Abstract: We intend to point out the differences which exist
between the classical Gini concentration coefficient and a proposed
bipolarization index defined for an arbitrary random variable which
have a finite support.
In fact Gini's index measures only the "poverty degree" for the
individuals from a given population taking into consideration their
wages. The Gini coefficient is not so sensitive to the significant
income variations in the "rich people class" .
In practice there are multiple interdependent relations between the
pauperization and the socio-economical polarization phenomena. The
presence of a strong pauperization aspect inside the population
induces often a polarization effect in this society. But the
pauperization and the polarization phenomena are not identical. For
this reason it isn't always adequate to use a Gini type coefficient,
based on the Lorenz order, to estimate the bipolarization level of the
individuals from the studied population.
The present paper emphasizes these ideas by considering two
families of random variables which have a linear or a triangular type
distributions. In addition, the continuous variation, depending on the
parameter "time" of the chosen distributions, could simulate a real
dynamical evolution of the population.
Abstract: A generic and extendible Multi-Agent Data Mining
(MADM) framework, MADMF (the Multi-Agent Data Mining
Framework) is described. The central feature of the framework is that
it avoids the use of agreed meta-language formats by supporting a
framework of wrappers.
The advantage offered is that the framework is easily extendible,
so that further data agents and mining agents can simply be added to
the framework. A demonstration MADMF framework is currently
available. The paper includes details of the MADMF architecture and
the wrapper principle incorporated into it. A full description and
evaluation of the framework-s operation is provided by considering
two MADM scenarios.
Abstract: Determining how many virtual machines a Linux host
could run can be a challenge. One of tough missions is to find the
balance among performance, density and usability. Now KVM
hypervisor has become the most popular open source full
virtualization solution. It supports several ways of running guests with
more memory than host really has. Due to large differences between
minimum and maximum guest memory requirements, this paper
presents initial results on same-page merging, ballooning and live
migration techniques that aims at optimum memory usage on
KVM-based cloud platform. Given the design of initial experiments,
the results data is worth reference for system administrators. The
results from these experiments concluded that each method offers
different reliability tradeoff.
Abstract: This paper presents an authoring tool which makes a
user easily and intuitively design vibrotactile sensation. A mobile
hardware platform powered by ANDROID, a multi-purpose haptic
driver and a linear resonance actuator are used to implement the
system of the presented authoring tool. The tool allows users to easily
and simply create a vibrotactile sensation by drawing vibrotactile
images and to feel the sensation by rubbing drawn images on the touch
screen of a mobile device. The tool supports a graphical interface for
designing, editing and playing vibrotactile images as well as a
pre-defined file format for save and open.
Abstract: In this paper, we propose a new method to distinguish
between arousal and relaxation states by using multiple features
acquired from a photoplethysmogram (PPG) and support vector
machine (SVM). To induce arousal and relaxation states in subjects, 2
kinds of sound stimuli are used, and their corresponding biosignals are
obtained using the PPG sensor. Two features–pulse to pulse interval
(PPI) and pulse amplitude (PA)–are extracted from acquired PPG
data, and a nonlinear classification between arousal and relaxation is
performed using SVM.
This methodology has several advantages when compared with
previous similar studies. Firstly, we extracted 2 separate features from
PPG, i.e., PPI and PA. Secondly, in order to improve the classification
accuracy, SVM-based nonlinear classification was performed.
Thirdly, to solve classification problems caused by generalized
features of whole subjects, we defined each threshold according to
individual features.
Experimental results showed that the average classification
accuracy was 74.67%. Also, the proposed method showed the better
identification performance than the single feature based methods.
From this result, we confirmed that arousal and relaxation can be
classified using SVM and PPG features.
Abstract: Power System Security is a major concern in real time
operation. Conventional method of security evaluation consists of
performing continuous load flow and transient stability studies by
simulation program. This is highly time consuming and infeasible
for on-line application. Pattern Recognition (PR) is a promising
tool for on-line security evaluation. This paper proposes a Support
Vector Machine (SVM) based binary classification for static and
transient security evaluation. The proposed SVM based PR approach
is implemented on New England 39 Bus and IEEE 57 Bus systems.
The simulation results of SVM classifier is compared with the other
classifier algorithms like Method of Least Squares (MLS), Multi-
Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA)
classifiers.
Abstract: The use of 3D computer-aided design (CAD) models
to support construction project planning has been increasing in the
previous year. 3D CAD models reveal more planning ideas by
visually showing the construction site environment in different stages
of the construction process. Using 3D CAD models together with
scheduling software to prepare construction plan can identify errors
in process sequence and spatial arrangement, which is vital to the
success of a construction project. A number of 4D (3D plus time)
CAD tools has been developed and utilized in different construction
projects due to the awareness of their importance. Virtual prototyping
extends the idea of 4D CAD by integrating more features for
simulating real construction process. Virtual prototyping originates
from the manufacturing industry where production of products such
as cars and airplanes are virtually simulated in computer before they
are built in the factory. Virtual prototyping integrates 3D CAD,
simulation engine, analysis tools (like structural analysis and
collision detection), and knowledgebase to streamline the whole
product design and production process. In this paper, we present the
application of a virtual prototyping software which has been used in
a few construction projects in Hong Kong to support construction
project planning. Specifically, the paper presents an implementation
of virtual prototyping in a residential building project in Hong Kong.
The applicability, difficulties and benefits of construction virtual
prototyping are examined based on this project.
Abstract: The increasing recognition of the need for education to be closely aligned with team playing, project based learning and problem solving approaches has increase the interest in collaborative learning among university and college instructors. Using online collaboration learning in learning can enhance the outcome and achievement of students as well as improve their communication, critical thinking and personnel skills. The current research aims at examining the effect of OCL on the student's achievement at Kingdom of Bahrain. Numbers of objectives were set to achieve the aim of the research include: investigating the current situation regarding the collaborative learning and OCL at the Kingdom of Bahrain by identifying the advantages and effectiveness of OCL as a learning tool over traditional learning, examining the factors that affect OCL as well as examining the impact of OCL on the student's achievement. To achieve these objectives, quantitative method was adopted. Two hundred and thirty one questionnaires were distributed to students in different local and private universities at Kingdom of Bahrain. The findings of the research show that most of the students prefer to use FTFCL in learning and that OCL is already adopted in some universities especially in University of Bahrain. Moreover, the most factors affecting the adopted OCL are perceived readiness, and guidance and support.
Abstract: We present an Electronic Nose (ENose), which is
aimed at identifying the presence of one out of two gases, possibly
detecting the presence of a mixture of the two. Estimation of the
concentrations of the components is also performed for a volatile
organic compound (VOC) constituted by methanol and acetone, for
the ranges 40-400 and 22-220 ppm (parts-per-million), respectively.
Our system contains 8 sensors, 5 of them being gas sensors (of the
class TGS from FIGARO USA, INC., whose sensing element is a tin
dioxide (SnO2) semiconductor), the remaining being a temperature
sensor (LM35 from National Semiconductor Corporation), a
humidity sensor (HIH–3610 from Honeywell), and a pressure sensor
(XFAM from Fujikura Ltd.).
Our integrated hardware–software system uses some machine
learning principles and least square regression principle to identify at
first a new gas sample, or a mixture, and then to estimate the
concentrations. In particular we adopt a training model using the
Support Vector Machine (SVM) approach with linear kernel to teach
the system how discriminate among different gases. Then we apply
another training model using the least square regression, to predict
the concentrations.
The experimental results demonstrate that the proposed
multiclassification and regression scheme is effective in the
identification of the tested VOCs of methanol and acetone with
96.61% correctness. The concentration prediction is obtained with
0.979 and 0.964 correlation coefficient for the predicted versus real
concentrations of methanol and acetone, respectively.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents in legacy e-learning environments. It introduces the design and development of a scalable
and interoperable integration platform supporting various assessment agents for e-learning environments. The agents are implemented in
order to provide intelligent assessment services to computational intelligent techniques such as Bayesian Networks and Genetic
Algorithms. The utilization of new and emerging technologies like web services allows integrating the provided services to any web
based legacy e-learning environment.
Abstract: Aggression is a multi- factorial concept and multilevel
in nature. The Young Adolescent is being influenced by family,
school and community. This paper is aimed to determine the
following: aggression level among young adolescents, difference of
level of aggression on school and year levels and to determine the
correlates of aggression. There were 142 high school students from
two different national highs schools (Region 3 and National Capital
Region).Convenience sampling was use in this study. The following
measures were used namely: Aggression Scale, Parental Support
Fighting Scale, Positive Behavior Scale and Exposure to Violence
and Trauma questionnaire. There was no significant difference in
aggression level among different year level and schools. The
findings of the study suggested that high level of community violence
and having low parental support for non-aggressive behavior
contribute to the prediction of aggression.
Abstract: SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.
Abstract: This paper discusses site selection process for
biological soil conservation planning. It was supported by a valuefocused
approach and spatial multi-criteria evaluation techniques. A
first set of spatial criteria was used to design a number of potential
sites. Next, a new set of spatial and non-spatial criteria was
employed, including the natural factors and the financial costs,
together with the degree of suitability for the Bonkuh watershed to
biological soil conservation planning and to recommend the most
acceptable program. The whole process was facilitated by a new
software tool that supports spatial multiple criteria evaluation, or
SMCE in GIS software (ILWIS). The application of this tool,
combined with a continual feedback by the public attentions, has
provided an effective methodology to solve complex decisional
problem in biological soil conservation planning.
Abstract: A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.
Abstract: Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.
Abstract: Through the analysis of the process digital design
based on digital mockup, the fact indicates that a distributed
cooperative supporting environment is the foundation conditions to
adopt design approach based on DMU. Data access authorization is
concerned firstly because the value and sensitivity of the data for the
enterprise. The access control for administrators is often rather weak
other than business user. So authors established an enhanced system to
avoid the administrators accessing the engineering data by potential
approach and without authorization. Thus the data security is
improved.
Abstract: IPN and IPE sections, which are commonly used European I shapes, are widely used in steel structures as cantilever beams to support overhangs. A considerable number of studies exist on calculating lateral torsional buckling load of I sections. However, most of them provide series solutions or complex closed-form equations. In this paper, a simple equation is presented to calculate lateral torsional buckling load of IPN and IPE section cantilever beams. First, differential equation of lateral torsional buckling is solved numerically for various loading cases. Then a parametric study is conducted on results to present an equation for lateral torsional buckling load of European IPN and IPE beams. Finally, results obtained by presented equation are compared to differential equation solutions and finite element model results. ABAQUS software is utilized to generate finite element models of beams. It is seen that the results obtained from presented equation coincide with differential equation solutions and ABAQUS software results. It can be suggested that presented formula can be safely used to calculate critical lateral torsional buckling load of European IPN and IPE section cantilevers.
Abstract: Application of Information Technology (IT) has
revolutionized the functioning of business all over the world. Its
impact has been felt mostly among the information of dependent
industries. Tourism is one of such industry. The conceptual
framework in this study represents an innovation of travel
information searching system on mobile devices which is used as
tools to deliver travel information (such as hotels, restaurants, tourist
attractions and souvenir shops) for each user by travelers
segmentation based on data mining technique to segment the tourists-
behavior patterns then match them with tourism products and
services. This system innovation is designed to be a knowledge
incremental learning. It is a marketing strategy to support business to
respond traveler-s demand effectively.
Abstract: A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.
Abstract: The IEEE802.16 standard which has emerged as
Broadband Wireless Access (BWA) technology, promises to deliver
high data rate over large areas to a large number of subscribers in the
near future. This paper analyze the effect of overheads over capacity
of downlink (DL) of orthogonal frequency division multiple access
(OFDMA)–based on the IEEE802.16e mobile WiMAX system with
and without overheads. The analysis focuses in particular on the
impact of Adaptive Modulation and Coding (AMC) as well as
deriving an algorithm to determine the maximum numbers of
subscribers that each specific WiMAX sector may support. An
analytical study of the WiMAX propagation channel by using Cost-
231 Hata Model is presented. Numerical results and discussion
estimated by using Matlab to simulate the algorithm for different
multi-users parameters.