Abstract: Today due to rising levels of housing- necessities,
several problems have been raised regarding to urban quality of life.
The aim of the research is to study social and spatial aspects of
housing environment and to find out their interaction with the urban
quality of life. As a case of study two pilot areas of Famagusta city in
North Cyprus, were selected: Baykal, considered as an established
urban district and Tuzla, a newly developed peri-urban district. In
order to determine urban quality of life in planning and developing of
housing areas, social and spatial aspects of selected areas have been
examined, differences between them according to the planning policy
have been pointed out, advantages and disadvantages of housing
planning have been found. As a practical implementation of the
research a number of households in each selected area have been
interviewed in order to draw a conclusion.
Abstract: In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Abstract: As the resources for naturally occurring aggregates
diminished at an ever increasing rate, researchers are keen to utilize
recycled materials in road construction in harmony with sustainable
development. Steel slag, a waste product from the steel making
industry, is one of the recycled materials reported to exhibit great
potential to replace naturally occurring aggregates in asphalt
mixtures. This paper presents the resilient modulus properties of
steel slag asphalt mixtures subjected to short term oven ageing
(STOA). The resilient modulus test was carried out to evaluate the
stiffness of asphalt mixtures at 10ºC, 25ºC and 40ºC. Previous
studies showed that stiffness changes in asphalt mixture played an
important role in inflicting pavement distress particularly cracking
and rutting that are common at low and high temperatures
respectively. Temperature was found to significantly influence the
resilient modulus of asphalt mixes. The resilient modulus of the
asphalt specimens tested decreased by more than 90% when the test
temperature increased from 10°C to 40°C.
Abstract: As it is known, buoyancy and drag forces rule bubble's rise velocity in a liquid column. These forces are strongly dependent on fluid properties, gravity as well as equivalent's diameter. This study reports a set of bubble rising velocity experiments in a liquid column using water or glycerol. Several records of terminal velocity were obtained. The results show that bubble's rise terminal velocity is strongly dependent on dynamic viscosity effect. The data set allowed to have some terminal velocities data interval of 8.0 ? 32.9 cm/s with Reynolds number interval 1.3 -7490. The bubble's movement was recorded with a video camera. The main goal is to present an original set data and results that will be discussed based on two-phase flow's theory. It will also discussed, the prediction of terminal velocity of a single bubble in liquid, as well as the range of its applicability. In conclusion, this study presents general expressions for the determination of the terminal velocity of isolated gas bubbles of a Reynolds number range, when the fluid proprieties are known.
Abstract: A numerical investigation of the effects of nanosecond
barrier discharge on the stability of a two-dimensional free shear layer
is performed. The computations are carried out using a compressible
Navier-Stokes algorithm coupled with a thermodynamic model of the
discharge. The results show that significant increases in the shear
layer-s momentum thickness and Reynolds stresses occur due to
actuation. Dependence on both frequency and amplitude of actuation
are considered, and a comparison is made of the computed growth
rates with those predicted by linear stability theory. Amplitude and
frequency ranges for the efficient promotion of shear-layer instabilities
are identified.
Abstract: A multiple-option analytical model for the evaluation of the energy performance and distribution of aerodynamic forces acting on a vertical-axis Darrieus wind turbine depending on both rotor architecture and operating conditions is presented. For this purpose, a numerical algorithm, capable of generating the desired rotor conformation depending on design geometric parameters, is coupled to a Single/Double-Disk Multiple-Streamtube Blade Element – Momentum code. Both single and double-disk configurations are analyzed and model predictions are compared to literature experimental data in order to test the capability of the code for predicting rotor performance. Effective airfoil characteristics based on local blade Reynolds number are obtained through interpolation of literature low-Reynolds airfoil databases. Some corrections are introduced inside the original model with the aim of simulating also the effects of blade dynamic stall, rotor streamtube expansion and blade finite aspect ratio, for which a new empirical relationship to better fit the experimental data is proposed. In order to predict also open field rotor operation, a freestream wind shear profile is implemented, reproducing the effect of atmospheric boundary layer.
Abstract: In this paper multi-objective genetic algorithms are
employed for Pareto approach optimization of ideal Turboshaft
engines. In the multi-objective optimization a number of conflicting
objective functions are to be optimized simultaneously. The
important objective functions that have been considered for
optimization are specific thrust (F/m& 0), specific fuel consumption
( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O
η .
These objectives are usually conflicting with each other. The design
variables consist of thermodynamic parameters (compressor pressure
ratio, turbine temperature ratio and Mach number).
At the first stage single objective optimization has been
investigated and the method of NSGA-II has been used for multiobjective
optimization. Optimization procedures are performed for
two and four objective functions and the results are compared for
ideal Turboshaft engine. In order to investigate the optimal
thermodynamic behavior of two objectives, different set, each
including two objectives of output parameters, are considered
individually. For each set Pareto front are depicted. The sets of
selected decision variables based on this Pareto front, will cause the
best possible combination of corresponding objective functions.
There is no superiority for the points on the Pareto front figure,
but they are superior to any other point. In the case of four objective
optimization the results are given in tables.
Abstract: In response to address different development challenges, Tanzania is striving to achieve its fourth attribute of the National Development Vision, i.e. to have a well educated and learned society by the year 2025. One of the most cost effective methods that can reach a large part of the society in a short time is to integrate ICT in education through e-learning initiatives. However, elearning initiatives are challenged by limited or lack of connectivity to majority of secondary schools, especially those in rural and remote areas. This paper has explores the possibility for rural secondary school to access online e-Learning resources from a centralized e- Learning Management System (e-LMS). The scope of this paper is limited to schools that have computers irrespective of internet connectivity, resulting in two categories schools; those with internet access and those without. Different connectivity configurations have been proposed according to the ICT infrastructure status of the respective schools. However, majority of rural secondary schools in Tanzania have neither computers nor internet connection. Therefore this is a challenge to be addressed for the disadvantaged schools to benefit from e-Learning initiatives.
Abstract: In this research a comparison between k-epsilon and
LES model for a deoiling hydrocyclone is conducted. Flow field of
hydrocyclone is obtained by three-dimensional simulations with
OpenFOAM code. Potential of prediction for both methods of this
complex swirl flow is discussed. Large eddy simulation method
results have more similarity to experiment and its results are
presented in figures from different hydrocyclone cross sections.
Abstract: This study examined a habitat-suitability assessment method namely the Ecological Niche Factor Analysis (ENFA). A virtual species was created and then dispatched in a geographic information system model of a real landscape in three historic scenarios: (1) spreading, (2) equilibrium, and (3) overabundance. In each scenario, the virtual species was sampled and these simulated data sets were used as inputs for the ENFA to reconstruct the habitat suitability model. The 'equilibrium' scenario gives the highest quantity and quality among three scenarios. ENFA was sensitive to the distribution scenarios but not sensitive to sample sizes. The use of a virtual species proved to be a very efficient method, allowing one to fully control the quality of the input data as well as to accurately evaluate the predictive power of the analyses.
Abstract: The purpose of this study was to determine the
influence of physical activity and dietary fat intake on Body Mass
Index (BMI) of lecturers within a higher learning institutionalized
setting. The study adopted a Cross-sectional Correlational Design
and included 120 lecturers selected proportionately by simple
random sampling techniques from a population of 600 lecturers. Data
was collected using questionnaires, which had sections including
physical activity checklist adopted from the international physical
activity questionnaire (IPAQ), 24-hour food recall, anthropometric
measurements mainly weight and height. Analysis involved the use
of bivariate correlations and linear regression. A significant inverse
association was registered between BMI and duration (in minutes)
spent doing moderate intense physical activity per day (r=-0.322,
p
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: This paper intends to identify the ethnic Kazakhstani
Koreans- political process of identity formation by exploring their
narrative and practice about the state language represented in the
course of their becoming the new citizens of a new independent state.
The Russophone Kazakhstani Koreans- inability to speak the official
language of their affiliated state is considered there as dissatisfying the
basic requirement of citizens of the independent state, so that they are
becoming marginalized from the public sphere. Their contradictory
attitude that at once demonstrates nominal reception and practical
rejection of the obligatory state language unveils a high barrier inside
between their self-language and other-language. In this paper, the
ethnic Korean group-s conflicting linguistic identity is not seen as a
free and simple choice, but as a dynamic struggle and political process
in which the subject-s past experiences and memories intersect with
the external elements of pressure.
Abstract: The response of growth and yield of rainfed-chickpea
to population density should be evaluated based on long-term
experiments to include the climate variability. This is achievable just
by simulation. In this simulation study, this evaluation was done by
running the CYRUS model for long-term daily weather data of five
locations in Iran. The tested population densities were 7 to 59 (with
interval of 2) stands per square meter. Various functions, including
quadratic, segmented, beta, broken linear, and dent-like functions,
were tested. Considering root mean square of deviations and linear
regression statistics [intercept (a), slope (b), and correlation
coefficient (r)] for predicted versus observed variables, the quadratic
and broken linear functions appeared to be appropriate for describing
the changes in biomass and grain yield, and in harvest index,
respectively. Results indicated that in all locations, grain yield tends
to show increasing trend with crowding the population, but
subsequently decreases. This was also true for biomass in five
locations. The harvest index appeared to have plateau state across
low population densities, but decreasing trend with more increasing
density. The turning point (optimum population density) for grain
yield was 30.68 stands per square meter in Isfahan, 30.54 in Shiraz,
31.47 in Kermanshah, 34.85 in Tabriz, and 32.00 in Mashhad. The
optimum population density for biomass ranged from 24.6 (in
Tabriz) to 35.3 stands per square meter (Mashhad). For harvest index
it varied between 35.87 and 40.12 stands per square meter.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue – despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: A multi-agent system is developed here to predict
monthly details of the upcoming peak of the 24th solar magnetic
cycle. While studies typically predict the timing and magnitude of
cycle peaks using annual data, this one utilizes the unsmoothed
monthly sunspot number instead. Monthly numbers display more
pronounced fluctuations during periods of strong solar magnetic
activity than the annual sunspot numbers. Because strong magnetic
activities may cause significant economic damages, predicting
monthly variations should provide different and perhaps helpful
information for decision-making purposes. The multi-agent system
developed here operates in two stages. In the first, it produces twelve
predictions of the monthly numbers. In the second, it uses those
predictions to deliver a final forecast. Acting as expert agents, genetic
programming and neural networks produce the twelve fits and
forecasts as well as the final forecast. According to the results
obtained, the next peak is predicted to be 156 and is expected to
occur in October 2011- with an average of 136 for that year.
Abstract: The paper which is dedicated to describing the effect
made by the “significant other", presents the new model of
interrelation between self-reflection, the “significant other"
phenomenon and aggression. Tendencies of direction and type
frustration response developments in detail are discussed. New
results have been received through designing of the original
experiment. It is based on modifications of the “Picture – Frustration
Study" test by S. Rosenzweig.
Abstract: There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.
Abstract: The nature of consumer products causes the difficulty
in forecasting the future demands and the accuracy of the forecasts
significantly affects the overall performance of the supply chain
system. In this study, two data mining methods, artificial neural
network (ANN) and support vector machine (SVM), were utilized to
predict the demand of consumer products. The training data used was
the actual demand of six different products from a consumer product
company in Thailand. The results indicated that SVM had a better
forecast quality (in term of MAPE) than ANN in every category of
products. Moreover, another important finding was the margin
difference of MAPE from these two methods was significantly high
when the data was highly correlated.
Abstract: Meeting users- requirements is one of predictors of project success. There should be a match between the expectations of the users and the perception of key project personnel with respect to usability and functionality. The aim of this study is to make a comparison of key project personnel-s and potential users- (customer representatives) evaluations of the relative importance of usability and functionality factors in a software design project. Analytical Network Process (ANP) was used to analyze the relative importance of the factors. The results show that navigation and interaction are the most significant factors,andsatisfaction and efficiency are the least important factors for both groups. Further, it can be concluded that having similar orders and scores of usability and functionality factors for both groups shows that key project personnel have captured the expectations and requirements of potential users accurately.