Abstract: There are many problems associated with the World Wide
Web: getting lost in the hyperspace; the web content is still accessible only
to humans and difficulties of web administration. The solution to these
problems is the Semantic Web which is considered to be the extension
for the current web presents information in both human readable and
machine processable form. The aim of this study is to reach new
generic foundation architecture for the Semantic Web because there
is no clear architecture for it, there are four versions, but still up to
now there is no agreement for one of these versions nor is there a
clear picture for the relation between different layers and
technologies inside this architecture. This can be done depending on
the idea of previous versions as well as Gerber-s evaluation method
as a step toward an agreement for one Semantic Web architecture.
Abstract: Since dealing with high dimensional data is
computationally complex and sometimes even intractable, recently
several feature reductions methods have been developed to reduce
the dimensionality of the data in order to simplify the calculation
analysis in various applications such as text categorization, signal
processing, image retrieval, gene expressions and etc. Among feature
reduction techniques, feature selection is one the most popular
methods due to the preservation of the original features.
In this paper, we propose a new unsupervised feature selection
method which will remove redundant features from the original
feature space by the use of probability density functions of various
features. To show the effectiveness of the proposed method, popular
feature selection methods have been implemented and compared.
Experimental results on the several datasets derived from UCI
repository database, illustrate the effectiveness of our proposed
methods in comparison with the other compared methods in terms of
both classification accuracy and the number of selected features.
Abstract: Educational institutions are increasingly exploring the affordances of 3D virtual worlds for instruction and research, but few studies have been done to document current practices and uses of this emerging technology. This observational survey examines the virtual presences of 170 accredited educational institutions found in one such 3D virtual world called Second Life®, created by San- Francisco based Linden Lab®. The study focuses on what educational institutions look like in this virtual environment, the types of spaces educational institutions are creating or simulating, and what types of activities are being conducted.
Abstract: This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.
Abstract: Customarily, the LMTD correction factor, FT, is used
to screen alternative designs for a heat exchanger. Designs with
unacceptably low FT values are discarded. In this paper, authors have
proposed a more fundamental criterion, based on feasibility of a
multipass exchanger as the only criteria, followed by economic
optimization. This criterion, coupled with asymptotic energy targets,
provide the complete optimization space in a heat exchanger network
(HEN), where cost-optimization of HEN can be performed with only
Heat Recovery Approach temperature (HRAT) and number-of-shells
as variables.
Abstract: In this study, we used shape memory alloys as
actuators to build a biomorphic robot which can imitate the motion of
an earthworm. The robot can be used to explore in a narrow space.
Therefore we chose shape memory alloys as actuators. Because of the
small deformation of a wire shape memory alloy, spiral shape memory
alloys are selected and installed both on the X axis and Y axis (each
axis having two shape memory alloys) to enable the biomorphic robot
to do reciprocating motion. By the mechanism we designed, the robot
can increase the distance as it moves in a duty cycle. In addition, two
shape memory alloys are added to the robot head for controlling right
and left turns. By sending pulses through the I/O card from the
controller, the signals are then amplified by a driver to heat the shape
memory alloys in order to make the SMA shrink to pull the mechanism
to move.
Abstract: The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease.
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: With the explosive growth of data available on the
Internet, personalization of this information space become a
necessity. At present time with the rapid increasing popularity of the
WWW, Websites are playing a crucial role to convey knowledge and
information to the end users. Discovering hidden and meaningful
information about Web users usage patterns is critical to determine
effective marketing strategies to optimize the Web server usage for
accommodating future growth. The task of mining useful information
becomes more challenging when the Web traffic volume is enormous
and keeps on growing. In this paper, we propose a intelligent model
to discover and analyze useful knowledge from the available Web
log data.
Abstract: Due to dynamic evolution, the ability of a
manufacturing technology to produce a special product is changing.
Therefore, it is essential to monitor the established techniques and
processes to detect whether a company-s production will fit future
circumstances. Concerning the manufacturing technology planning
process, companies must decide when to change to a new technology
for maintaining and increasing competitive advantages. In this
context, the maturity assessment of the focused technologies is
crucial. This article presents an approach for defining the maturity of
a manufacturing technology from a strategic point of view. The
concept is based on the approach of technology readiness level
(TRL) according to NASA (National Aeronautics and Space
Administration), but also includes dynamic changes. Therefore, the
model takes into account the concept of the technology life cycle.
Furthermore, it enables a company to estimate the ideal date for
implementation of a new manufacturing technology.
Abstract: In the present work, we propose a new method for
solving the matrix equation AXB=F . The new method can
be considered as a generalized form of the well-known global full
orthogonalization method (Gl-FOM) for solving multiple linear
systems. Hence, the method will be called extended Gl-FOM (EGl-
FOM). For implementing EGl-FOM, generalized forms of block
Krylov subspace and global Arnoldi process are presented. Finally,
some numerical experiments are given to illustrate the efficiency of
our new method.
Abstract: A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.
Abstract: This paper describes the design and modeling
procedure of a novel 5-phase segment type switched reluctance motor
(ST-SRM) under simultaneous two-phase (bipolar) excitation of
windings. The rotor cores of ST-SRM are embedded in an aluminum
block as well as to improve the performance characteristics. The
magnetic circuit of the produced ST-SRM is constructed so that the
magnetic flux paths are short and exclusive to each phase, thereby
minimizing the commutation switching and eddy current losses in the
laminations. The design and simulation principles presented apply
primarily to conventional SRM and ST-SRM. It is proved that the
novel 5-phase switched reluctance motor under two-phase excitation
is superior among the criteria used in comparison. The purposed
model is particularly well suited for high torque and weight
constrained applications such as automobiles, aerospace and military
applications.
Abstract: We present new finite element methods for Helmholtz and Maxwell equations on general three-dimensional polyhedral meshes, based on domain decomposition with boundary elements on the surfaces of the polyhedral volume elements. The methods use the lowest-order polynomial spaces and produce sparse, symmetric linear systems despite the use of boundary elements. Moreover, piecewise constant coefficients are admissible. The resulting approximation on the element surfaces can be extended throughout the domain via representation formulas. Numerical experiments confirm that the convergence behavior on tetrahedral meshes is comparable to that of standard finite element methods, and equally good performance is attained on more general meshes.
Abstract: In this paper the optimal control strategy for
Permanent Magnet Synchronous Motor (PMSM) based drive system
is presented. The designed full optimal control is available for speed
operating range up to base speed. The optimal voltage space-vector
assures input energy reduction and stator loss minimization,
maintaining the output energy in the same limits with the
conventional PMSM electrical drive. The optimal control with three
components is based on the energetically criteria and it is applicable
in numerical version, being a nonrecursive solution. The simulation
results confirm the increased efficiency of the optimal PMSM drive.
The properties of the optimal voltage space vector are shown.
Abstract: This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: This paper presents a comparison between two Pulse
Width Modulation (PWM) algorithms applied to a three-level Neutral
Point Clamped (NPC) Voltage Source Inverter (VSI). The first
algorithm applied is the triangular-sinusoidal strategy; the second is
the Space Vector Pulse Width Modulation (SVPWM) strategy. In the
first part, we present a topology of three-level NCP VSI. After that,
we develop the two PWM strategies to control this converter. At the
end the experimental results are presented.
Abstract: The paper deals with an analysis of visibility records collected from 210 European airports to obtain a realistic estimation of the availability of Free Space Optical (FSO) data links. Commercially available optical links usually operate in the 850nm waveband. Thus the influence of the atmosphere on the optical beam and on the visible light is similar. Long-term visibility records represent an invaluable source of data for the estimation of the quality of service of FSO links. The model used characterizes both the statistical properties of fade depths and the statistical properties of individual fade durations. Results are presented for Italy, France, and Germany.