is recorded and is continuously updated. The
proposed algorithm has been tested for applications which require
sensing of multiple target points, referred to as point coverage
applications. Results show that the proposed algorithm outclasses the
existing algorithms. It always finds the optimum solution, and that
too by making fewer number of fitness function evaluations than the
existing approaches.
Abstract: This study utilizes a frequency domain approach over
the period of 1996 to 2013 to examine the causal relationship between
governance and economic growth in ten Asian countries, which have
different levels of democracy; classified as “Free”, “Partly Free”, and
“Not Free” countries. The empirical results show that there is no
Granger causality running from governance to economic growth in
“Not Free” countries and “Partly Free” countries with the exception of
Singapore. As for “Free” countries such as South Korea and Taiwan,
there is a one-way causality running from governance to economic
growth. The findings of this study indicate that policy makers in South
Korea, Taiwan, and Singapore could use governance index to improve
their predictions of the future economic growth.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
Abstract: This paper directs attention to the limitations of the
teacher-centered strategy in teaching. The aim of this study is to draw
more educational attention to learner-centered strategy in order to
shift the emphasis from the traditional concept of teaching to a new
concept in teaching. To begin bridging the traditional concept of
teaching and the new concept, the study will explore the new concept
of teaching to support teaching in Arab World generally and in Iraq
specifically. A qualitative case study orientation was used to collect
data in the form of classroom observations, interviews and field
notes. The teaching practices used by three university instructors are
investigated and according to the findings, some explanations and
recommendations are made.
Abstract: In this study, the signal of brain electrical activities of
the sixteen students selected from the Department of Electrical and
Energy at Usak University have been recorded during a lecturer
performed happiness emotions for the first group and anger emotions
for the second group in different time while the groups were in the
classroom separately. The attention and meditation data extracted
from the recorded signals have been analyzed and evaluated toward
the teacher’s specific emotion states simultaneously. Attention levels
of students who are under influence of happiness emotions of the
lecturer have a positive trend and attention levels of students who are
under influence of anger emotions of the lecturer have a negative
trend. The meditation or mental relaxation levels of students who are
under influence of happiness emotions of the lecturer are 34.3%
higher comparing with the mental relaxation levels of students who
are under influence of anger emotions of the lecturer.
Abstract: The growth of organic farming practices in the last
few decades is continuing to stimulate the international debate about
this alternative food market. As a part of a PhD project research
about embeddedness in Alternative Food Networks (AFNs), this
paper focuses on the promotional aspects of organic farms websites
from the Madrid region. As a theoretical tool, some knowledge
categories drawn on the geographic studies literature are used to
classify the many ideas expressed in the web pages. By analysing
texts and pictures of 30 websites, the study aims to question how and
to what extent actors from organic world communicate to the
potential customers their personal beliefs about farming practices,
products qualities, and ecological and social benefits. Moreover, the
paper raises the question of whether organic farming laws and
regulations lack of completeness about the social and cultural aspects
of food.