Abstract: In this paper a novel, simple and reliable digital firing
scheme has been implemented for speed control of three-phase
induction motor using ac voltage controller. The system consists of
three-phase supply connected to the three-phase induction motor via
three triacs and its control circuit. The ac voltage controller has three
modes of operation depending on the shape of supply current. The
performance of the induction motor differs in each mode where the
speed is directly proportional with firing angle in two modes and
inversely in the third one. So, the control system has to detect the
current mode of operation to choose the correct firing angle of triacs.
Three sensors are used to feed the line currents to control system to
detect the mode of operation. The control strategy is implemented
using a low cost Xilinx Spartan-3E field programmable gate array
(FPGA) device. Three PI-controllers are designed on FPGA to
control the system in the three-modes. Simulation of the system is
carried out using PSIM computer program. The simulation results
show stable operation for different loading conditions especially in
mode 2/3. The simulation results have been compared with the
experimental results from laboratory prototype.
Abstract: In this paper, we develop quartic nonpolynomial
spline method for the numerical solution of third order two point
boundary value problems. It is shown that the new method gives
approximations, which are better than those produced by other spline
methods. Convergence analysis of the method is discussed through
standard procedures. Two numerical examples are given to illustrate
the applicability and efficiency of the novel method.
Abstract: E-Learning systems are used by many learners and
teachers. The developer is developing the e-Learning system. However,
the developer cannot do system construction to satisfy all of
users- demands. We discuss a method of constructing e-Learning
systems where learners and teachers can design, try to use, and share
extending system functions that they want to use; which may be nally
added to the system by system managers.
Abstract: In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.
Abstract: As a vital activity for companies, new product
development (NPD) is also a very risky process due to the high
uncertainty degree encountered at every development stage and the
inevitable dependence on how previous steps are successfully
accomplished. Hence, there is an apparent need to evaluate new
product initiatives systematically and make accurate decisions under
uncertainty. Another major concern is the time pressure to launch a
significant number of new products to preserve and increase the
competitive power of the company. In this work, we propose an
integrated decision-making framework based on neural networks and
fuzzy logic to make appropriate decisions and accelerate the
evaluation process. We are especially interested in the two initial
stages where new product ideas are selected (go/no go decision) and
the implementation order of the corresponding projects are
determined. We show that this two-staged intelligent approach allows
practitioners to roughly and quickly separate good and bad product
ideas by making use of previous experiences, and then, analyze a
more shortened list rigorously.
Abstract: How to simulate experimentally the air flow and heat
transfer under microgravity on the ground is important, which has not
been completely solved so far. Influence of gravity on air natural
convection results in convection heat transfer on ground difference
from that on orbit. In order to obtain air temperature and velocity
deviations of manned spacecraft during terrestrial thermal test,
dimensionless number analysis and numerical simulation analysis are
performed. The calculated temperature distribution and velocity
distribution of the horizontal test cases are compared to the vertical
cases. The results show that the influence of gravity is neglected for
facility drawer racks and more obvious for vertical cabins.
Abstract: The significant effects of the interactions between the
system boundaries and the near wall molecules in miniaturized
gaseous devices lead to the formation of the Knudsen layer in which
the Navier-Stokes-Fourier (NSF) equations fail to predict the correct
associated phenomena. In this paper, the well-known lattice
Boltzmann method (LBM) is employed to simulate the fluid flow and
heat transfer processes in rarefied gaseous micro media. Persuaded
by the problematic deficiency of the LBM in capturing the Knudsen
layer phenomena, present study tends to concentrate on the effective
molecular mean free path concept the main essence of which is to
compensate the incapability of this mesoscopic method in dealing
with the momentum and energy transport within the above mentioned
kinetic boundary layer. The results show qualitative and quantitative
accuracy comparable to the solutions of the linearized Boltzmann
equation or the DSMC data for the Knudsen numbers of O (1) .
Abstract: The “PYRAMIDS" Block Cipher is a symmetric encryption algorithm of a 64, 128, 256-bit length, that accepts a variable key length of 128, 192, 256 bits. The algorithm is an iterated cipher consisting of repeated applications of a simple round transformation with different operations and different sequence in each round. The algorithm was previously software implemented in Cµ code. In this paper, a hardware implementation of the algorithm, using Field Programmable Gate Arrays (FPGA), is presented. In this work, we discuss the algorithm, the implemented micro-architecture, and the simulation and implementation results. Moreover, we present a detailed comparison with other implemented standard algorithms. In addition, we include the floor plan as well as the circuit diagrams of the various micro-architecture modules.
Abstract: Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.
Abstract: This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.
Abstract: This paper details a new concept of using compressed air as a potential zero pollution power source for motorbikes. In place of an internal combustion engine, the motorbike is equipped with an air turbine transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor diameters, casing diameters and ratio of rotor to casing diameters of the turbine have been considered and analyzed. It is concluded that the work output is found optimum for some typical values of rotor / casing diameter ratios. In this study, the maximum power works out to 3.825 kW (5.20 HP) for casing diameter of 200 mm and rotor to casing diameter ratio of 0.65 to 0.60 which is sufficient to run motorbike.
Abstract: The present study was conducted to observe the effect
of Plantago psyllium on blood glucose and cholesterol levels in
normal and alloxan induced diabetic rats. To investigate the effect of
Plantago psyllium 40 rats were included in this study divided into
four groups of ten rats in each group. One group A was normal,
second group B was diabetic, third group C was non diabetic and
hypercholesterolemic and fourth group D was diabetic and
hypercholesterolemic. Two groups B and D were made diabetic by
intraperitonial injection of alloxan dissolved in 1mL distilled water at
a dose of 125mg/Kg of body weight. Two groups C and D were
made hypercholesterolemic by oral administration of powder
cholesterol (1g/Kg of body weight). The blood samples from all the
rats were collected from coccygial vein on 1st day, then on 21st and
42nd day respectively. All the samples were analyzed for blood
glucose and cholesterol level by using enzymatic kits. The blood
glucose and cholesterol levels of treated groups of rats showed
significant reduction after 7 weeks of treatment with Plantago
psyllium. By statistical analysis of results it was found that Plantago
psyllium has anti-diabetic and hypocholesterolemic activity in
diabetic and hypercholesterolemic albino rats.
Abstract: This study investigated the relationship between urban
and rural ozone concentrations and quantified the extent to which
ambient rural conditions and the concentrations of other pollutants
can be used to predict urban ozone concentrations. The study
describes the variations of ozone in weekday and weekends as well as
the daily maximum recorded at selected monitoring stations. The
results showed that Putrajaya station had the highest concentrations
of O3 on weekend due the titration of NO during the weekday.
Additionally, Jerantut had the lowest average concentration with a
reading value high on Wednesdays. The comparisons of average and
maximum concentrations of ozone for the three stations showed that
the strongest significant correlation is recorded in Jerantut station
with the value R2= 0.769. Ozone concentrations originating from a
neighbouring urban site form a better predictor to the urban ozone
concentrations than widespread rural ozone at some levels of
temporal averaging. It is found that in urban and rural of Malaysian
peninsular, the concentration of ozone depends on the concentration
of NOx and seasonal meteorological factors. The HYSPLIT Model
(the northeast monsoon) showed that the wind direction can also
influence the concentration of ozone in the atmosphere in the studied
areas.
Abstract: Social Business Process Management (SBPM)
promises to overcome limitations of traditional BPM by allowing
flexible process design and enactment through the involvement of
users from a social community. This paper proposes a meta-model
and architecture for socially driven business process management
systems. It discusses the main facets of the architecture such as goalbased
role assignment that combines social recommendations with
user profile, and process recommendation, through a real example of
a charity organization.
Abstract: This paper proposes a method which reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory error correction code. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting codes. The genetic algorithm is employed to solve the non linear power optimization problem. The method is applied to two commonly used SEC-DED codes: standard Hamming and odd column weight Hsiao codes. Experiments were performed to show the performance of the proposed method.
Abstract: In this work, we present a comparison between
different techniques of image compression. First, the image is
divided in blocks which are organized according to a certain scan.
Later, several compression techniques are applied, combined or
alone. Such techniques are: wavelets (Haar's basis), Karhunen-Loève
Transform, etc. Simulations show that the combined versions are the
best, with minor Mean Squared Error (MSE), and higher Peak Signal
to Noise Ratio (PSNR) and better image quality, even in the presence
of noise.
Abstract: The purposes of this study are 1) to identify
learning styles of university students in Bangkok, and 2) to study
the frequency of the relevant instructional context of the identified
learning styles. Learning Styles employed in this study are those of
Honey and Mumford, which include 1) Reflectors, 2) Theorists, 3)
Pragmatists, and 4) Activists. The population comprises 1383
students and 5 lecturers. Research tools are 2 questionnaires – one
used for identifying students- learning styles, and the other used for
identifying the frequency of the relevant instructional context of
the identified learning styles.
The research findings reveal that 32.30 percent - are Activists,
while 28.10 percent are Theorists, 20.10 are Reflectors, and 19.50
are Pragmatists. In terms of the relevant instructional context of the
identified 4 learning styles, it is found that the frequency level of
the instructional context is totally in high level. Moreover, 2 lists of
the context being conducted most frequently are 'Lead'in activity
to review background knowledge,- and 'Information retrieval
report.' And these two activities serve the learning styles of
theorists and activists. It is, therefore, suggested that more
instructional context supporting the activists, the majority of the
population, learning best by doing, as well as emotional learning
situation should be added.
Abstract: A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: The main criteria of designing in the most hydraulic
constructions essentially are based on runoff or discharge of water. Two of those important criteria are runoff and return period. Mostly,
these measures are calculated or estimated by stochastic data.
Another feature in hydrological data is their impreciseness.
Therefore, in order to deal with uncertainty and impreciseness, based
on Buckley-s estimation method, a new fuzzy method of evaluating hydrological measures are developed. The method introduces
triangular shape fuzzy numbers for different measures in which both
of the uncertainty and impreciseness concepts are considered. Besides, since another important consideration in most of the
hydrological studies is comparison of a measure during different
months or years, a new fuzzy method which is consistent with special form of proposed fuzzy numbers, is also developed. Finally, to
illustrate the methods more explicitly, the two algorithms are tested on one simple example and a real case study.