Abstract: Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
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: The development incompatible with environment cannot be sustainable. Using renewable energy sources such as solar energy, geothermal energy and wind energy can make sustainable development in a region. Iran has a lot of renewable and nonrenewable energy resources. Since Iran has a special geographic position, it has lot of solar and wind energy resources. Both solar and wind energy are free, renewable and adaptable with environment. The study of 10 year wind data in Iranian South coastal and Islands synoptic stations shows that the production of wind power electricity and water pumping is possible in this region. In this research, we studied the local and temporal distribution of wind using three – hour statistics of windspeed in Iranian South coastal and Islands synoptic stations. This research shows that the production of wind power electricity is possible in this region all the year.
Abstract: Counting people from a video stream in a noisy environment is a challenging task. This project aims at developing a counting system for transport vehicles, integrated in a video surveillance product. This article presents a method for the detection and tracking of multiple faces in a video by using a model of first and second order local moments. An iterative process is used to estimate the position and shape of multiple faces in images, and to track them. the trajectories are then processed to count people entering and leaving the vehicle.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: An iterative algorithm is proposed and tested in Cournot Game models, which is based on the convergence of sequential best responses and the utilization of a genetic algorithm for determining each player-s best response to a given strategy profile of its opponents. An extra outer loop is used, to address the problem of finite accuracy, which is inherent in genetic algorithms, since the set of feasible values in such an algorithm is finite. The algorithm is tested in five Cournot models, three of which have convergent best replies sequence, one with divergent sequential best replies and one with “local NE traps"[14], where classical local search algorithms fail to identify the Nash Equilibrium. After a series of simulations, we conclude that the algorithm proposed converges to the Nash Equilibrium, with any level of accuracy needed, in all but the case where the sequential best replies process diverges.
Abstract: Aiming the application of localized hyperthermia, a
magnetic induction system with new approaches is proposed. The techniques in this system for improving the effectiveness of localized hyperthermia are that using magnetic circuit and the multiple-coil array instead of a giant coil for generating magnetic field. Specially, amorphous metal is adopted as the material of magnetic circuit. Detail
design parameters of hardware are well described. Simulation tool is
employed for this work and experiment result is reported as well.
Abstract: A model to identify the lifetime of target tracking
wireless sensor network is proposed. The model is a static clusterbased
architecture and aims to provide two factors. First, it is to
increase the lifetime of target tracking wireless sensor network.
Secondly, it is to enable good localization result with low energy
consumption for each sensor in the network. The model consists of
heterogeneous sensors and each sensing member node in a cluster
uses two operation modes–active mode and sleep mode. The
performance results illustrate that the proposed architecture consumes
less energy and increases lifetime than centralized and dynamic
clustering architectures, for target tracking sensor network.
Abstract: In automotive systems almost all steps concerning the
calibration of several control systems, e.g., low idle governor or
boost pressure governor, are made with the vehicle because the timeto-
production and cost requirements on the projects do not allow for
the vehicle analysis necessary to build reliable models. Here is
presented a procedure using parametric and NN (neural network)
models that enables the generation of vehicle system models based
on normal ECU engine control unit) vehicle measurements. These
models are locally valid and permit pre and follow-up calibrations so
that, only the final calibrations have to be done with the vehicle.
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: Ethnicity identification of face images is of interest in
many areas of application, but existing methods are few and limited.
This paper presents a fusion scheme that uses block-based uniform
local binary patterns and Haar wavelet transform to combine local
and global features. In particular, the LL subband coefficients of the
whole face are fused with the histograms of uniform local binary
patterns from block partitions of the face. We applied the principal
component analysis on the fused features and managed to reduce the
dimensionality of the feature space from 536 down to around 15
without sacrificing too much accuracy. We have conducted a number
of preliminary experiments using a collection of 746 subject face
images. The test results show good accuracy and demonstrate the
potential of fusing global and local features. The fusion approach is
robust, making it easy to further improve the identification at both
feature and score levels.
Abstract: Quaternary InxAlyGa1-x-yN semiconductors have
attracted much research interest because the use of this quaternary
offer the great flexibility in tailoring their band gap profile while
maintaining their lattice-matching and structural integrity. The
structural and optical properties of InxAlyGa1-x-yN alloys grown by
molecular beam epitaxy (MBE) is presented. The structural quality of
InxAlyGa1-x-yN layers was characterized using high-resolution X-ray
diffraction (HRXRD). The results confirm that the InxAlyGa1-x-yN
films had wurtzite structure and without phase separation. As the In
composition increases, the Bragg angle of the (0002) InxAlyGa1-x-yN
peak gradually decreases, indicating the increase in the lattice constant
c of the alloys. FWHM of (0002) InxAlyGa1-x-yN decreases with
increasing In composition from 0 to 0.04, that could indicate the
decrease of quality of the samples due to point defects leading to
non-uniformity of the epilayers. UV-VIS spectroscopy have been used
to study the energy band gap of InxAlyGa1-x-yN. As the indium (In)
compositions increases, the energy band gap decreases. However, for
InxAlyGa1-x-yN with In composition of 0.1, the band gap shows a
sudden increase in energy. This is probably due to local alloy
compositional fluctuations in the epilayer. The bowing parameter
which appears also to be very sensitive on In content is investigated
and obtained b = 50.08 for quaternary InxAlyGa1-x-yN alloys. From
photoluminescence (PL) measurement, green luminescence (GL)
appears at PL spectrum of InxAlyGa1-x-yN, emitted for all x at ~530 nm
and it become more pronounced as the In composition (x) increased,
which is believed cause by gallium vacancies and related to isolated
native defects.
Abstract: A numerical study on the turbulent flow and heat
transfer characteristics in the rectangular channel with different types
of baffles is carried out. The inclined baffles have the width of 19.8
cm, the square diamond type hole having one side length of 2.55 cm,
and the inclination angle of 5o. Reynolds number is varied between
23,000 and 57,000. The SST turbulence model is applied in the
calculation. The validity of the numerical results is examined by the
experimental data. The numerical results of the flow field depict that
the flow patterns around the different baffle type are entirely different
and these significantly affect the local heat transfer characteristics.
The heat transfer and friction factor characteristics are significantly
affected by the perforation density of the baffle plate. It is found that
the heat transfer enhancement of baffle type II (3 hole baffle) has the
best values.
Abstract: The iris recognition technology is the most accurate,
fast and less invasive one compared to other biometric techniques
using for example fingerprints, face, retina, hand geometry, voice or
signature patterns. The system developed in this study has the
potential to play a key role in areas of high-risk security and can
enable organizations with means allowing only to the authorized
personnel a fast and secure way to gain access to such areas. The
paper aim is to perform the iris region detection and iris inner and
outer boundaries localization. The system was implemented on
windows platform using Visual C# programming language. It is easy
and efficient tool for image processing to get great performance
accuracy. In particular, the system includes two main parts. The first
is to preprocess the iris images by using Canny edge detection
methods, segments the iris region from the rest of the image and
determine the location of the iris boundaries by applying Hough
transform. The proposed system tested on 756 iris images from 60
eyes of CASIA iris database images.
Abstract: The majority of micro-entrepreneurs in Malaysia
operate very small-scaled business activities such as food stalls,
burger stalls, night market hawkers, grocery stores, constructions,
rubber and oil palm small holders, and other agro-based services and
activities. Why are they venturing into entrepreneurship - is it for
survival, out of interest or due to encouragement and assistance from
the local government? And why is it that some micro-entrepreneurs
are lagging behind in entrepreneurship, and what do they need to
rectify this situation so that they are able to progress further?
Furthermore, what are the skills that the micro entrepreneurs should
developed to transform them into successful micro-enterprises and
become small and medium-sized enterprises (SME)? This paper
proposes a 7-Step approach that can serve as a basis for identification
of critical entrepreneurial success factors that enable policy makers,
practitioners, consultants, training managers and other agencies in
developing tools to assist micro business owners. This paper also
highlights the experience of one of the successful companies in
Malaysia that has transformed from micro-enterprise to become a
large organization in less than 10 years.
Abstract: This paper examines the forced convection flow of
incompressible, electrically conducting viscous fluid past a sharp
wedge in the presence of heat generation or absorption with an
applied magnetic field. The system of partial differential equations
governing Falkner - Skan wedge flow and heat transfer is first
transformed into a system of ordinary differential equations using
similarity transformations which is later solved using an implicit
finite - difference scheme, along with quasilinearization technique.
Numerical computations are performed for air (Pr = 0.7) and
displayed graphically to illustrate the influence of pertinent physical
parameters on local skin friction and heat transfer coefficients and,
also on, velocity and temperature fields. It is observed that the
magnetic field increases both the coefficients of skin friction and heat
transfer. The effect of heat generation or absorption is found to be
very significant on heat transfer, but its effect on the skin friction is
negligible. Indeed, the occurrence of overshoot is noticed in the
temperature profiles during heat generation process, causing the
reversal in the direction of heat transfer.
Abstract: Utilization of diverse germplasm is needed to enhance
the genetic diversity of cultivars. The objective of this study was to
evaluate the genetic relationships of 98 alfalfa germplasm accessions
using morphological traits and SSR markers. From the 98 tested
populations, 81 were locals originating in Europe, 17 were introduced
from USA, Australia, New Zealand and Canada. Three primers
generated 67 polymorphic bands. The average polymorphic
information content (PIC) was very high (> 0.90) over all three used
primer combinations. Cluster analysis using Unweighted Pair Group
Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient
grouped the accessions into 2 major clusters with 4 sub-clusters with
no correlation between genetic and morphological diversity. The SSR
analysis clearly indicated that even with three polymorphic primers,
reliable estimation of genetic diversity could be obtained.
Abstract: A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.
Abstract: Global climate change has become the preeminent
threat to human security in the 21st century. From mitigation perspective, this study aims to evaluate the performance of biogas
renewable project under clean development mechanism activities
(namely Korat-Waste-to-Energy) in Thailand and to assess local perceptions towards the significance of climate change mitigation and
sustainability of such project in their community. Questionnaire was
developed based on the national sustainable development criteria and
was distributed among systematically selected households within
project boundaries (n=260). Majority of the respondents strongly agreed with the reduction of odor problems (81%) and air pollution
(76%). However, they were unsure about greenhouse gas reduction from such project and ignorant about the key issues of climate change. A lesson learned suggested that there is a need to further
investigate the possible socio-psychological barriers may significantly shape public perception and understandings of climate
change in the local context.
Abstract: In this work we present some matrix operators named
circulant operators and their action on square matrices. This study on
square matrices provides new insights into the structure of the space
of square matrices. Moreover it can be useful in various fields as in
agents networking on Grid or large-scale distributed self-organizing
grid systems.