Abstract: An ontology is widely used in many kinds of applications as a knowledge representation tool for domain knowledge. However, even though an ontology schema is well prepared by domain experts, it is tedious and cost-intensive to add instances into the ontology. The most confident and trust-worthy way to add instances into the ontology is to gather instances from tables in the related Web pages. In automatic populating of instances, the primary task is to find the most proper concept among all possible concepts within the ontology for a given table. This paper proposes a novel method for this problem by defining the similarity between the table and the concept using the overlap of their properties. According to a series of experiments, the proposed method achieves 76.98% of accuracy. This implies that the proposed method is a plausible way for automatic ontology population from Web tables.
Abstract: Curriculum is one of the most important inputs in higher education system and for knowing the strong and weak spots of it we need evaluation. The main purpose of this study was to survey of the curriculum quality of Insurance Management field. Case: University of Allameh Taba Tabaee(according to view point of students,alumni,employer and faculty members).Descriptive statistics (mean, tables, percentages, frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criterions considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. objectives, teaching and learning methods criterions was desirable level, content criteria was undesirable level, space and facilities, time and assessment of learning were rather desirable level. The quality of curriculum of insurance management field was relatively desirable level.
Abstract: Multi-agent communication of Semantic Web
information cannot be realized without the need to reason with
ontology and agent locations. This is because for an agent to be able to
reason with an external semantic web ontology, it must know where
and how to access to that ontology. Similarly, for an agent to be able to
communicate with another agent, it must know where and how to send
a message to that agent. In this paper we propose a framework of an
agent which can reason with ontology and agent locations in order to
perform reasoning with multiple distributed ontologies and perform
communication with other agents on the semantic web. The agent
framework and its communication mechanism are formulated entirely
in meta-logic.
Abstract: The special constraints of sensor networks impose a
number of technical challenges for employing them. In this review,
we study the issues and existing protocols in three areas: coverage
and routing. We present two types of coverage problems: to
determine the minimum number of sensor nodes that need to perform
active sensing in order to monitor a certain area; and to decide the
quality of service that can be provided by a given sensor network.
While most routing protocols in sensor networks are data-centric,
there are other types of routing protocols as well, such as
hierarchical, location-based, and QoS-aware. We describe and
compare several protocols in each group. We present several multipath
routing protocols and single-path with local repair routing
protocols, which are proposed for recovering from sensor node
crashes. We also discuss some transport layer schemes for reliable
data transmission in lossy wireless channels.
Abstract: The reluctance motor is an electric motor in which
torque is produced by the tendency of its moveable part to move to a
position where the inductance of the excited winding is maximized.
In this paper switched reluctance motors (SRMs) with two different
configurations(3-phase SRM with 4rotor poles and 6 stator poles, 4-
phase SRM with 6rotor poles and 8 stator poles) is designed by
RMxprt, and performance of them is analyzed. Efficiency and torque
of SRM for different configurations in full-load condition have been
presented. The results indicate that with correct choosing of motor
applications, maximum efficiency can be found.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.
Abstract: As one of the big government bank, Bank X is paying attention its performance, so that it can compete. One of them is the existence of organizational culture which recognized with term TIPEC (Trust, Integrity, Professionalism, Costumer Focus, and Excellence). In application of organizational culture, it is needed the existence of employee involvement (job involvement). It can be influenced by various factors, such as Locus of Control. Related to above mentioned, the problems are how employee tendency of Locus of Control, how job involvement, how organizational culture applied by employees and how influence of Locus of Control and job involvement to the organizational culture applied by employees. Researchers collected data with questioner spreading, and respondents number of 30 people. After that, the data were analyzed with SPSS software constructively. The influence of Locus of Control and job involvement to the application of organizational culture was strong, i.e. 58.3%.
Abstract: Land use change, if not based on proper scientific
investigation affects other physical, chemical, and biological
properties of soil and leading to increased destruction and erosion. It
was imperative to study the effects of changing rangelands to
farmlands on some Soil quality indexes. Undisturbed soil samples
were collected from the depths of 0-10 and 10-30 centimeter in
pasture with good vegetation cover(GP), pasture with medium
vegetation cover(MP), abandoned dry land farming(ADF) and
degraded dry land farming(DDF) land uses in Ghareh Aghaj
watershed of Isfahan province. The results revealed that organic
matter(OM), cation exchange capacity(CEC) and available
potassium(AK) decreasing in the depth of 0-10 centimeter were 66.6,
38.8 and 70 percent and in the depth of 10-30 centimeter were 58,
61.4 and 83.5 percent respectively in DDF comparison with GP.
Concerning to the results, it seems that land use change can decrease
soil quality and increase soil degradation and lead in undesirable
consequences.
Abstract: World has entered in 21st century. The technology of
computer graphics and digital cameras is prevalent. High resolution
display and printer are available. Therefore high resolution images
are needed in order to produce high quality display images and high
quality prints. However, since high resolution images are not usually
provided, there is a need to magnify the original images. One
common difficulty in the previous magnification techniques is that of
preserving details, i.e. edges and at the same time smoothing the data
for not introducing the spurious artefacts. A definitive solution to this
is still an open issue. In this paper an image magnification using
adaptive interpolation by pixel level data-dependent geometrical
shapes is proposed that tries to take into account information about
the edges (sharp luminance variations) and smoothness of the image.
It calculate threshold, classify interpolation region in the form of
geometrical shapes and then assign suitable values inside
interpolation region to the undefined pixels while preserving the
sharp luminance variations and smoothness at the same time.
The results of proposed technique has been compared qualitatively
and quantitatively with five other techniques. In which the qualitative
results show that the proposed method beats completely the Nearest
Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The
quantitative results are competitive and consistent with NN, BL, BC
and others.
Abstract: Space Vector Pulse Width Modulation SVPWM is
one of the most used techniques to generate sinusoidal voltage and
current due to its facility and efficiency with low harmonics
distortion. This algorithm is specially used in power electronic
applications. This paper describes simulation algorithm of SVPWM
& SPWM using MatLab/simulink environment. It also implements a
closed loop three phases DC-AC converter controlling its outputs
voltages amplitude and frequency using MatLab. Also comparison
between SVPWM & SPWM results is given.
Abstract: This paper introduces an automatic voice classification
system for the diagnosis of individual constitution based on Sasang
Constitutional Medicine (SCM) in Traditional Korean Medicine
(TKM). For the developing of this algorithm, we used the voices of
309 female speakers and extracted a total of 134 speech features from
the voice data consisting of 5 sustained vowels and one sentence. The
classification system, based on a rule-based algorithm that is derived
from a non parametric statistical method, presents 3 types of decisions:
reserved, positive and negative decisions. In conclusion, 71.5% of the
voice data were diagnosed by this system, of which 47.7% were
correct positive decisions and 69.7% were correct negative decisions.
Abstract: The rapid advance of communication technology is
evolving the network environment into the broadband convergence
network. Likewise, the IT services operated in the individual network
are also being quickly converged in the broadband convergence
network environment. VoIP and IPTV are two examples of such new
services. Efforts are being made to develop the video phone service,
which is an advanced form of the voice-oriented VoIP service.
However, the new IT services will be subject to stability and reliability
vulnerabilities if the relevant security issues are not answered during
the convergence of the existing IT services currently being operated in
individual networks within the wider broadband network
environment. To resolve such problems, this paper attempts to analyze
the possible threats and identify the necessary security measures
before the deployment of the new IT services. Furthermore, it
measures the quality of the encryption algorithm application example
to describe the appropriate algorithm in order to present security
technology that will have no negative impact on the quality of the
video phone service.
Abstract: Dealing with hundreds of features in character
recognition systems is not unusual. This large number of features
leads to the increase of computational workload of recognition
process. There have been many methods which try to remove
unnecessary or redundant features and reduce feature dimensionality.
Besides because of the characteristics of Farsi scripts, it-s not
possible to apply other languages algorithms to Farsi directly. In this
paper some methods for feature subset selection using genetic
algorithms are applied on a Farsi optical character recognition (OCR)
system. Experimental results show that application of genetic
algorithms (GA) to feature subset selection in a Farsi OCR results in
lower computational complexity and enhanced recognition rate.
Abstract: Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.
Abstract: In this paper, the Tabu search algorithm is used to
solve a transportation problem which consists of determining the
shortest routes with the appropriate vehicle capacity to facilitate the
travel of the students attending the University of Mauritius. The aim
of this work is to minimize the total cost of the distance travelled by
the vehicles in serving all the customers. An initial solution is
obtained by the TOUR algorithm which basically constructs a giant
tour containing all the customers and partitions it in an optimal way
so as to produce a set of feasible routes. The Tabu search algorithm
then makes use of a search procedure, a swapping procedure and the
intensification and diversification mechanism to find the best set of
feasible routes.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: We have developed an energy based approach for identifying the binding sites and important residues for binding in protein-protein complexes. We found that the residues and residuepairs with charged and aromatic side chains are important for binding. These residues influence to form cation-¤Ç, electrostatic and aromatic interactions. Our observation has been verified with the experimental binding specificity of protein-protein complexes and found good agreement with experiments. The analysis on surrounding hydrophobicity reveals that the binding residues are less hydrophobic than non-binding sites, which suggests that the hydrophobic core are important for folding and stability whereas the surface seeking residues play a critical role in binding. Further, the propensity of residues in the binding sites of receptors and ligands, number of medium and long-range contacts, and influence of neighboring residues will be discussed.
Abstract: Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model of communication system having Quadrature amplitude modulation and Rician fading channel is implemented using MATLAB communication block set. Bit error rate and number of errors is evaluated for RLS and LMS equalizer algorithm, due to change in Signal to Noise Ratio (SNR) and fading component gain in Rician fading Channel.
Abstract: There are few studies on eggshell of leatherback turtle
which is endangered species in Thailand. This study was focusing on
the ultrastructure and elemental composition of leatherback turtle
eggshells collected from Andaman Sea Shore, Thailand during the
nesting season using scanning electron microscope (SEM). Three
eggshell layers of leatherback turtle; the outer cuticle layer or
calcareous layer, the middle layer or middle multistrata layer and the
inner fibrous layer were recognized. The outer calcareous layer was
thick and porosity which consisted of loose nodular units of various
crystal shapes and sizes. The loose attachment between these units
resulted in numerous spaces and openings. The middle layer was
compact thick with several multistrata and contained numerous
openings connecting to both outer cuticle layer and inner fibrous
layer. The inner fibrous layer was compact and thin, and composed of
numerous reticular fibers. Energy dispersive X-ray microanalysis
detector revealed energy spectrum of X-rays character emitted from
all elements on each layer. The percentages of all elements were
found in the following order: carbon (C) > oxygen (O) > calcium
(Ca) > sulfur (S) > potassium (K) > aluminum (Al) > iodine (I) >
silicon (Si) > chlorine (Cl) > sodium (Na) > fluorine (F) >
phosphorus (P) > magnesium (Mg). Each layer consisted of high
percentage of CaCO3 (approximately 98%) implying that it was
essential for turtle embryonic development. A significant difference
was found in the percentages of Ca and Mo in the 3layers. Moreover,
transition metal, metal and toxic non-metal contaminations were
found in leatherback turtle eggshell samples. These were palladium
(Pd), molybdenum (Mo), copper (Cu), aluminum (Al), lead (Pb), and
bromine (Br). The contamination elements were seen in the outer
layers except for Mo. All elements were readily observed and
mapped using Smiling program. X-ray images which mapped the
location of all elements were showed. Calcium containing in the
eggshell appeared in high contents and was widely distributing in
clusters of the outer cuticle layer to form CaCO3 structure. Moreover,
the accumulation of Na and Cl was observed to form NaCl which was
widely distributing in 3 eggshell layers. The results from this study
would be valuable on assessing the emergent success in this
endangered species.
Abstract: The paper studies implications between knowledge spillovers and technological innovation capability in the following three aspects: firstly, the paper debates on the effect of knowledge spillover on some perspectives of technological innovation ability; secondly, it discusses how different roles of knowledge spillover affect the technological innovation capability; finally, the paper creates the model of the factors of knowledge spillovers influencing to technological innovation capability. It concludes that knowledge spillovers affect all the main aspects of technological innovation ultimately to impact of technological innovation capabilities.