Abstract: Equilibrium and stability equations of a thin rectangular plate with length a, width b, and thickness h(x)=C1x+C2, made of functionally graded materials under thermal loads are derived based on the first order shear deformation theory. It is assumed that the material properties vary as a power form of thickness coordinate variable z. The derived equilibrium and buckling equations are then solved analytically for a plate with simply supported boundary conditions. One type of thermal loading, uniform temperature rise and gradient through the thickness are considered, and the buckling temperatures are derived. The influences of the plate aspect ratio, the relative thickness, the gradient index and the transverse shear on buckling temperature difference are all discussed.
Abstract: Primary studies are being carried out in Turkey for
expanding information and communication technologies (ICT) aided instruction activities. Subject of the present study is to identify
whether those studies achieved their goals in the application. Information technologies (IT) formative teachers in the primary
schools, and academicians in the faculties of education were interviewed to investigate the process and results of implementing
computer-aided instruction methods whose basis is strengthened in theory. Analysis of the results gained from two separate surveys
demonstrated that capability of the teachers in elementary education institutions for carrying into effect computer-aided instruction and
technical infrastructure has not been established for computer-aided instruction practices yet. Prospective teachers must be well-equipped in ICT to duly fulfill requirements of modern education and also
must be self-confident. Finally, scope and intensity of the courses given in connection with teaching of the ICT in faculties of education needs to be revised.
Abstract: Mining Sequential Patterns in large databases has become
an important data mining task with broad applications. It is
an important task in data mining field, which describes potential
sequenced relationships among items in a database. There are many
different algorithms introduced for this task. Conventional algorithms
can find the exact optimal Sequential Pattern rule but it takes a
long time, particularly when they are applied on large databases.
Nowadays, some evolutionary algorithms, such as Particle Swarm
Optimization and Genetic Algorithm, were proposed and have been
applied to solve this problem. This paper will introduce a new kind
of hybrid evolutionary algorithm that combines Genetic Algorithm
(GA) with Particle Swarm Optimization (PSO) to mine Sequential
Pattern, in order to improve the speed of evolutionary algorithms
convergence. This algorithm is referred to as SP-GAPSO.
Abstract: Schema matching plays a key role in many different
applications, such as schema integration, data integration, data
warehousing, data transformation, E-commerce, peer-to-peer data
management, ontology matching and integration, semantic Web,
semantic query processing, etc. Manual matching is expensive and
error-prone, so it is therefore important to develop techniques to
automate the schema matching process. In this paper, we present a
solution for XML schema automated matching problem which
produces semantic mappings between corresponding schema
elements of given source and target schemas. This solution
contributed in solving more comprehensively and efficiently XML
schema automated matching problem. Our solution based on
combining linguistic similarity, data type compatibility and structural
similarity of XML schema elements. After describing our solution,
we present experimental results that demonstrate the effectiveness of
this approach.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.
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: 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: 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: We present the development of a system of programs designed for the compilation and execution of applications for handheld computers. In introduction we describe the purpose of the project and its components. The next two paragraphs present the first two components of the project (the scanner and parser generators). Then we describe the Object Pascal compiler and the virtual machines for Windows and Palm OS. In conclusion we emphasize the ways in which the project can be extended.
Abstract: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
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: The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.
Abstract: This paper presents a new sufficient condition for the
existence, uniqueness and global asymptotic stability of the equilibrium point for Cohen-Grossberg neural networks with multiple time delays. The results establish a relationship between the network parameters
of the neural system independently of the delay parameters. The results are also compared with the previously reported results in
the literature.
Abstract: Mycophenolic acid “MPA" is a secondary metabolite
of Penicillium bervicompactum with antibiotic and
immunosuppressive properties. In this study, fermentation process
was established for production of mycophenolic acid by Penicillium
bervicompactum MUCL 19011 in shake flask. The maximum MPA
production, product yield and productivity were 1.379 g/L, 18.6 mg/g
glucose and 4.9 mg/L.h respectively. Glucose consumption, biomass
and MPA production profiles were investigated during fermentation
time. It was found that MPA production starts approximately after
180 hours and reaches to a maximum at 280 h. In the next step, the
effects of methionine and acetate concentrations on MPA production
were evaluated. Maximum MPA production, product yield and
productivity (1.763 g/L, 23.8 mg/g glucose and 6.30 mg/L. h
respectively) were obtained with using 2.5 g/L methionine in culture
medium. Further addition of methionine had not more positive effect
on MPA production. Finally, results showed that the addition of
acetate to the culture medium had not any observable effect on MPA
production.
Abstract: Let G be a graph of order n, and let k 2 and m 0 be two integers. Let h : E(G) [0, 1] be a function. If e∋x h(e) = k holds for each x V (G), then we call G[Fh] a fractional k-factor of G with indicator function h where Fh = {e E(G) : h(e) > 0}. A graph G is called a fractional (k,m)-deleted graph if there exists a fractional k-factor G[Fh] of G with indicator function h such that h(e) = 0 for any e E(H), where H is any subgraph of G with m edges. In this paper, it is proved that G is a fractional (k,m)-deleted graph if (G) k + m + m k+1 , n 4k2 + 2k − 6 + (4k 2 +6k−2)m−2 k−1 and max{dG(x), dG(y)} n 2 for any vertices x and y of G with dG(x, y) = 2. Furthermore, it is shown that the result in this paper is best possible in some sense.
Abstract: Perhaps no single issue has been cited as either the root
cause and / or the greatest challenge to the restructured power system then the lack of adequate reliable transmission. Probabilistic transmission planning has become increasingly necessary and important in recent
years. The transmission planning analysis carried out by the authors,
spans a 10-year horizon, taking into consideration a value of 2 % load
increase / year at each consumer. Taking into consideration this increased
load, a probabilistic power flow was carried out, all the system components
being regarded from probabilistic point of view. Several contingencies
have been generated, for assessing the security of the power system. The results have been analyzed and several important conclusions were pointed. The objective is to achieve a network that works without limit violations for all (or most of) scenario realizations. The case study is represented by the IEEE 14 buses test power system.
Abstract: As emails communications have no consistent
authentication procedure to ensure the authenticity, we present an
investigation analysis approach for detecting forged emails based on
Random Forests and Naïve Bays classifiers. Instead of investigating
the email headers, we use the body content to extract a unique writing
style for all the possible suspects. Our approach consists of four main
steps: (1) The cybercrime investigator extract different effective
features including structural, lexical, linguistic, and syntactic
evidence from previous emails for all the possible suspects, (2) The
extracted features vectors are normalized to increase the accuracy
rate. (3) The normalized features are then used to train the learning
engine, (4) upon receiving the anonymous email (M); we apply the
feature extraction process to produce a feature vector. Finally, using
the machine learning classifiers the email is assigned to one of the
suspects- whose writing style closely matches M. Experimental
results on real data sets show the improved performance of the
proposed method and the ability of identifying the authors with a
very limited number of features.
Abstract: The objective of this research was to find the
relationship between auspicious meaning in eastern wisdom and the
interpretation as a guideline for the design and development of
community souvenirs. The sample group included 400 customers in
Bangkok who used to buy community souvenir products. The
information was applied to design the souvenirs which were
considered for the appropriateness by 5 design specialists. The data
were analyzed to find frequency, percentage, and SD with the results
as follows. 1) The best factor referring to the auspicious meaning is
color. The application of auspicious meaning can make the value
added to the product and bring the fortune to the receivers. 2) The
effectiveness of the auspicious meaning integration on the design of
community souvenir product was in high level. When considering in
each aspect, it was found that the interpretation aspect was in high
level, the congruency of the auspicious meaning and the utility of the
product was in high level. The attractiveness and the good design
were in very high level while the potential of the value added in the
product design was in high level. The suitable application to the
design of community souvenir product was in high level.
Abstract: Drought is a phenomenon caused by
environmental and climatic changes. This phenomenon is
affected by shortage of rainfall and temperature. Dust is one
of important environmental problems caused by climate
change and drought. With recent multi-year drought, many
environmental crises caused by dust in Iran and Middle East.
Dust in the vast areas of the provinces occurs with high
frequency. By dust affecting many problems created in terms
of health, social and economic. In this study, we tried to study
the most important factors causing dust. In this way we have
used the satellite images and meteorological data. Finally,
strategies to deal with the dust will be mentioned.
Abstract: Information theory and Statistics play an important role in Biological Sciences when we use information measures for the study of diversity and equitability. In this communication, we develop the link among the three disciplines and prove that sampling distributions can be used to develop new information measures. Our study will be an interdisciplinary and will find its applications in Biological systems.