Abstract: In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Abstract: Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
Abstract: In this research work, poly (acrylonitrile-butadienestyrene)/
polypropylene (ABS/PP) blends were processed by melt
compounding in a twin-screw extruder. Upgrading of the thermal
characteristics of the obtained materials was attempted by the
incorporation of organically modified montmorillonite (OMMT), as
well as, by the addition of two types of compatibilizers;
polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS
grafted with maleic anhydride (ABS-g-MAH). The effect of the
above treatments was investigated separately and in combination.
Increasing the PP content in ABS matrix seems to increase the
thermal stability of their blend and the glass transition temperature
(Tg) of SAN phase of ABS. From the other part, the addition of ABS
to PP promotes the formation of its β-phase, which is maximum at 30
wt% ABS concentration, and increases the crystallization temperature
(Tc) of PP. In addition, it increases the crystallization rate of PP.The
β-phase of PP in ABS/PP blends is reduced by the addition of
compatibilizers or/and organoclay reinforcement. The incorporation
of compatibilizers increases the thermal stability of PP and reduces
its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it
decreases slightly the Tgs of PP and SAN phases of ABS/PP blends.
Regarding the storage modulus of the ABS/PP blends, it presents a
change in their behavior at about 10°C and return to their initial
behavior at ~110°C. The incorporation of OMMT to no compatibilized
and compatibilized ABS/PP blends enhances their storage modulus.
Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: In this paper, the two-dimension differential transformation method (DTM) is employed to obtain the closed form solutions of the three famous coupled partial differential equation with physical interest namely, the coupled Korteweg-de Vries(KdV) equations, the coupled Burgers equations and coupled nonlinear Schrödinger equation. We begin by showing that how the differential transformation method applies to a linear and non-linear part of any PDEs and apply on these coupled PDEs to illustrate the sufficiency of the method for this kind of nonlinear differential equations. The results obtained are in good agreement with the exact solution. These results show that the technique introduced here is accurate and easy to apply.
Abstract: Buyer coalition with a combination of items is a group of buyers joining together to purchase a combination of items with a larger discount. The primary aim of existing buyer coalition with a combination of items research is to generate a large total discount. However, the aim is hard to achieve because this research is based on the assumption that each buyer completely knows other buyers- information or at least one buyer knows other buyers- information in a coalition by exchange of information. These assumption contrast with the real world environment where buyers join a coalition with incomplete information, i.e., they concerned only with their expected discounts. Therefore, this paper proposes a new buyer community coalition formation with a combination of items scheme, called the Community Compromised Combinatorial Coalition scheme, under such an environment of incomplete information. In order to generate a larger total discount, after buyers who want to join a coalition propose their minimum required saving, a coalition structure that gives a maximum total retail prices is formed. Then, the total discount division of the coalition is divided among buyers in the coalition depending on their minimum required saving and is a Pareto optimal. In mathematical analysis, we compare concepts of this scheme with concepts of the existing buyer coalition scheme. Our mathematical analysis results show that the total discount of the coalition in this scheme is larger than that in the existing buyer coalition scheme.
Abstract: The modern queueing theory is one of the powerful
tools for a quantitative and qualitative analysis of communication systems, computer networks, transportation systems, and many other technical systems. The paper is designated to the analysis of queueing
systems, arising in the networks theory and communications theory
(called open queueing network). The authors of this research in the
sphere of queueing theory present the theorem about the law of the iterated logarithm (LIL) for the queue length of a customers in open
queueing network and its application to the mathematical model of
the open message switching system.
Abstract: Network exchange is now widely used. However, it still
cannot avoid the problems evolving from network exchange. For
example. A buyer may not receive the order even if he/she makes the
payment. For another example, the seller possibly get nothing even
when the merchandise is sent. Some studies about the fair exchange
have proposed protocols for the design of efficiency and exploited the
signature property to specify that two parties agree on the exchange.
The information about purchased item and price are disclosed in
this way. This paper proposes a new fair network payment protocol
with off-line trusted third party. The proposed protocol can protect
the buyers- purchase message from being traced. In addition, the
proposed protocol can meet the proposed requirements. The most
significant feature is Non-transfer property we achieved.
Abstract: Indigenous Knowledge (IK) has many social and
economic benefits. However, IK is at the risk of extinction due to the
difficulties to preserve it as most of the IK largely remains
undocumented. This study aims to design a model of the factors
affecting the adoption of Information and Communication
Technologies (ICTs) for the preservation of IK. The proposed model
is based on theoretical frameworks on ICT adoption. It was designed
following a literature review of ICT adoption theories for households,
and of the factors affecting ICT adoption for IK. The theory that
fitted to the best all factors was then chosen as the basis for the
proposed model. This study found that the Model of Adoption of
Technology in Households (MATH) is the most suitable theoretical
framework for modeling ICT adoption factors for the preservation of
IK.
Abstract: In this paper the Differential Quadrature Method (DQM) is employed to study the coupled lateral-torsional free vibration behavior of the laminated composite beams. In such structures due to the fiber orientations in various layers, the lateral displacement leads to a twisting moment. The coupling of lateral and torsional vibrations is modeled by the bending-twisting material coupling rigidity. In the present study, in addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies of the beam. The governing differential equations of motion which form a system of three coupled PDEs are solved numerically using DQ procedure under different boundary conditions consist of the combinations of simply, clamped, free and other end conditions. The resulting natural frequencies and mode shapes for cantilever beam are compared with similar results in the literature and good agreement is achieved.
Abstract: 16-Mercaptohexadecanoic acid (MHDA) and tripeptide glutathione conjugated with gold nanoparticles (Au-NPs) are characterized by Fourier Transform InfaRared (FTIR) spectroscopy combined with Surface-enhanced Raman scattering (SERS) spectroscopy. Surface Plasmon Resonance (SPR) technique based on FTIR spectroscopy has become an important tool in biophysics, which is perspective for the study of organic compounds. FTIR-spectra of MHDA shows the line at 2500 cm-1 attributed to thiol group which is modified by presence of Au-NPs, suggesting the formation of bond between thiol group and gold. We also can observe the peaks originate from characteristic chemical group. A Raman spectrum of the same sample is also promising. Our preliminary experiments confirm that SERS-effect takes place for MHDA connected with Au-NPs and enable us to detected small number (less than 106 cm-2) of MHDA molecules. Combination of spectroscopy methods: FTIR and SERS – enable to study optical properties of Au- NPs and immobilized bio-molecules in context of a bio-nano-sensors.
Abstract: This contribution deals with the relationship between
communication effectiveness and the extent of communication
among organizational units. To facilitate communication between
employees and to increase the level of understanding, the knowledge
of communication tools is necessary. Recent experience has shown
that personal communication is critical for smooth running of
companies and cannot be fully replaced by any form of technical
communication devices.
Below are presented the outcomes of the research on the
relationship between the extent of communication among
organisational units and its efficiency.
Abstract: Ground-level tropospheric ozone is one of the air
pollutants of most concern. It is mainly produced by photochemical
processes involving nitrogen oxides and volatile organic compounds
in the lower parts of the atmosphere. Ozone levels become
particularly high in regions close to high ozone precursor emissions
and during summer, when stagnant meteorological conditions with
high insolation and high temperatures are common.
In this work, some results of a study about urban ozone
distribution patterns in the city of Badajoz, which is the largest and
most industrialized city in Extremadura region (southwest Spain) are
shown. Fourteen sampling campaigns, at least one per month, were
carried out to measure ambient air ozone concentrations, during
periods that were selected according to favourable conditions to
ozone production, using an automatic portable analyzer.
Later, to evaluate the ozone distribution at the city, the measured
ozone data were analyzed using geostatistical techniques. Thus, first,
during the exploratory analysis of data, it was revealed that they were
distributed normally, which is a desirable property for the subsequent
stages of the geostatistical study. Secondly, during the structural
analysis of data, theoretical spherical models provided the best fit for
all monthly experimental variograms. The parameters of these
variograms (sill, range and nugget) revealed that the maximum
distance of spatial dependence is between 302-790 m and the
variable, air ozone concentration, is not evenly distributed in reduced
distances. Finally, predictive ozone maps were derived for all points
of the experimental study area, by use of geostatistical algorithms
(kriging). High prediction accuracy was obtained in all cases as
cross-validation showed. Useful information for hazard assessment
was also provided when probability maps, based on kriging
interpolation and kriging standard deviation, were produced.
Abstract: Bacterial magnetic nanoparticles have great useful potential in biotechnological and biomedical applications. In this study, a liquid growth medium was modified for cultivation a fastidious magnetotactic bacterium that has been isolated from Anzali
lagoon, Iran in our previous research. These modifications include
change in vitamin, mineral, carbon sources and etcetera. In our
experience, the serum bottles and designed air-tight laboratory bottles
were used to create microaerobic conditions in order to development
of a method for scale-up experiment. This information may serve as a
guide to green chemistry based biological protocols for the synthesis
of magnetic nanoparticles with control over the chemical
composition, morphology and size.
Abstract: Internet is largely composed of textual contents and a
huge volume of digital contents gets floated over the Internet daily.
The ease of information sharing and re-production has made it
difficult to preserve author-s copyright. Digital watermarking came
up as a solution for copyright protection of plain text problem after
1993. In this paper, we propose a zero text watermarking algorithm
based on occurrence frequency of non-vowel ASCII characters and
words for copyright protection of plain text. The embedding
algorithm makes use of frequency non-vowel ASCII characters and
words to generate a specialized author key. The extraction algorithm
uses this key to extract watermark, hence identify the original
copyright owner. Experimental results illustrate the effectiveness of
the proposed algorithm on text encountering meaning preserving
attacks performed by five independent attackers.
Abstract: One part of the total employee-s reward is apart from basic wages or salary, employee-s benefits and intangible elements also so called contingent (variable) pay. Contingent pay is connected to performance, contribution, capcompetency or skills of individual employees, and to team-s or company-wide performance or to combination of few of the mentioned possibilities. Main aim of this article is to define, based on available information, contingent pay, describe reasons for its implementation and arguments for and against this type of remuneration, but also bring information not only about its extent and level of utilization by organizations of the Czech Republic operating in the field of environmental protection, but also mention their practical experience with this type of remuneration.
Abstract: We investigate an asymmetric connections model with a
dynamic network formation process, using an agent based simulation.
We permit heterogeneity of agents- value. Valuable persons seem
to have many links on real social networks. We focus on this
point of view, and examine whether valuable agents change the
structures of the terminal networks. Simulation reveals that valuable
agents diversify the terminal networks. We can not find evidence that
valuable agents increase the possibility that star networks survive the
dynamic process. We find that valuable agents disperse the degrees
of agents in each terminal network on an average.
Abstract: A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.
Abstract: The objective of this paper is to a design of pattern
classification model based on the back-propagation (BP) algorithm for
decision support system. Standard BP model has done full connection
of each node in the layers from input to output layers. Therefore, it
takes a lot of computing time and iteration computing for good
performance and less accepted error rate when we are doing some
pattern generation or training the network.
However, this model is using exclusive connection in between
hidden layer nodes and output nodes. The advantage of this model is
less number of iteration and better performance compare with standard
back-propagation model. We simulated some cases of classification
data and different setting of network factors (e.g. hidden layer number
and nodes, number of classification and iteration). During our
simulation, we found that most of simulations cases were satisfied by
BP based using exclusive connection network model compared to
standard BP. We expect that this algorithm can be available to
identification of user face, analysis of data, mapping data in between
environment data and information.
Abstract: A number of competing methodologies have been developed
to identify genes and classify DNA sequences into coding
and non-coding sequences. This classification process is fundamental
in gene finding and gene annotation tools and is one of the most
challenging tasks in bioinformatics and computational biology. An
information theory measure based on mutual information has shown
good accuracy in classifying DNA sequences into coding and noncoding.
In this paper we describe a species independent iterative
approach that distinguishes coding from non-coding sequences using
the mutual information measure (MIM). A set of sixty prokaryotes is
used to extract universal training data. To facilitate comparisons with
the published results of other researchers, a test set of 51 bacterial
and archaeal genomes was used to evaluate MIM. These results
demonstrate that MIM produces superior results while remaining
species independent.