Abstract: From the importance of the conference and its
constructive role in the studies discussion, there must be a strong
organization that allows the exploitation of the discussions in opening
new horizons. The vast amount of information scattered across the
web, make it difficult to find experts, who can play a prominent role
in organizing conferences. In this paper we proposed a new approach
of extracting researchers- information from various Web resources
and correlating them in order to confirm their correctness. As a
validator of this approach, we propose a service that will be useful to
set up a conference. Its main objective is to find appropriate experts,
as well as the social events for a conference. For this application we
us Semantic Web technologies like RDF and ontology to represent
the confirmed information, which are linked to another ontology
(skills ontology) that are used to present and compute the expertise.
Abstract: In this study we propose a novel monitor hydraulic
automatic gauge control (HAGC) system based on fuzzy feedforward
controller. This is used in the development of cold rolling
mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average
yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in
the entry steel strip. The proposed method uses a mathematical model
of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In
order to improve the speed of the controller in rejecting disturbances
introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation
results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.
Abstract: We report here, the results of molecular dynamics
simulation of p-doped (Ga-face)GaN over n-doped (Siface)(
0001)4H-SiC hetero-epitaxial material system with one-layer
each of Ga-flux and (Al-face)AlN, as the interface materials, in the
form of, the total Density of States (DOS). It is found that the total
DOS at the Fermi-level for the heavily p-doped (Ga-face)GaN and ndoped
(Si-face)4H-SiC hetero-epitaxial system, with one layer of
(Al-face)AlN as the interface material, is comparatively higher than
that of the various cases studied, indicating that there could be good
vertical conduction across the (Ga-face)GaN over (Si-face)(0001)4HSiC
hetero-epitaxial material system.
Abstract: While computers are known to facilitate lower levels of learning, such as rote memorization of facts, measurable through electronically administered and graded multiple-choice questions, yes/no, and true/false answers, the imparting and measurement of higher-level cognitive skills is more vexing. These require more open-ended delivery and answers, and may be more problematic in an entirely virtual environment, notwithstanding the advances in technologies such as wikis, blogs, discussion boards, etc. As with the integration of all technology, merit is based more on the instructional design of the course than on the technology employed in, and of, itself. With this in mind, this study examined the perceptions of online students in an introductory Computer Information Systems course regarding the fostering of various higher-order thinking and team-building skills as a result of the activities, resources and technologies (ART) used in the course.
Abstract: In order to study seed yield and seed yield
components in bean under reduced irrigation condition and
assessment drought tolerance of genotypes, 15 lines of White beans
were evaluated in two separate RCB design with 3 replications under
stress and non stress conditions. Analysis of variance showed that
there were significant differences among varieties in terms of traits
under study, indicating the existence of genetic variation among
varieties. The results indicate that drought stress reduced seed yield,
number of seed per plant, biological yield and number of pod in
White been. In non stress condition, yield was highly correlated with
the biological yield, whereas in stress condition it was highly
correlated with harvest index. Results of stepwise regression showed
that, selection can we done based on, biological yield, harvest index,
number of seed per pod, seed length, 100 seed weight. Result of path
analysis showed that the highest direct effect, being positive, was
related to biological yield in non stress and to harvest index in stress
conditions. Factor analysis were accomplished in stress and nonstress
condition a, there were 4 factors that explained more than 76
percent of total variations. We used several selection indices such as
Stress Susceptibility Index ( SSI ), Geometric Mean Productivity (
GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and
Tolerance Index ( TOL ) to study drought tolerance of genotypes, we
found that the best Stress Index for selection tolerance genotypes
were STI, GMP and MP were the greatest correlations between these
Indices and seed yield under stress and non stress conditions. In
classification of genotypes base on phenotypic characteristics, using
cluster analysis ( UPGMA ), all allels classified in 5 separate groups
in stress and non stress conditions.
Abstract: In present paper we proposed a simple and effective method to compress an image. Here we found success in size reduction of an image without much compromising with it-s quality. Here we used Haar Wavelet Transform to transform our original image and after quantization and thresholding of DWT coefficients Run length coding and Huffman coding schemes have been used to encode the image. DWT is base for quite populate JPEG 2000 technique.
Abstract: The study presents a brief and synthetic discussion of selected conclusions resulting from multidimensional and in-depth empirical studies. Its theoretical part presents the assumptions referring to social responsibility management from the perspective of the specific nature of small enterprise functioning, while the empirical part presents the selected dysfunctions and paradoxes in social responsibility management referring to this group of enterprises. The paper is summarized by a short list of the resulting recommendations.
Abstract: Elastic and inelastic scattering of α-particles by 9Be nuclei at different incident energies have been analyzed. Optical model parameters (OMPs) of α-particles elastic scattering by 9Be at different energies have been obtained. Coupled Reaction Channel (CRC) of elastic scattering, inelastic scattering and transfer reaction has been calculated using Fresco Code. The effect of involving CRC calculations on the analysis of differential cross section has been studied. The transfer reaction of (5He) in the reaction 9Be(α,9Be)α has been studied. The spectroscopic factor of 9Be≡α+5He has been extracted.
Abstract: In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).
Abstract: This paper examines the students’ self-concept among 16- and 17- year- old adolescents in Malaysian secondary schools. Previous studies have shown that positive self-concept played an important role in student adjustment and academic performance during schooling. This study attempts to investigate the factors influencing students’ perceptions toward their own self-concept. A total of 1168 students participated in the survey. This study utilized the CoPs (UM) instrument to measure self-concept. Principal Component Analysis (PCA) revealed three factors: academic selfconcept, physical self-concept and social self-concept. This study confirmed that students perceived certain internal context factors, and revealed that external context factor also have an impact on their self-concept.
Abstract: The particular interests of this paper is to explore if the simple Genetic Algorithms (GA) starts with population of only two individuals and applying different crossover technique over these parents to produced 104 children, each one has different attributes inherited from their parents; is better than starting with population of 100 individuals; and using only one type crossover (order crossover OX). For this reason we implement GA with 52 different crossover techniques; each one produce two children; which means 104 different children will be produced and this may discover more search space, also we implement classic GA with order crossover and many experiments were done over 3 Travel Salesman Problem (TSP) to find out which method is better, and according to the results we can say that GA with Multi-crossovers is much better.
Abstract: novel and simple method is introduced for rapid and
highly efficient water treatment by reverse osmosis (RO) method using
multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN)
polymer as a flexible, highly efficient, reusable and semi-permeable
mixed matrix membrane (MMM). For this purpose, MWCNTs were
directly synthesized and on-line purified by chemical vapor deposition
(CVD) process, followed by directing the MWCNT bundles towards an
ultrasonic bath, in which PAN polymer was simultaneously suspended
inside a solid porous silica support in water at temperature to ~70 οC.
Fabrication process of MMM was finally completed by hot isostatic
pressing (HIP) process. In accordance with the analytical figures of
merit, the efficiency of fabricated MMM was ~97%. The rate of water
treatment process was also evaluated to 6.35 L min-1. The results reveal
that, the CNT-based MMM is suitable for rapid treatment of different
forms of industrial, sea, drinking and well water samples.
Abstract: This paper presents a novel method for prediction of
the mechanical behavior of proximal femur using the general
framework of the quantitative computed tomography (QCT)-based
finite element Analysis (FEA). A systematic imaging and modeling
procedure was developed for reliable correspondence between the
QCT-based FEA and the in-vitro mechanical testing. A speciallydesigned
holding frame was used to define and maintain a unique
geometrical reference system during the analysis and testing. The
QCT images were directly converted into voxel-based 3D finite
element models for linear and nonlinear analyses. The equivalent
plastic strain and the strain energy density measures were used to
identify the critical elements and predict the failure patterns. The
samples were destructively tested using a specially-designed gripping
fixture (with five degrees of freedom) mounted within a universal
mechanical testing machine. Very good agreements were found
between the experimental and the predicted failure patterns and the
associated load levels.
Abstract: In this article, we propose a methodology for the
characterization of the suspended matter along Algiers-s bay. An
approach by multi layers perceptron (MLP) with training by back
propagation of the gradient optimized by the algorithm of Levenberg
Marquardt (LM) is used. The accent was put on the choice of the
components of the base of training where a comparative study made
for four methods: Random and three alternatives of classification by
K-Means. The samples are taken from suspended matter image,
obtained by analytical model based on polynomial regression by
taking account of in situ measurements. The mask which selects the
zone of interest (water in our case) was carried out by using a multi
spectral classification by ISODATA algorithm. To improve the
result of classification, a cleaning of this mask was carried out using
the tools of mathematical morphology. The results of this study
presented in the forms of curves, tables and of images show the
founded good of our methodology.
Abstract: Based on the thermodynamic theory, the dependence of
sublimation energy of metal on temperature and pressure is discussed,
and the results indicate that the sublimation energy decreases linearly
with the increase of temperature and pressure. Combined with this
result, the blow-off impulse of aluminum induced by pulsed X-ray is
simulated by smoothed particle hydrodynamics (SPH) method. The
numerical results show that, while the change of sublimation energy
with temperature and pressure is considered, the blow-off impulse of
aluminum is larger than the case that the sublimation energy is
assumed to be a constant.
Abstract: The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.
Abstract: We present a hybrid architecture of recurrent neural
networks (RNNs) inspired by hidden Markov models (HMMs). We
train the hybrid architecture using genetic algorithms to learn and
represent dynamical systems. We train the hybrid architecture on a
set of deterministic finite-state automata strings and observe the
generalization performance of the hybrid architecture when presented
with a new set of strings which were not present in the training data
set. In this way, we show that the hybrid system of HMM and RNN
can learn and represent deterministic finite-state automata. We ran
experiments with different sets of population sizes in the genetic
algorithm; we also ran experiments to find out which weight
initializations were best for training the hybrid architecture. The
results show that the hybrid architecture of recurrent neural networks
inspired by hidden Markov models can train and represent dynamical
systems. The best training and generalization performance is
achieved when the hybrid architecture is initialized with random real
weight values of range -15 to 15.
Abstract: In order to study the influence of different methods of controlling weeds such as mechanical weeding and mechanical weeder efficiency analysis in mechanical cultivation conditions, in farming year of 2011 an experiment was done in a farm in coupling and development of technology center in Haraz,Iran. The treatments consisted of (I) control treatment: where no weeding was done, (II) use of mechanical weeding without engine and (III) power mechanical weeding. Results showed that experimental treatments had significantly different effects (p=0.05) on yield traits and number of filled grains per panicle, while treatments had the significant effects on grain weight and dry weight of weeds in the first, second and third weeding methods at 1% of confidence level. Treatment (II) had its most significant effect on number of filled grains per panicle and yield performance standpoint, which was 3705.97 kg ha-1 in its highest peak. Treatment (III) was ranked as second influential with 3559.8 kg ha-1. In addition, under (I) treatments, 2364.73 kg ha-1 of yield produced. The minimum dry weights of weeds in all weeding methods were related to the treatment (II), (III) and (I), respectively. The correlation coefficient analysis showed that total yield had a significant positive correlation with the panicle grain yield per plant (r= 0.55*) and the number of grains per panicle-1 (r= 0.57*) and the number of filled grains (r= 0.63*). Total rice yield also had negative correlation of r= -0. 64* with weed dry weight at second weed sampling time (17 DAT). The weed dry weight at third and fourth sampling times (24 and 40 DAT) had negative correlations of -0.65** and r=-0.61* with rice yield, respectively.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: Cogeneration may be defined as a system which
contains electricity production and regain of the thermo value of
exhaust gases simultaneously. The examination is based on the data-s
of an active cogeneration plant. This study, it is aimed to determine
which component of the system should be revised first to raise the
efficiency and decrease the loss of exergy. For this purpose, second
law analysis of thermodynamics is applied to each component due to
consider the effects of environmental conditions and take the quality
of energy into consideration as well as the quantity of it. The exergy
balance equations are produced and exergy loss is calculated for each
component. 44,44 % loss of exergy in heat exchanger, 29,59 % in
combustion chamber, 18,68 % in steam boiler, 5,25 % in gas turbine
and 2,03 % in compressor is calculated.