Abstract: Induction machine models used for steady-state and
transient analysis require machine parameters that are usually
considered design parameters or data. The knowledge of induction
machine parameters is very important for Indirect Field Oriented
Control (IFOC). A mismatched set of parameters will degrade the
response of speed and torque control. This paper presents an
improvement approach on rotor time constant adaptation in IFOC for
Induction Machines (IM). Our approach tends to improve the
estimation accuracy of the fundamental model for flux estimation.
Based on the reduced order of the IM model, the rotor fluxes and
rotor time constant are estimated using only the stator currents and
voltages. This reduced order model offers many advantages for real
time identification parameters of the IM.
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 study has investigated a vehicle Lumped
Parameter Model (LPM) in frontal crash. There are several ways for
determining spring and damper characteristics and type of problem
shall be considered as system identification. This study use Genetic
Algorithm (GA) procedure, being an effective procedure in case of
optimization issues, for optimizing errors, between target data
(experimental data) and calculated results (being obtained by
analytical solving). In this study analyzed model in 5-DOF then
compared our results with 5-DOF serial model. Finally, the response
of model due to external excitement is investigated.
Abstract: Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.
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: The Brazilian legislation has only established
diagnostic reference levels (DRLs) in terms of Multiple Scan
Average Dose (MSAD) as a quality control parameter for computed
tomography (CT) scanners. Compliance with DRLs can be verified
by measuring the Computed Tomography Kerma Index (Ca,100) with
a pencil ionization chamber or by obtaining the kerma distribution in
CT scans with radiochromic films or rod shape lithium fluoride
termoluminescent dosimeters (TLD-100). TL dosimeters were used
to record kerma profiles and to determine MSAD values of a Bright
Speed model GE CT scanner. Measurements were done with
radiochromic films and TL dosimeters distributed in cylinders
positioned in the center and in four peripheral bores of a standard
polymethylmethacrylate (PMMA) body CT dosimetry phantom.
Irradiations were done using a protocol for adult chest. The
maximum values were found at the midpoint of the longitudinal axis.
The MSAD values obtained with three dosimetric techniques were
compared.
Abstract: Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrollments of the University of Alabama. In recent years, a number of techniques have been proposed for forecasting based on fuzzy set theory methods. These methods have either used enrollment numbers or differences of enrollments as the universe of discourse. We propose using the year to year percentage change as the universe of discourse. In this communication, the approach of Jilani, Burney, and Ardil is modified by using the year to year percentage change as the universe of discourse. We use enrollment figures for the University of Alabama to illustrate our proposed method. The proposed method results in better forecasting accuracy than existing models.
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: Characteristics of ad hoc networks and even their existence depend on the nodes forming them. Thus, services and applications designed for ad hoc networks should adapt to this dynamic and distributed environment. In particular, multicast algorithms having reliability and scalability requirements should abstain from centralized approaches. We aspire to define a reliable and scalable multicast protocol for ad hoc networks. Our target is to utilize epidemic techniques for this purpose. In this paper, we present a brief survey of epidemic algorithms for reliable multicasting in ad hoc networks, and describe formulations and analytical results for simple epidemics. Then, P2P anti-entropy algorithm for content distribution and our prototype simulation model are described together with our initial results demonstrating the behavior of the algorithm.
Abstract: It is essential to have a uniform and calm flow field
for a settling tank to have high performance. In general, the
recirculation zones always occurred in sedimentation tanks. The
presence of these regions may have different effects. The nonuniformity
of the velocity field, the short-circuiting at the surface and
the motion of the jet at the bed of the tank that occurs because of the
recirculation in the sedimentation layer, are affected by the geometry
of the tank. There are some ways to decrease the size of these dead
zones, which would increase the performance. One of the ways is to
use a suitable baffle configuration. In this study, the presence of
baffle with different position has been investigated by a finite volume
method, with VOF (Volume of Fluid) model. Besides, the k-ε
turbulence model is used in the numerical calculations. The results
indicate that the best position of the baffle is obtained when the
volume of the recirculation region is minimized or is divided to
smaller part and the flow field trend to be uniform in the settling
zone.
Abstract: This paper adopts a notion of expectation-perception
gap of systems users as information systems (IS) failure. Problems
leading to the expectation-perception gap are identified and modelled
as five interrelated discrepancies or gaps throughout the process of
information systems development (ISD). It describes an empirical
study on how systems developers and users perceive the size of each
gap and the extent to which each problematic issue contributes to the
gap. The key to achieving success in ISD is to keep the expectationperception
gap closed by closing all 5 pertaining gaps. The gap model
suggests that most factors in IS failure are related to organizational,
cognitive and social aspects of information systems design.
Organization requirement analysis, being the weakest link of IS
development, is particularly worthy of investigation.
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: This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.
Abstract: The information revealed by derivatives can help to
better characterize digital near-end crosstalk signatures with the
ultimate goal of identifying the specific aggressor signal.
Unfortunately, derivatives tend to be very sensitive to even low
levels of noise. In this work we approximated the derivatives of both
quiet and noisy digital signals using a wavelet-based technique. The
results are presented for Gaussian digital edges, IBIS Model digital
edges, and digital edges in oscilloscope data captured from an actual
printed circuit board. Tradeoffs between accuracy and noise
immunity are presented. The results show that the wavelet technique
can produce first derivative approximations that are accurate to
within 5% or better, even under noisy conditions. The wavelet
technique can be used to calculate the derivative of a digital signal
edge when conventional methods fail.
Abstract: International markets driven forces are changing
continuously, therefore companies need to gain a competitive edge in
such markets. Improving the company's products, processes and
practices is no longer auxiliary. Lean production is a production
management philosophy that consolidates work tasks with minimum
waste resulting in improved productivity. Lean production practices
can be mapped into many production areas. One of these is
Manufacturing Equipment and Technology (MET). Many lean
production practices can be implemented in MET, namely, specific
equipment configurations, total preventive maintenance, visual
control, new equipment/ technologies, production process
reengineering and shared vision of perfection.The purpose of this
paper is to investigate the implementation level of these six practices
in Jordanian industries. To achieve that a questionnaire survey has
been designed according to five-point Likert scale. The questionnaire
is validated through pilot study and through experts review. A sample
of 350 Jordanian companies were surveyed, the response rate was
83%. The respondents were asked to rate the extent of
implementation for each of practices. A relationship conceptual
model is developed, hypotheses are proposed, and consequently the
essential statistical analyses are then performed. An assessment tool
that enables management to monitor the progress and the
effectiveness of lean practices implementation is designed and
presented. Consequently, the results show that the average
implementation level of lean practices in MET is 77%, Jordanian
companies are implementing successfully the considered lean
production practices, and the presented model has Cronbach-s alpha
value of 0.87 which is good evidence on model consistency and
results validation.
Abstract: Sedimentation formation is a complex hydraulic phenomenon that has emerged as a major operational and maintenance consideration in modern hydraulic engineering in general and river engineering in particular. Sediments accumulation along the river course and their eventual storage in a form of islands affect water intake in the canal systems that are fed by the storage reservoirs. Without proper management, sediment transport can lead to major operational challenges in water distribution system of arid regions like the Dez and Hamidieh command areas. The paper aims to investigate sedimentation in the Western Canal of Dez Diversion Weir using the SHARC model and compare the results with the two intake structures of the Hamidieh dam in Iran using SSIIM model. The objective was to identify the factors which influence the process, check reliability of outcome and provide ways in which to mitigate the implications on operation and maintenance of the structures. Results estimated sand and silt bed loads concentrations to be 193 ppm and 827ppm respectively. This followed ,ore or less similar pattern in Hamidieh where the sediment formation impeded water intake in the canal system. Given the available data on average annual bed loads and average suspended sediment loads of 165ppm and 837ppm in the Dez, there was a significant statistical difference (16%) between the sand grains, whereas no significant difference (1.2%) was find in the silt grain sizes. One explanation for such finding being that along the 6 Km river course there was considerable meandering effects which explains recent shift in the hydraulic behavior along the stream course under investigation. The sand concentration in downstream relative to present state of the canal showed a steep descending curve. Sediment trapping on the other hand indicated a steep ascending curve. These occurred because the diversion weir was not considered in the simulation model. The comparative study showed very close similarities in the results which explains the fact that both software can be used as accurate and reliable analytical tools for simulation of the sedimentation in hydraulic engineering.
Abstract: In this work we study analytically and numerically the
performance of the mean heave motion of an OWC coupled with the
governing equation of the spreading ocean waves due to the wide
variation in an open parabolic channel with constant depth. This
paper considers that the ocean wave propagation is under the
assumption of a shallow flow condition. In order to verify the effect
of the waves in the OWC firstly we establish the analytical model in
a non-dimensional form based on the energy equation. The proposed
wave-power system has to aims: one is to perturb the ocean waves as
a consequence of the channel shape in order to concentrate the
maximum ocean wave amplitude in the neighborhood of the OWC
and the second is to determine the pressure and volume oscillation of
air inside the compression chamber.
Abstract: A complete CAD procedure to model a twisted-bladed
vertical-axis wind turbine (VAWT) is presented with the aim of
determining some practical guidelines to be used for the generation
of an easily-meshable CAD geometry to be adopted as the basis of
both CFD and FEM numerical simulations.
Abstract: Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.