Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: Using the concept of measure of noncompactness, we present some results concerning the existence, uniform local attractivity and global attractivity of solutions for a functional integral equation. Our results improve and extend some previous known results and based on weaker conditions. Some examples which show that our results are applicable when the previous results are inapplicable are also included.
Abstract: Novel Coconut oil nanofluids of various concentrations have been prepared through ultrasonically assisted sol-gel method. The structural and morphological properties of the copper oxide nanoparticle have been analyzed with respectively and it revealed the monoclinic end-centered structure of crystallite and shuttle like flake morphology of agglomerates. Ultrasonic studies have been made for the nanofluids at different temperatures. The molecular interactions responsible for the changes in acoustical parameter with respect to concentration and temperature are discussed.
Abstract: This study is to evaluate the behavior of integral and
segmental specimens through static and cyclic tests. Integral
specimens were made with the same size to be compared with
segmental specimens that were made by connected precast members.
To evaluate its bending performance and serviceability, 1 integral and
3 segmental specimens were tested under static load. And 1 integral
and 2 segmental specimens were tested under cyclic load, respectively.
Different load ranges were considered in the cyclic tests to evaluate the
safety and serviceability. The test results showed that under static
loading, segmental specimens had about 94% of the integral
specimen's maximum moment, averagely. Under cyclic loading, the
segmental specimens showed that had enough safety in the range of
higher than service load and enough serviceability. In conclusion, the
maximum crack width (0.16mm) satisfied the allowable crack width
(0.30mm) in the range of service load.
Abstract: The projection methods, usually viewed as the methods
for computing eigenvalues, can also be used to estimate pseudospectra.
This paper proposes a kind of projection methods for computing
the pseudospectra of large scale matrices, including orthogonalization
projection method and oblique projection method respectively. This
possibility may be of practical importance in applications involving
large scale highly nonnormal matrices. Numerical algorithms are
given and some numerical experiments illustrate the efficiency of
the new algorithms.
Abstract: This paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method.
Abstract: This paper proposes an Interactive Chinese Character
Learning System (ICCLS) based on pictorial evolution as an
edutainment concept in computer-based learning of language. The
advantage of the language origination itself is taken as a learning
platform due to the complexity in Chinese language as compared to
other types of languages. Users especially children enjoy more by
utilize this learning system because they are able to memories the
Chinese Character easily and understand more of the origin of the
Chinese character under pleasurable learning environment, compares
to traditional approach which children need to rote learning Chinese
Character under un-pleasurable environment. Skeletonization is used
as the representation of Chinese character and object with an animated
pictograph evolution to facilitate the learning of the language. Shortest
skeleton path matching technique is employed for fast and accurate
matching in our implementation. User is required to either write a
word or draw a simple 2D object in the input panel and the matched
word and object will be displayed as well as the pictograph evolution
to instill learning. The target of computer-based learning system is for
pre-school children between 4 to 6 years old to learn Chinese
characters in a flexible and entertaining manner besides utilizing
visual and mind mapping strategy as learning methodology.
Abstract: The finite-difference time-domain (FDTD) method is
one of the most widely used computational methods in
electromagnetic. This paper describes the design of two-dimensional
(2D) FDTD simulation software for transverse magnetic (TM)
polarization using Berenger's split-field perfectly matched layer
(PML) formulation. The software is developed using Matlab
programming language. Numerical examples validate the software.
Abstract: Sweet potato products are necessary for the provision
of essential nutrients in every household, regardless of their poverty
status. Their consumption appears to be highly influenced by socioeconomic
factors, such as malnutrition, food insecurity and
unemployment. Therefore, market availability is crucial for these
cultivars to resolve some of the socio-economic factors. The aim of
the study was to investigate market availability of sweet potato
cultivars in the North West Province. In this study, both qualitative
and quantitative research methodologies were used. Qualitative
methodology was used to explain the quantitative outcomes of the
variables. On the other hand, quantitative results were used to test the
hypothesis. The study used SPSS software to analyse the data. Crosstabulation
and Chi-square statistics were used to obtain the
descriptive and inferential analyses, respectively. The study found
that the Blesbok cultivar is dominating the markets of the North West
Province, with the Monate cultivar dominating in the Bojanala
Platinum (75%) and Dr Ruth Segomotsi Mompati (25%) districts. It
is also found that a unit increase in the supply of sweet potato
cultivars in both local and district municipal markets is accompanied
by a reduced demand of 28% and 33% at district and local markets,
respectively. All these results were found to be significant at p
Abstract: This paper looks into areas not covered by prominent
Agent-Oriented Software Engineering (AOSE) methodologies.
Extensive paper review led to the identification of two issues, first
most of these methodologies almost neglect semantic web and
ontology. Second, as expected, each one has its strength and
weakness and may focus on some phases of the development
lifecycle but not all of the phases. The work presented here builds
extensions to a highly regarded AOSE methodology (MaSE) in order
to cover the areas that this methodology does not concentrate on. The
extensions include introducing an ontology stage for semantic
representation and integrating early requirement specification from a
methodology which mainly focuses on that. The integration involved
developing transformation rules (with the necessary handling of nonmatching
notions) between the two sets of representations and
building the software which automates the transformation. The
application of this integration on a case study is also presented in the
paper. The main flow of MaSE stages was changed to smoothly
accommodate the new additions.
Abstract: The institutions seek to improve their performance
and quality of service, so that their patients are satisfied. This
research project aims, conduct a time study program in the area of
gynecological surgery, to determine the current level of capacity and
optimize the programming time in order to adequately respond to
demand. The system is analyzed by waiting lines and uses the
simulation using ARENA to evaluate proposals for improvement and
optimization programming time each of the surgeries.
Abstract: Views on therapists- attraction have influenced the ethical and professional development of the mental health fields. Because the majority of therapist attraction literature (63.6%) has been conducted from a psychoanalytic standpoint, approaches to attraction from feminist perspectives have not been adequately developed. Considering the lack of a feminist voice regarding attraction, this article attempts to offer a feminist perspective on this issue. The purpose of this article is to offer a feminist perspective on the phenomenon of attraction in order to raise awareness about the importance of power inequalities, intersectionalities, contextual variables and the need for action in the field.
Abstract: In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos.
Abstract: Hybrid algorithm is the hot issue in Computational
Intelligence (CI) study. From in-depth discussion on Simulation
Mechanism Based (SMB) classification method and composite patterns,
this paper presents the Mamdani model based Adaptive Neural
Fuzzy Inference System (M-ANFIS) and weight updating formula in
consideration with qualitative representation of inference consequent
parts in fuzzy neural networks. M-ANFIS model adopts Mamdani
fuzzy inference system which has advantages in consequent part.
Experiment results of applying M-ANFIS to evaluate traffic Level
of service show that M-ANFIS, as a new hybrid algorithm in computational
intelligence, has great advantages in non-linear modeling,
membership functions in consequent parts, scale of training data and
amount of adjusted parameters.
Abstract: This paper presents an improved image segmentation
model with edge preserving regularization based on the
piecewise-smooth Mumford-Shah functional. A level set formulation
is considered for the Mumford-Shah functional minimization in
segmentation, and the corresponding partial difference equations are
solved by the backward Euler discretization. Aiming at encouraging
edge preserving regularization, a new edge indicator function is
introduced at level set frame. In which all the grid points which is used
to locate the level set curve are considered to avoid blurring the edges
and a nonlinear smooth constraint function as regularization term is
applied to smooth the image in the isophote direction instead of the
gradient direction. In implementation, some strategies such as a new
scheme for extension of u+ and u- computation of the grid points and
speedup of the convergence are studied to improve the efficacy of the
algorithm. The resulting algorithm has been implemented and
compared with the previous methods, and has been proved efficiently
by several cases.
Abstract: In this work we evaluate the possibility of predicting
the emotional state of a person based on the EEG. We investigate
the problem of classifying valence from EEG signals during
the presentation of affective pictures, utilizing the "frontal EEG
asymmetry" phenomenon. To distinguish positive and negative
emotions, we applied the Common Spatial Patterns algorithm.
In contrast to our expectations, the affective pictures did not
reliably elicit changes in frontal asymmetry. The classifying task
thereby becomes very hard as reflected by the poor classifier
performance. We suspect that the masking of the source of the
brain activity related to emotions, coming mostly from deeper
structures in the brain, and the insufficient emotional engagement
are among main reasons why it is difficult to predict the emotional
state of a person.
Abstract: Sarkhoon gas plant, located in south of Iran, has been installed to removal H2S contained in a high pressure natural gas stream. The solvent used for the H2S removal from gaseous stream is 34% by weight (wt%) Di-ethanol amine (DEA) solutions. Due to increasing concentration of heat stable salt (HSS) in solvent, corrosivity of amine solution had been increased. Reports indicated that there was corrosion on the shell of regeneration column. Because source formation of HSS was unknown, we decided to control the amount of HSS at the limit less than 3% wt amine solvent. Therefore, two small columns were filled by strong anionic base and carbon active, and then polluted amine was passed through beds. Finally a temporary amine recovery package on industrial scale was made based on laboratory’s results. From economical point of view we could save $700000 beside corrosion occurrence of the stripping column has been vigorously decreased.
Abstract: Because of the reservoir effect, dynamic analysis of concrete dams is more involved than other common structures. This problem is mostly sourced by the differences between reservoir water, dam body and foundation material behaviors. To account for the reservoir effect in dynamic analysis of concrete gravity dams, two methods are generally employed. Eulerian method in reservoir modeling gives rise to a set of coupled equations, whereas in Lagrangian method, the same equations for dam and foundation structure are used. The Purpose of this paper is to evaluate and study possible advantages and disadvantages of both methods. Specifically, application of the above methods in the analysis of dam-foundationreservoir systems is leveraged to calculate the hydrodynamic pressure on dam faces. Within the frame work of dam- foundationreservoir systems, dam displacement under earthquake for various dimensions and characteristics are also studied. The results of both Lagrangian and Eulerian methods in effects of loading frequency, boundary condition and foundation elasticity modulus are quantitatively evaluated and compared. Our analyses show that each method has individual advantages and disadvantages. As such, in any particular case, one of the two methods may prove more suitable as presented in the results section of this study.
Abstract: The internet has become an attractive avenue for
global e-business, e-learning, knowledge sharing, etc. Due to
continuous increase in the volume of web content, it is not practically
possible for a user to extract information by browsing and integrating
data from a huge amount of web sources retrieved by the existing
search engines. The semantic web technology enables advancement
in information extraction by providing a suite of tools to integrate
data from different sources. To take full advantage of semantic web,
it is necessary to annotate existing web pages into semantic web
pages. This research develops a tool, named OWIE (Ontology-based
Web Information Extraction), for semantic web annotation using
domain specific ontologies. The tool automatically extracts
information from html pages with the help of pre-defined ontologies
and gives them semantic representation. Two case studies have been
conducted to analyze the accuracy of OWIE.
Abstract: This study aims at using multi-source data to monitor
coral biodiversity and coral bleaching. We used coral reef at Racha
Islands, Phuket as a study area. There were three sources of data:
coral diversity, sensor based data and satellite data.