Abstract: A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise
Abstract: Recently, fast neural networks for object/face
detection were presented in [1-3]. The speed up factor of these
networks relies on performing cross correlation in the frequency
domain between the input image and the weights of the hidden
layer. But, these equations given in [1-3] for conventional and fast
neural networks are not valid for many reasons presented here. In
this paper, correct equations for cross correlation in the spatial and
frequency domains are presented. Furthermore, correct formulas for
the number of computation steps required by conventional and fast
neural networks given in [1-3] are introduced. A new formula for
the speed up ratio is established. Also, corrections for the equations
of fast multi scale object/face detection are given. Moreover,
commutative cross correlation is achieved. Simulation results show
that sub-image detection based on cross correlation in the frequency
domain is faster than classical neural networks.
Abstract: Multi User Virtual Worlds are becoming a valuable educational tool. Learning experiences within these worlds focus on discovery and active experiences that both engage students and motivate them to explore new concepts. As educators, we need to explore these environments to determine how they can most effectively be used in our instructional practices. This paper explores the current application of virtual worlds to identify meaningful educational strategies that are being used to engage students and enhance teaching and learning.
Abstract: In this paper, we present the video quality measure
estimation via a neural network. This latter predicts MOS (mean
opinion score) by providing height parameters extracted from
original and coded videos. The eight parameters that are used are: the
average of DFT differences, the standard deviation of DFT
differences, the average of DCT differences, the standard deviation
of DCT differences, the variance of energy of color, the luminance
Y, the chrominance U and the chrominance V. We chose Euclidean
Distance to make comparison between the calculated and estimated
output.
Abstract: In the present work, a study has been made on the combination of the electrical discharge machining (EDM) with ultrasonic vibrations to improve the machining efficiency. In experiments the graphite used as tool electrode and material of workpiece was AISIH13 tool steel. The parameters such as discharge peak current and pulse duration were changed to explore their effect on the material removal rate (MRR), relative tool wear ratio (TWR) and surface roughness. From the experimental result it can be seen that ultrasonic vibration of the workpiece can significantly reduces the inactive pulses and improves the stability of process. It was found that ultrasonic assisted EDM (US-EDM) is effective in attaining a high material removal rate (MRR) in finishing regime.
Abstract: The belief decision tree (BDT) approach is a decision
tree in an uncertain environment where the uncertainty is represented
through the Transferable Belief Model (TBM), one interpretation
of the belief function theory. The uncertainty can appear either in
the actual class of training objects or attribute values of objects to
classify. In this paper, we develop a post-pruning method of belief
decision trees in order to reduce size and improve classification
accuracy on unseen cases. The pruning of decision tree has a
considerable intention in the areas of machine learning.
Abstract: This paper considers the autonomous navigation
problem of multiple n-link nonholonomic mobile manipulators within
an obstacle-ridden environment. We present a set of nonlinear
acceleration controllers, derived from the Lyapunov-based control
scheme, which generates collision-free trajectories of the mobile
manipulators from initial configurations to final configurations in a
constrained environment cluttered with stationary solid objects of
different shapes and sizes. We demonstrate the efficiency of the
control scheme and the resulting acceleration controllers of the
mobile manipulators with results through computer simulations of an
interesting scenario.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: A numerical study is presented on buckling and post
buckling behaviour of laminated carbon fiber reinforced plastic
(CFRP) thin-walled cylindrical shells under axial compression using
asymmetric meshing technique (AMT). Asymmetric meshing
technique is a perturbation technique to introduce disturbance without
changing geometry, boundary conditions or loading conditions.
Asymmetric meshing affects predicted buckling load, buckling mode
shape and post-buckling behaviour. Linear (eigenvalue) and nonlinear
(Riks) analyses have been performed to study the effect of
asymmetric meshing in the form of a patch on buckling behaviour.
The reduction in the buckling load using Asymmetric meshing
technique was observed to be about 15%. An isolated dimple formed
near the bifurcation point and the size of which increased to reach a
stable state in the post-buckling region. The load-displacement curve
behaviour applying asymmetric meshing is quite similar to the curve
obtained using initial geometric imperfection in the shell model.
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: There are only limited studies that directly correlate
the increase in reinforced concrete (RC) panel structural capacities in
resisting the blast loads with different RC panel structural properties
in terms of blast loading characteristics, RC panel dimensions, steel
reinforcement ratio and concrete material strength. In this paper,
numerical analyses of dynamic response and damage of the one-way
RC panel to blast loads are carried out using the commercial software
LS-DYNA. A series of simulations are performed to predict the blast
response and damage of columns with different level and magnitude
of blast loads. The numerical results are used to develop pressureimpulse
(P-I) diagrams of one-way RC panels. Based on the
numerical results, the empirical formulae are derived to calculate the
pressure and impulse asymptotes of the P-I diagrams of RC panels.
The results presented in this paper can be used to construct P-I
diagrams of RC panels with different concrete and reinforcement
properties. The P-I diagrams are very useful to assess panel capacities
in resisting different blast loads.
Abstract: Cameras are often mounted on platforms that canmove like rovers, booms, gantries and aircraft. People operate suchplatforms to capture desired views of scene or target. To avoidcollisions with the environment and occlusions, such platforms oftenpossess redundant degrees-of-freedom. As a result, manipulatingsuch platforms demands much skill. Visual-servoing some degrees-of-freedom may reduce operator burden and improve tracking per-formance. This concept, which we call human-in-the-loop visual-servoing, is demonstrated in this paper and applies a Α-β-γ filter and feedforward controller to a broadcast camera boom.
Abstract: It has been established that microRNAs (miRNAs) play
an important role in gene expression by post-transcriptional regulation
of messengerRNAs (mRNAs). However, the precise relationships
between microRNAs and their target genes in sense of numbers,
types and biological relevance remain largely unclear. Dissecting the
miRNA-target relationships will render more insights for miRNA
targets identification and validation therefore promote the understanding
of miRNA function. In miRBase, miRanda is the key
algorithm used for target prediction for Zebrafish. This algorithm
is high-throughput but brings lots of false positives (noise). Since
validation of a large scale of targets through laboratory experiments
is very time consuming, several computational methods for miRNA
targets validation should be developed. In this paper, we present an
integrative method to investigate several aspects of the relationships
between miRNAs and their targets with the final purpose of extracting
high confident targets from miRanda predicted targets pool. This is
achieved by using the techniques ranging from statistical tests to
clustering and association rules. Our research focuses on Zebrafish.
It was found that validated targets do not necessarily associate with
the highest sequence matching. Besides, for some miRNA families,
the frequency of their predicted targets is significantly higher in the
genomic region nearby their own physical location. Finally, in a case
study of dre-miR-10 and dre-miR-196, it was found that the predicted
target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR-
10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar
characteristics as validated target genes and therefore represent high
confidence target candidates.
Abstract: In this paper, Steam Assisted Gravity Drainage
(SAGD) is introduced and its advantages over ordinary steam
injection is demonstrated. A simple simulation model is built and
three scenarios of natural production, ordinary steam injection, and
SAGD are compared in terms of their cumulative oil production and
cumulative oil steam ratio. The results show that SAGD can
significantly enhance oil production in quite a short period of time.
However, since the distance between injection and production wells
is short, the oil to steam ratio decreases gradually through time.
Abstract: Forming a legal culture among citizens is a
complicated and lengthy process, influencing all spheres of social
life. It includes promoting justice, learning rights and duties, the
introduction of juridical norms and knowledge, and also a process of
developing a system of legal acts and constitutional norms. Currently,
the evaluative and emotional influence of attempts to establish a legal
culture among the citizens of Kazakhstan is limited by real legal
practice. As a result, the values essential to a sound civil society are
absent from the consciousness of the Kazakh people who are thus, in
turn, not able to develop respect for these values. One of the
disadvantages of the modern Kazakh educational system is a
tendency to underrate the actual forces shaping the worldview of
Kazakh youths. The mass-media, which are going through a
personnel crisis, cannot provide society with the legal and political
information necessary to form the sort of legal culture required for a
true civil society.
Abstract: A new code synchronization algorithm is proposed in
this paper for the secondary cell-search stage in wideband CDMA
systems. Rather than using the Cyclically Permutable (CP) code in the
Secondary Synchronization Channel (S-SCH) to simultaneously
determine the frame boundary and scrambling code group, the new
synchronization algorithm implements the same function with less
system complexity and less Mean Acquisition Time (MAT). The
Secondary Synchronization Code (SSC) is redesigned by splitting into
two sub-sequences. We treat the information of scrambling code group
as data bits and use simple time diversity BCH coding for further
reliability. It avoids involved and time-costly Reed-Solomon (RS)
code computations and comparisons. Analysis and simulation results
show that the Synchronization Error Rate (SER) yielded by the new
algorithm in Rayleigh fading channels is close to that of the
conventional algorithm in the standard. This new synchronization
algorithm reduces system complexities, shortens the average
cell-search time and can be implemented in the slot-based cell-search
pipeline. By taking antenna diversity and pipelining correlation
processes, the new algorithm also shows its flexible application in
multiple antenna systems.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: The Internet has become an indispensable part of our lives. Witnessing recent web-based mass collaboration, e.g. Wikipedia, people are questioning whether the Internet has made fundamental changes to the society or whether it is merely a hyperbolic fad. It has long been assumed that collective action for a certain goal yields the problem of free-riding, due to its non-exclusive and non-rival characteristics. Then, thanks to recent technological advances, the on-line space experienced the following changes that enabled it to produce public goods: 1) decrease in the cost of production or coordination 2) externality from networked structure 3) production function which integrates both self-interest and altruism. However, this research doubts the homogeneity of on-line mass collaboration and argues that a more sophisticated and systematical approach is required. The alternative that we suggest is to connect the characteristics of the goal to the motivation. Despite various approaches, previous literature fails to recognize that motivation can be structurally restricted by the characteristic of the goal. First we draw a typology of on-line mass collaboration with 'the extent of expected beneficiary' and 'the existence of externality', and then we examine each combination of motivation using Benkler-s framework. Finally, we explore and connect such typology with its possible dominant participating motivation.
Abstract: In this paper, we present a system for content-based
retrieval of large database of classified satellite images, based on
user's relevance feedback (RF).Through our proposed system, we
divide each satellite image scene into small subimages, which stored
in the database. The modified radial basis functions neural network
has important role in clustering the subimages of database according
to the Euclidean distance between the query feature vector and the
other subimages feature vectors. The advantage of using RF
technique in such queries is demonstrated by analyzing the database
retrieval results.
Abstract: An experiment was conducted with 80 unsexed
broilers of the Arbor Acress strain to determine the capability of a
carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado,
orange, melon and Dutch egg plant) in the same proportion for
replacing corn in broiler diet. This study involved a completely
randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of
juice wastes mixture in diets) and 4 replicates per treatment. Diets
were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg
diet). Measured variables were feed consumption, average daily
gain, feed conversion, as well as percentages of abdominal fat pad,
carcass, digestive organs (liver, pancreas and gizzard), and heart.
Data were analyzed by analysis of variance for CRD. Increasing
juice wastes mixture levels in diets increased feed consumption
(P