Abstract: Carbon disulfide is widely used for the production of
viscose rayon, rubber, and other organic materials and it is a
feedstock for the synthesis of sulfuric acid. The objective of this
paper is to analyze possibilities for efficient production of CS2 from
sour natural gas reformation (H2SMR) (2H2S+CH4 =CS2 +4H2) .
Also, the effect of H2S to CH4 feed ratio and reaction temperature on
carbon disulfide production is investigated numerically in a
reforming reactor. The chemical reaction model is based on an
assumed Probability Density Function (PDF) parameterized by the
mean and variance of mixture fraction and β-PDF shape. The results
show that the major factors influencing CS2 production are reactor
temperature. The yield of carbon disulfide increases with increasing
H2S to CH4 feed gas ratio (H2S/CH4≤4). Also the yield of C(s)
increases with increasing temperature until the temperature reaches
to 1000°K, and then due to increase of CS2 production and
consumption of C(s), yield of C(s) drops with further increase in the
temperature. The predicted CH4 and H2S conversion and yield of
carbon disulfide are in good agreement with result of Huang and TRaissi.
Abstract: Recent advances in wireless sensor networks have led
to many routing methods designed for energy-efficiency in wireless
sensor networks. Despite that many routing methods have been
proposed in USN, a single routing method cannot be energy-efficient
if the environment of the ubiquitous sensor network varies. We present
the controlling network access to various hosts and the services they
offer, rather than on securing them one by one with a network security
model. When ubiquitous sensor networks are deployed in hostile
environments, an adversary may compromise some sensor nodes and
use them to inject false sensing reports. False reports can lead to not
only false alarms but also the depletion of limited energy resource in
battery powered networks. The interleaved hop-by-hop authentication
scheme detects such false reports through interleaved authentication.
This paper presents a LMDD (Low energy method for data delivery)
algorithm that provides energy-efficiency by dynamically changing
protocols installed at the sensor nodes. The algorithm changes
protocols based on the output of the fuzzy logic which is the fitness
level of the protocols for the environment.
Abstract: Matrix metalloproteinase-3 (MMP3) is key member
of the MMP family, and is known to be present in coronary
atherosclerotic. Several studies have demonstrated that MMP-3
5A/6A polymorphism modify each transcriptional activity in allele
specific manner. We hypothesized that this polymorphism may play
a role as risk factor for development of coronary stenosis. The aim of
our study was to estimate MMP-3 (5A/6A) gene polymorphism on
interindividual variability in risk for coronary stenosis in an Iranian
population.DNA was extracted from white blood cells and genotypes
were obtained from coronary stenosis cases (n=95) and controls
(n=100) by PCR (polymerase chain reaction) and restriction
fragment length polymorphism techniques. Significant differences
between cases and controls were observed for MMP3 genotype
frequencies (X2=199.305, p< 0.001); the 6A allele was less
frequently seen in the control group, compared to the disease group
(85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data
imply the involvement of -1612 5A/6A polymorphism in coronary
stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a
genetic susceptibility factor for coronary stenosis.
Abstract: In this paper, the effect of width and height of the
model on the earthquake response in the finite element method is
discussed. For this purpose an earth dam as a soil structure under
earthquake has been considered. Various dam-foundation models are
analyzed by Plaxis, a finite element package for solving geotechnical
problems. The results indicate considerable differences in the seismic
responses.
Abstract: Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.
Abstract: Addition of milli or micro sized particles to the heat
transfer fluid is one of the many techniques employed for improving
heat transfer rate. Though this looks simple, this method has
practical problems such as high pressure loss, clogging and erosion
of the material of construction. These problems can be overcome by
using nanofluids, which is a dispersion of nanosized particles in a
base fluid. Nanoparticles increase the thermal conductivity of the
base fluid manifold which in turn increases the heat transfer rate.
Nanoparticles also increase the viscosity of the basefluid resulting in
higher pressure drop for the nanofluid compared to the base fluid. So
it is imperative that the Reynolds number (Re) and the volume
fraction have to be optimum for better thermal hydraulic
effectiveness. In this work, the heat transfer enhancement using
aluminium oxide nanofluid using low and high volume fraction
nanofluids in turbulent pipe flow with constant wall temperature has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach. Nanofluid, up till
a volume fraction of 1% is found to be an effective heat transfer
enhancement technique. The Nusselt number (Nu) and friction factor
predictions for the low volume fractions (i.e. 0.02%, 0.1 and 0.5%)
agree very well with the experimental values of Sundar and Sharma
(2010). While, predictions for the high volume fraction nanofluids
(i.e. 1%, 4% and 6%) are found to have reasonable agreement with
both experimental and numerical results available in the literature.
So the computationally inexpensive single phase approach can be
used for heat transfer and pressure drop prediction of new nanofluids.
Abstract: Dynamic Causal Modeling (DCM) functional
Magnetic Resonance Imaging (fMRI) is a promising technique to
study the connectivity among brain regions and effects of stimuli
through modeling neuronal interactions from time-series
neuroimaging. The aim of this study is to study characteristics of a
mirror neuron system (MNS) in elderly group (age: 60-70 years old).
Twenty volunteers were MRI scanned with visual stimuli to study a
functional brain network. DCM was employed to determine the
mechanism of mirror neuron effects. The results revealed major
activated areas including precentral gyrus, inferior parietal lobule,
inferior occipital gyrus, and supplementary motor area. When visual
stimuli were presented, the feed-forward connectivity from visual
area to conjunction area was increased and forwarded to motor area.
Moreover, the connectivity from the conjunction areas to premotor
area was also increased. Such findings can be useful for future
diagnostic process for elderly with diseases such as Parkinson-s and
Alzheimer-s.
Abstract: In comparison to the original SVM, which involves a
quadratic programming task; LS–SVM simplifies the required
computation, but unfortunately the sparseness of standard SVM is
lost. Another problem is that LS-SVM is only optimal if the training
samples are corrupted by Gaussian noise. In Least Squares SVM
(LS–SVM), the nonlinear solution is obtained, by first mapping the
input vector to a high dimensional kernel space in a nonlinear
fashion, where the solution is calculated from a linear equation set. In
this paper a geometric view of the kernel space is introduced, which
enables us to develop a new formulation to achieve a sparse and
robust estimate.
Abstract: The utilize of renewable energy sources becomes
more crucial and fascinatingly, wider application of renewable
energy devices at domestic, commercial and industrial levels is not
only affect to stronger awareness but also significantly installed
capacities. Moreover, biomass principally is in form of woods and
converts to be energy for using by humans for a long time.
Gasification is a process of conversion of solid carbonaceous fuel
into combustible gas by partial combustion. Many gasified models
have various operating conditions because the parameters kept in
each model are differentiated. This study applied the experimental
data including three inputs variables including biomass consumption;
temperature at combustion zone and ash discharge rate and gas flow
rate as only one output variable. In this paper, response surface
methods were applied for identification of the gasified system
equation suitable for experimental data. The result showed that linear
model gave superlative results.
Abstract: In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.
Abstract: Sparse representation which can represent high dimensional
data effectively has been successfully used in computer vision
and pattern recognition problems. However, it doesn-t consider the
label information of data samples. To overcome this limitation,
we develop a novel dimensionality reduction algorithm namely
dscriminatively regularized sparse subspace learning(DR-SSL) in this
paper. The proposed DR-SSL algorithm can not only make use of
the sparse representation to model the data, but also can effective
employ the label information to guide the procedure of dimensionality
reduction. In addition,the presented algorithm can effectively deal
with the out-of-sample problem.The experiments on gene-expression
data sets show that the proposed algorithm is an effective tool for
dimensionality reduction and gene-expression data classification.
Abstract: Intellectual capital measurement is a central aspect of knowledge management. The measurement and the evaluation of intangible assets play a key role in allowing an effective management of these assets as sources of competitiveness. For these reasons, managers and practitioners need conceptual and analytical tools taking into account the unique characteristics and economic significance of Intellectual Capital. Following this lead, we propose an efficiency and productivity analysis of Intellectual Capital, as a determinant factor of the company competitive advantage. The analysis is carried out by means of Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). These techniques identify Bests Practice companies that have accomplished competitive advantage implementing successful strategies of Intellectual Capital management, and offer to inefficient companies development paths by means of benchmarking. The proposed methodology is employed on the Biotechnology industry in the period 2007-2010.
Abstract: The study aimed to evaluated the reproductive performance response to short term oestrus synchronization during the transition period. One hundred and sixty-five indigenous multiparous non-lactating goats were subdivided into the following six treatment groups for oestrus synchronization: NT control Group (N= 30), Fe-21d, FGA vaginal sponge for 21days+eCG at 19thd; FPe- 11d, FGA 11d + PGF2α and eCG at 9th d; FPe-10d, FGA 10d+ PGF2α and eCG at 8th d; FPe-9d, FGA 9d +PGF2α and eCG at 7thd; PFe-5d, PGF2α at d0 + FGA 5d + eCG at 5thd. The goats were natural mated (1 male/6 females). Fecundity rates (n. births /n. females treated x 100) were statistically higher (P < 0.05) in short term FPe-9d (157.9%), FPe- 11d (115.4%), FPe-10d (111.1%) and PFe-5d (107.7%) groups compared to the NT control Group (66.7%).
Abstract: Little attention has been paid to information
transmission between the portfolios of large stocks and small stocks in the Korean stock market. This study investigates the return and volatility transmission mechanisms between large and small stocks in
the Korea Exchange (KRX). This study also explores whether bad news in the large stock market leads to a volatility of the small stock
market that is larger than the good news volatility of the large stock market. By employing the Granger causality test, we found
unidirectional return transmissions from the large stocks to medium
and small stocks. This evidence indicates that pat information about
the large stocks has a better ability to predict the returns of the medium and small stocks in the Korean stock market. Moreover, by using the
asymmetric GARCH-BEKK model, we observed the unidirectional relationship of asymmetric volatility transmission from large stocks to
the medium and small stocks. This finding suggests that volatility in
the medium and small stocks following a negative shock in the large
stocks is larger than that following a positive shock in the large stocks.
Abstract: Nowadays there are several grid connected converter
in the grid system. These grid connected converters are generally the
converters of renewable energy sources, industrial four quadrant
drives and other converters with DC link. These converters are
connected to the grid through a three phase bridge. The standards
prescribe the maximal harmonic emission which could be easily
limited with high switching frequency. The increased switching
losses can be reduced to the half with the utilization of the wellknown
Flat-top modulation. The suggested control method is the
expansion of the Flat-top modulation with which the losses could be
also reduced to the half compared to the Flat-top modulation.
Comparing to traditional control these requirements can be
simultaneously satisfied much better with the DLF (DC Link
Floating) method.
Abstract: The primary purpose of this article is an attempt to
find the implication of globalization on education. Globalization has
an important role as a process in the economical, political, cultural
and technological dimensions in the life of the contemporary human
being and has been affected by it. Education has its effects in this
procedure and while influencing it through educating global citizens
having universal human features and characteristics, has been
influenced by this phenomenon too. Nowadays, the role of education
is not just to develop in the students the knowledge and skills
necessary for the new kinds of jobs. If education wants to help
students be prepared of the new global society, it has to make them
engaged productive and critical citizens for the global era, so that
they can reflect about their roles as key actors in a dynamic often
uneven, matrix of economic and cultural exchanges. If education
wants to reinforce and raise the national identity, the value system
and the children and teenagers, it should make them ready for living
in the global era of this century. The used method in this research is
documentary and analyzing the documents. Studies in this field show
globalization has influences on the processes of the production,
distribution and consuming of knowledge. The happening of this
event in the information era has not only provide the necessary
opportunities for the exchanges of education worldwide but also has
privileges for the developing countries which enables them to
strengthen educational bases of their society and have an important
step toward their future.
Abstract: In this paper, an accurate theoretical analysis for the achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct-sequence/fast frequency hopping code-division multiple-access (DS/FFH-CDMA) system operating in a Rayleigh fading environment is presented. The analysis covers the downlink operation and leads to the derivation of an exact mathematical expression between the normalized average channel capacity available to each system-s user, under simultaneous optimal power and rate adaptation and the system-s parameters, as the number of hops per bit, the processing gain applied, the number of users per cell and the received signal-tonoise power ratio over the signal bandwidth. Finally, numerical results are presented to illustrate the proposed mathematical analysis.
Abstract: The success of an e-learning system is highly
dependent on the quality of its educational content and how effective,
complete, and simple the design tool can be for teachers. Educational
modeling languages (EMLs) are proposed as design languages
intended to teachers for modeling diverse teaching-learning
experiences, independently of the pedagogical approach and in
different contexts. However, most existing EMLs are criticized for
being too abstract and too complex to be understood and manipulated
by teachers. In this paper, we present a visual EML that simplifies the
process of designing learning scenarios for teachers with no
programming background. Based on the conceptual framework of the
activity theory, our resulting visual EML focuses on using Domainspecific
modeling techniques to provide a pedagogical level of
abstraction in the design process.
Abstract: The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Abstract: A key requirement for e-learning materials is
reusability and interoperability, that is the possibility to use at least
part of the contents in different courses, and to deliver them trough
different platforms. These features make possible to limit the cost of
new packages, but require the development of material according to
proper specifications. SCORM (Sharable Content Object Reference
Model) is a set of guidelines suitable for this purpose. A specific
adaptation project has been started to make possible to reuse existing
materials. The paper describes the main characteristics of SCORM
specification, and the procedure used to modify the existing material.