Abstract: The analysis of electromagnetic environment using
deterministic mathematical models is characterized by the
impossibility of analyzing a large number of interacting network
stations with a priori unknown parameters, and this is characteristic,
for example, of mobile wireless communication networks. One of the
tasks of the tools used in designing, planning and optimization of
mobile wireless network is to carry out simulation of electromagnetic
environment based on mathematical modelling methods, including
computer experiment, and to estimate its effect on radio
communication devices. This paper proposes the development of a
statistical model of electromagnetic environment of a mobile
wireless communication network by describing the parameters and
factors affecting it including the propagation channel and their
statistical models.
Abstract: In this paper, the two-dimensional stagger grid
interface pressure (SGIP) model has been generalized and presented
into three-dimensional form. For this purpose, various models of
surface tension force for interfacial flows have been investigated and
compared with each other. The VOF method has been used for
tracking the interface. To show the ability of the SGIP model for
three-dimensional flows in comparison with other models, pressure
contours, maximum spurious velocities, norm spurious flow
velocities and pressure jump error for motionless drop of liquid and
bubble of gas are calculated using different models. It has been
pointed out that SGIP model in comparison with the CSF, CSS and
PCIL models produces the least maximum and norm spurious
velocities. Additionally, the new model produces more accurate
results in calculating the pressure jumps across the interface for
motionless drop of liquid and bubble of gas which is generated in
surface tension force.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.
Abstract: The present paper reports the removal of Cd(II) and
Zn(II) ions using synthetic Zeolit NaA. The adsorption capacity of
the sorbent (Zeolite NaA) strongly depends on simultaneous or not
simultaneous (concurrent) presence of Cd(II) and Zn(II) in the
sorbate. When Cd(II) and Zn(II) are present simultaneously
(concurrently) in the sorbate, Zn(II) ions were sorbed at higher rate.
Equilibrium data fitted Langmuir, Freundlich and Tempkin isotherms
well. The applicability of the isotherm equation to describe the
adsorption process was judged by the correlation coefficients R2. The
Langmuir model yielded the best fit with R2 values equal to or higher
than 0.970, as compared to the Freundlich and Tempkin models. The
fact that 1/n values range from 0.322 to 0.755 indicates that the
adsorption of Cd(II) and Zn(II) ions from aqueous solutions also
favored by the Freundlich model.
Abstract: Semantic Web Technologies enable machines to
interpret data published in a machine-interpretable form on the web.
At the present time, only human beings are able to understand the
product information published online. The emerging semantic Web
technologies have the potential to deeply influence the further
development of the Internet Economy. In this paper we propose a
scenario based research approach to predict the effects of these new
technologies on electronic markets and business models of traders
and intermediaries and customers. Over 300 million searches are
conducted everyday on the Internet by people trying to find what
they need. A majority of these searches are in the domain of
consumer ecommerce, where a web user is looking for something to
buy. This represents a huge cost in terms of people hours and an
enormous drain of resources. Agent enabled semantic search will
have a dramatic impact on the precision of these searches. It will
reduce and possibly eliminate information asymmetry where a better
informed buyer gets the best value. By impacting this key
determinant of market prices semantic web will foster the evolution
of different business and economic models. We submit that there is a
need for developing these futuristic models based on our current
understanding of e-commerce models and nascent semantic web
technologies. We believe these business models will encourage
mainstream web developers and businesses to join the “semantic web
revolution."
Abstract: The zero truncated model is usually used in modeling
count data without zero. It is the opposite of zero inflated model.
Zero truncated Poisson and zero truncated negative binomial models
are discussed and used by some researchers in analyzing the
abundance of rare species and hospital stay. Zero truncated models
are used as the base in developing hurdle models. In this study, we
developed a new model, the zero truncated strict arcsine model,
which can be used as an alternative model in modeling count data
without zero and with extra variation. Two simulated and one real
life data sets are used and fitted into this developed model. The
results show that the model provides a good fit to the data. Maximum
likelihood estimation method is used in estimating the parameters.
Abstract: The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: In this study a neural network (NN) was proposed to
predict the sorption of binary mixture of copper-cobalt ions into
clinoptilolite as ion-exchanger. The configuration of the
backpropagation neural network giving the smallest mean square
error was three-layer NN with tangent sigmoid transfer function at
hidden layer with 10 neurons, linear transfer function at output layer
and Levenberg-Marquardt backpropagation training algorithm.
Experiments have been carried out in the batch reactor to obtain
equilibrium data of the individual sorption and the mixture of coppercobalt
ions. The obtained modeling results have shown that the used
of neural network has better adjusted the equilibrium data of the
binary system when compared with the conventional sorption
isotherm models.
Abstract: This paper presents a computational methodology
based on matrix operations for a computer based solution to the
problem of performance analysis of software reliability models
(SRMs). A set of seven comparison criteria have been formulated to
rank various non-homogenous Poisson process software reliability
models proposed during the past 30 years to estimate software
reliability measures such as the number of remaining faults, software
failure rate, and software reliability. Selection of optimal SRM for
use in a particular case has been an area of interest for researchers in
the field of software reliability. Tools and techniques for software
reliability model selection found in the literature cannot be used with
high level of confidence as they use a limited number of model
selection criteria. A real data set of middle size software project from
published papers has been used for demonstration of matrix method.
The result of this study will be a ranking of SRMs based on the
Permanent value of the criteria matrix formed for each model based
on the comparison criteria. The software reliability model with
highest value of the Permanent is ranked at number – 1 and so on.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
Abstract: In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Abstract: The transient hydrodynamics and thermal behaviors of
fluid flow in open-ended vertical parallel-plate porous microchannel are investigated semi-analytically under the effect of the hyperbolic
heat conduction model. The model that combines both the continuum approach and the possibility of slip at the boundary is adopted in the
study. The Effects of Knudsen number , Darcy number , and thermal relaxation time on the microchannel hydrodynamics and thermal behaviors are investigated using the hyperbolic heat
conduction models. It is found that as increases the slip in the hydrodynamic and thermal boundary condition increases. This slip in
the hydrodynamic boundary condition increases as increases. Also, the slip in the thermal boundary condition increases as
decreases especially the early stage of time.
Abstract: The effects of equilibrium time, solution pH, and
sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied
using a batch equilibration method. UV–VIS spectroscopy was used
to obtain the adsorption isotherms at 20° C. The optimum period for
adsorption was 300 min. However, MB removal increased from
81,82 % to 94,81 %. The equilibrium adsorption data was analyzed
by using Langmuir, Freundlich and Temkin isotherm models.
Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed
that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors
from aqueous solutions.
Abstract: Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.
Abstract: The use of Electronic Commerce (EC)
technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for
organizations that choose to adopt and implement ECommerce
systems. Factors of Business –to-business (B2B)
E-Commerce adoption and implementation have been
extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and
implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted
and tested in four SMEs located in Christchurch, New
Zealand. This paper explores the factors that impact the
decision and method of adoption and implementation of ECommerce
systems in automobile industry. Automobile
industry was chosen because the product they deal with i.e.
cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is
high. The factors that promote adoption and implementation of
E-Commerce technologies are discussed, together with the
barriers. This study will help SME owners to effectively
handle the adoption and implementation process and will also
improve the chance of successful E-Commerce
implementation. The implications of the findings for
managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in
small businesses and future research are discussed.
Abstract: This paper uses the radial basis function neural
network (RBFNN) for system identification of nonlinear systems.
Five nonlinear systems are used to examine the activity of RBFNN in
system modeling of nonlinear systems; the five nonlinear systems are
dual tank system, single tank system, DC motor system, and two
academic models. The feed forward method is considered in this
work for modelling the non-linear dynamic models, where the KMeans
clustering algorithm used in this paper to select the centers of
radial basis function network, because it is reliable, offers fast
convergence and can handle large data sets. The least mean square
method is used to adjust the weights to the output layer, and
Euclidean distance method used to measure the width of the Gaussian
function.
Abstract: Identifying and classifying intersections according to
severity is very important for implementation of safety related
counter measures and effective models are needed to compare and
assess the severity. Highway safety organizations have considered
intersection safety among their priorities. In spite of significant
advances in highways safety, the large numbers of crashes with high
severities still occur in the highways. Investigation of influential
factors on crashes enables engineers to carry out calculations in order
to reduce crash severity. Previous studies lacked a model capable of
simultaneous illustration of the influence of human factors, road,
vehicle, weather conditions and traffic features including traffic
volume and flow speed on the crash severity. Thus, this paper is
aimed at developing the models to illustrate the simultaneous
influence of these variables on the crash severity in urban highways.
The models represented in this study have been developed using
binary Logit Models. SPSS software has been used to calibrate the
models. It must be mentioned that backward regression method in
SPSS was used to identify the significant variables in the model.
Consider to obtained results it can be concluded that the main
factor in increasing of crash severity in urban highways are driver
age, movement with reverse gear, technical defect of the vehicle,
vehicle collision with motorcycle and bicycle, bridge, frontal impact
collisions, frontal-lateral collisions and multi-vehicle crashes in
urban highways which always increase the crash severity in urban
highways.
Abstract: Turbulence modeling of large-scale flow over a vegetated surface is complex. Such problems involve large scale computational domains, while the characteristics of flow near the surface are also involved. In modeling large scale flow, surface roughness including vegetation is generally taken into account by mean of roughness parameters in the modified law of the wall. However, the turbulence structure within the canopy region cannot be captured with this method, another method which applies source/sink terms to model plant drag can be used. These models have been developed and tested intensively but with a simple surface geometry. This paper aims to compare the use of roughness parameter, and additional source/sink terms in modeling the effect of plant drag on wind flow over a complex vegetated surface. The RNG k-ε turbulence model with the non-equilibrium wall function was tested with both cases. In addition, the k-ω turbulence model, which is claimed to be computationally stable, was also investigated with the source/sink terms. All numerical results were compared to the experimental results obtained at the study site Mason Bay, Stewart Island, New Zealand. In the near-surface region, it is found that the results obtained by using the source/sink term are more accurate than those using roughness parameters. The k-ω turbulence model with source/sink term is more appropriate as it is more accurate and more computationally stable than the RNG k-ε turbulence model. At higher region, there is no significant difference amongst the results obtained from all simulations.
Abstract: The paper deals with the most important changes that have occurred in business because of social media and its impact on organisations and leadership in recent years. It seeks to synthesize existing research, theories and concepts, in order to understand "social destinations", and to provide a bridge from past research to future success. Becoming a "social destination" is a strategic and tactical leadership and management issue and the paper will present the importance of destination leadership in choosing the way towards a social destination and some organisational models. It also presents some social media tools that can be used in transforming a destination into a social one. Adapting organisations to the twentyfirst century means adopting social media as a way of life and a way of business.