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: These paper, we approximate the average run length
(ARL) for CUSUM chart when observation are an exponential first
order moving average sequence (EMA1). We used Gauss-Legendre
numerical scheme for integral equations (IE) method for approximate
ARL0 and ARL1, where ARL in control and out of control,
respectively. We compared the results from IE method and exact
solution such that the two methods perform good agreement.
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: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: These In this work, a regular unit speed curve in six
dimensional Euclidean space, whose Frenet curvatures are constant,
is considered. Thereafter, a method to calculate Frenet apparatus of
this curve is presented.
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: The aim of the study was to investigate phytochemical
properties, antimicrobial activity and cytotoxicity of Aloe vera. The
phytochemical screening of the extracts of leaves of A. vera revealed
the presence of bioactive compounds such as alkaloids, tannins,
flavonoids phenolic compounds, and etc. with absence of cyanogenic
glycosides. Three different solvents such as methanol, ethanol and
Di-Methyl sulfoxide were used to screen the antimicrobial activity of
A. vera leaves against four human clinical pathogens by agar well
diffusion method. The maximum antibacterial activities were
observed in methanol extract followed by ethanol and Di-Methyl
sulfoxide. It was also found that remarkable antibacterial activities
with methanolic and ethanolic extracts of A. vera compared with the
standard antibiotic, tetracycline that was not active against E. coli
and S. boydii and supported the view that A. vera is a potent
antimicrobial agent compared with the conventional antibiotic.
Moreover, the brine shrimps (Artemia salina) toxicity test exhibited
LC50 value was 569.52 ppm. The resulting data indicated that the A.
vera plant have less toxic effects on brine shrimp. Hence, it is
signified that Aloe vera plant extract is safe to be used as an
antimicrobial agent.
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: 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: The essence of the 21st century is knowledge economy. Knowledge has become the key resource of economic growth and social development. Construction industry is no exception. Because of the characteristic of complexity, project manager can't depend only on information management. The only way to improve the level of construction project management is to set up a kind of effective knowledge accumulation mechanism. This paper first introduced the IFC standard and the concept of ontology. Then put forward the construction method of the architectural engineering domain ontology based on IFC. And finally build up the concepts, properties and the relationship between the concepts of the ontology. The deficiency of this paper is also pointed out.
Abstract: Two-dimensional (2D) bar codes were designed to
carry significantly more data with higher information density and
robustness than its 1D counterpart. Thanks to the popular
combination of cameras and mobile phones, it will naturally bring
great commercial value to use the camera phone for 2D bar code
reading. This paper addresses the problem of specific 2D bar code
design for mobile phones and introduces a low-level encoding
method of matrix codes. At the same time, we propose an efficient
scheme for 2D bar codes decoding, of which the effort is put on
solutions of the difficulties introduced by low image quality that is
very common in bar code images taken by a phone camera.
Abstract: In this study, we report the synthesis and
characterization of nanohydroxyapatite (nHAp) in gelatin-starch
matrix via biomimetic method. Characterization of the samples was
performed using X-ray diffraction (XRD) and Fourier Transform
infrared spectroscopy (FT-IR). The Size and morphology of the
nHAp samples were determined using scanning and transmission
electron microscopy (SEM and TEM). The results reveal that the
shape and morphology of nHAp is influenced by presence of
biopolymers as template. Carbonyl and amino groups from gelatin
and hydroxyl from starch play crucial roles in HAp formation on the
surface of gelatin-starch.
Abstract: Age and sex are biological terms that are socioculturally
constructed for marriage and marital sexual behavior in
every society. Marriage is a universal norm that makes legitimate
sexual behavior between a man and a woman in marital life cycle to
gain bio-social purposes. Cross-cultural studies reveal that marital
sexual frequency as a part of marital sexual behavior not only varies
within the couple-s life cycle, but also varies between and among
couples in diverse cultures. The purpose of the study was to compare
marital sexual frequency in association with age status and length of
marital relationship between Muslim and Santal couples in rural
Bangladesh. For this we assumed that (1) Santal culture compared to
Muslim culture preferred earlier age at marriage for meeting marital
sexual purposes in rural Bangladesh; (2) Marital duration among the
Muslim couples was higher than that among the Santal couples; (3)
Sexual frequency among the younger couples in both the ethnic
communities was higher than the older couples; (4) Sexual frequency
across the Muslim couples- marital life cycle was higher than that the
Santal couples- marital life cycle. In so doing, 288 active couples
(145 for Muslim and 143 for Santal) selected by cluster random
sampling were interviewed with questionnaire method. The findings
of Independent Samples T Test on age at marriage, current age,
marital duration and sexual frequency independently reveal that there
were significant differences in sexual frequency not only across the
couples- life cycle but also vary between the Muslim and Santal
couples in relation to marital duration. The results of Pearson-s Inter-
Correlation Coefficients reveal that although age at marriage, current
age and marital duration for husband and wife were significantly
positive correlated with each other between the communities, there
were significantly negative correlation between the age at marriage,
current age, marital duration and sexual frequency among the
selected couples between the communities.
Abstract: A new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuoustone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different levels of importance from which the bit stream will be generated. The subcomponents of each level of importance are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several enhance levels.
Abstract: When designing information systems that deal with
large amount of domain knowledge, system designers need to consider
ambiguities of labeling termsin domain vocabulary for navigating
users in the information space. The goal of this study is to develop a
methodology for system designers to label navigation items, taking
account of ambiguities stems from synonyms or polysemes of labeling
terms. In this paper, we propose a method for concept labeling based
on mappings between domain ontology andthesaurus, and report
results of an empirical evaluation.
Abstract: We present a dextran modified silicon microring
resonator sensor for high density antibody immobilization. An array
of sensors consisting of three sensor rings and a reference ring was
fabricated and its surface sensitivity and the limit of detection were
obtained using polyelectrolyte multilayers. The mass sensitivity and
the limit of detection of the fabricated sensor ring are 0.35 nm/ng
mm-2 and 42.8 pg/mm2 in air, respectively. Dextran modified sensor
surface was successfully prepared by covalent grafting of oxidized
dextran on 3-aminopropyltriethoxysilane (APTES) modified silicon
sensor surface. The antibody immobilization on hydrogel dextran
matrix improves 40% compared to traditional antibody
immobilization method via APTES and glutaraldehyde linkage.
Abstract: Clustering techniques have been used by many intelligent software agents to group similar access patterns of the Web users into high level themes which express users intentions and interests. However, such techniques have been mostly focusing on one salient feature of the Web document visited by the user, namely the extracted keywords. The major aim of these techniques is to come up with an optimal threshold for the number of keywords needed to produce more focused themes. In this paper we focus on both keyword and similarity thresholds to generate themes with concentrated themes, and hence build a more sound model of the user behavior. The purpose of this paper is two fold: use distance based clustering methods to recognize overall themes from the Proxy log file, and suggest an efficient cut off levels for the keyword and similarity thresholds which tend to produce more optimal clusters with better focus and efficient size.
Abstract: This work proposes an accurate crosstalk noise estimation method in the presence of multiple RLC lines for the use in design automation tools. This method correctly models the loading effects of non switching aggressors and aggressor tree branches using resistive shielding effect and realistic exponential input waveforms. Noise peak and width expressions have been derived. The results obtained are at good agreement with SPICE results. Results show that average error for noise peak is 4.7% and for the width is 6.15% while allowing a very fast analysis.