Abstract: In the present work, we propose a new technique to
enhance the learning capabilities and reduce the computation
intensity of a competitive learning multi-layered neural network
using the K-means clustering algorithm. The proposed model use
multi-layered network architecture with a back propagation learning
mechanism. The K-means algorithm is first applied to the training
dataset to reduce the amount of samples to be presented to the neural
network, by automatically selecting an optimal set of samples. The
obtained results demonstrate that the proposed technique performs
exceptionally in terms of both accuracy and computation time when
applied to the KDD99 dataset compared to a standard learning
schema that use the full dataset.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
Abstract: This work deals with unsupervised image deblurring.
We present a new deblurring procedure on images provided by lowresolution
synthetic aperture radar (SAR) or simply by multimedia in
presence of multiplicative (speckle) or additive noise, respectively.
The method we propose is defined as a two-step process. First, we
use an original technique for noise reduction in wavelet domain.
Then, the learning of a Kohonen self-organizing map (SOM) is
performed directly on the denoised image to take out it the blur. This
technique has been successfully applied to real SAR images, and the
simulation results are presented to demonstrate the effectiveness of
the proposed algorithms.
Abstract: In this study the behavior of interlaminar fracture of
carbon-epoxy thermoplastic laminated composite is investigated
numerically and experimentally. Tests are performed with Arcan
specimens. Testing with Arcan specimen gives the opportunity of
utilizing just one kind of specimen for extracting fracture properties
for mode I, mode II and different mixed mode ratios of materials with
exerting load via different loading angles. Variation of loading angles
in range of 0-90° made possible to achieve different mixed mode
ratios. Correction factors for various conditions are obtained from
ABAQUS 2D finite element models which demonstrate the finite
shape of Arcan specimens used in this study. Finally, applying the
correction factors to critical loads obtained experimentally, critical
interlaminar fracture toughness of this type of carbon- epoxy
composite has been attained.
Abstract: This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction
Abstract: This paper investigates the effectiveness of the use of
seismic isolation devices on the overall 3D seismic response of
curved highway viaducts with an emphasis on expansion joints.
Furthermore, an evaluation of the effectiveness of the use of cable
restrainers is presented. For this purpose, the bridge seismic
performance has been evaluated on four different radii of curvature,
considering two cases: restrained and unrestrained curved viaducts.
Depending on the radius of curvature, three-dimensional non-linear
dynamic analysis shows the vulnerability of curved viaducts to
pounding and deck unseating damage. In this study, the efficiency of
using LRB supports combined with cable restrainers on curved
viaducts is demonstrated, not only by reducing in all cases the
possible damage, but also by providing a similar behavior in the
viaducts despite of curvature radius.
Abstract: Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.
Abstract: The study and development of an innovative material
for building insulation is really important for a sustainable society in order to improve comfort and reducing energy consumption. The aim of this work is the development of insulating panels for
sustainable buildings based on an innovative material made by
cardboard and Phase Change Materials (PCMs).
The research has consisted in laboratory tests whose purpose has been the obtaining of the required properties for insulation panels: lightweight, porous structures and mechanical resistance. PCMs have been used for many years in the building industry as
smart insulation technology because of their properties of storage and release high quantity of latent heat at useful specific temperatures [1]- [2].
The integration of PCMs into cellulose matrix during the waste paper recycling process has been developed in order to obtain a
composite material.
Experiments on the productive process for the realization of insulating panels were done in order to make the new material
suitable for building application. The addition of rising agents
demonstrated the possibility to obtain a lighter structure with better
insulation properties.
Several tests were conducted to verify the new panel properties. The results obtained have shown the possibility to realize an
innovative and sustainable material suitable to replace insulating panels currently used.
Abstract: This paper presents the results of an analytical study
on the seismic response of a Multi-Span-Simply-Supported precast
bridge in Washington State. The bridge was built in the early 1960's
along Interstate 5 and was widened the first time in 1979 and the
second time in 2001. The primary objective of this research project
is to determine the seismic vulnerability of the bridge in order to
develop the required retrofit measure. The seismic vulnerability of
the bridge is evaluated using two seismic evaluation methods
presented in the FHWA Seismic Retrofitting Manual for Highway
Bridges, Method C and Method D2. The results of the seismic
analyses demonstrate that Method C and Method D2 vary markedly
in terms of the information they provide to the bridge designer
regarding the vulnerability of the bridge columns.
Abstract: This paper proposes a simple model of economic geography within the Dixit-Stiglitz-Iceberg framework that may be used to analyze migration patterns among three cities. The cost–benefit tradeoffs affecting incentives for three types of migration, including echelon migration, are discussed. This paper develops a tractable, heterogeneous-agent, general equilibrium model, where agents share constant human capital, and explores the relationship between the benefits of echelon migration and gross human capital. Using Chinese numerical solutions, we study the manifestation of echelon migration and how it responds to changes in transportation cost and elasticity of substitution. Numerical results demonstrate that (i) there are positive relationships between a migration-s benefit-and-wage ratio, (ii) there are positive relationships between gross human capital ratios and wage ratios as to origin and destination, and (iii) we identify 13 varieties of human capital convergence among cities. In particular, this model predicts population shock resulting from the processes of migration choice and echelon migration.
Abstract: The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Abstract: This paper aims to argue that religion and Faith-based
Organizations (FBOs) contribute to building democratic process
through the provision of education in Sierra Leone. Sierra Leone
experienced a civil war from 1991 to 2002 and about 70 percent of the
population lives in poverty. While the government has been in the
process of rebuilding the nation, many forms of Civil Society
Organizations (CSOs), including FBOs, have played a significant role
in promoting social development. Education plays an important role in
supporting people-s democratic movements through knowledge
acquisition, spiritual enlightenment and empowerment. This paper
discusses religious tolerance in Sierra Leone and how FBOs have
contributed to the provision of primary education in Sierra Leone. This
study is based on the author-s field research, which involved
interviews with teachers and development stakeholders, notably
government officials, Non-governmental Organizations (NGOs) and
FBOs, as well as questionnaires completed by pupils, parents and
teachers.
Abstract: Wavelet transform provides several important
characteristics which can be used in a texture analysis and
classification. In this work, an efficient texture classification method,
which combines concepts from wavelet and co-occurrence matrices,
is presented. An Euclidian distance classifier is used to evaluate the
various methods of classification. A comparative study is essential to
determine the ideal method. Using this conjecture, we developed a
novel feature set for texture classification and demonstrate its
effectiveness
Abstract: In this paper, we present a vertical nanowire thin film transistor with gate-all-around architecture, fabricated using CMOS compatible processes. A novel method of fabricating polysilicon vertical nanowires of diameter as small as 30 nm using wet-etch is presented. Both n-type and p-type vertical poly-silicon nanowire transistors exhibit superior electrical characteristics as compared to planar devices. On a poly-crystalline nanowire of 30 nm diameter, high Ion/Ioff ratio of 106, low drain-induced barrier lowering (DIBL) of 50 mV/V, and low sub-threshold slope SS~100mV/dec are demonstrated for a device with channel length of 100 nm.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.
Abstract: In the project FleGSens, a wireless sensor network
(WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information
security. The intended prototype consists of 200 sensor nodes for
monitoring a 500m long land strip. The system is focused on ensuring
integrity and authenticity of generated alarms and availability in the
presence of an attacker who may even compromise a limited number
of sensor nodes. In this paper, two of the main protocols developed
in the project are presented, a tracking protocol to provide secure
detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks
containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols
and particularly demonstrating the impact and cost of several attacks.
Abstract: This paper presents an integrated knowledge-based
approach to multi-scale modeling of aquatic systems, with a view to
enhancing predictive power and aiding environmental management
and policy-making. The basic phases of this approach have been
exemplified in the case of a bay in Saronicos Gulf (Attiki, Greece).
The results showed a significant problem with rising phytoplankton
blooms linked to excessive microbial growth, arisen mostly due to
increased nitrogen inflows; therefore, the nitrification/denitrification
processes of the benthic and water column sub-systems have
provided the quality variables to be monitored for assessing
environmental status. It is thereby demonstrated that the proposed
approach facilitates modeling choices and implementation option
decisions, while it provides substantial support for knowledge and
experience capitalization in long-term water management.
Abstract: Impinging jets are widely used in industrial cooling
systems for their high heat transfer characteristics at stagnation points.
However, the heat transfer characteristics are low in the downstream
direction. In order to improve the heat transfer coefficient further
downstream, investigations introducing ribs on jet-cooled flat plates
have been conducted. Most studies regarding the heat-transfer
enhancement using a rib-roughened wall have dealt with the rib pitch.
In this paper, we focused on the rib spacing and demonstrated that the
rib spacing must be more than 6 times the nozzle width to improve heat
transfer at Reynolds number Re=5.0×103 because it is necessary to
have enough space to allow reattachment of flow behind the first rib.