Abstract: Accounts of language acquisition differ significantly in their treatment of the role of prediction in language learning. In particular, nativist accounts posit that probabilistic learning about words and word sequences has little to do with how children come to use language. The accuracy of this claim was examined by testing whether distributional probabilities and frequency contributed to how well 3-4 year olds repeat simple word chunks. Corresponding chunks were the same length, expressed similar content, and were all grammatically acceptable, yet the results of the study showed marked differences in performance when overall distributional frequency varied. It was found that a distributional model of language predicted the empirical findings better than a number of other models, replicating earlier findings and showing that children attend to distributional probabilities in an adult corpus. This suggested that language is more prediction-and-error based, rather than on abstract rules which nativist camps suggest.
Abstract: A new observer based fault detection and diagnosis
scheme for predicting induction motors- faults is proposed in this
paper. Prediction of incipient faults, using different variants of
Kalman filter and their relative performance are evaluated. Only soft
faults are considered for this work. The data generation, filter
convergence issues, hypothesis testing and residue estimates are
addressed. Simulink model is used for data generation and various
types of faults are considered. A comparative assessment of the
estimates of different observers associated with these faults is
included.
Abstract: In aerospace applications, interactions of airflow with
aircraft structures can result in undesirable structural deformations.
This structural deformation in turn, can be predicted if the natural
modes of the structure are known. This can be achieved through
conventional modal testing that requires a known excitation force in
order to extract these dynamic properties. This technique can be
experimentally complex because of the need for artificial excitation
and it is also does not represent actual operational condition. The
current work presents part of research work that address the practical
implementation of operational modal analysis (OMA) applied to a
cantilevered hybrid composite plate employing single contactless
sensing system via laser vibrometer. OMA technique extracts the
modal parameters based only on the measurements of the dynamic
response. The OMA results were verified with impact hammer modal
testing and good agreement was obtained.
Abstract: The objective of this study is to investigate fire
behaviors, experimentally and numerically, in a scaled version of an
underground station. The effect of ventilation velocity on the fire is
examined. Fire experiments are simulated by burning 10 ml
isopropyl alcohol fuel in a fire pool with dimensions 5cm x 10cm x 4
mm at the center of 1/100 scaled underground station model. A
commercial CFD program FLUENT was used in numerical
simulations. For air flow simulations, k-ω SST turbulence model and
for combustion simulation, non-premixed combustion model are
used. This study showed that, the ventilation velocity is increased
from 1 m/s to 3 m/s the maximum temperature in the station is found
to be less for ventilation velocity of 1 m/s. The reason for these
experimental result lies on the relative dominance of oxygen supply
effect on cooling effect. Without piston effect, maximum temperature
occurs above the fuel pool. However, when the ventilation velocity
increased the flame was tilted in the direction of ventilation and the
location of maximum temperature moves along the flow direction.
The velocities measured experimentally in the station at different
locations are well matched by the CFD simulation results. The
prediction of general flow pattern is satisfactory with the smoke
visualization tests. The backlayering in velocity is well predicted by
CFD simulation. However, all over the station, the CFD simulations
predicted higher temperatures compared to experimental
measurements.
Abstract: In the present Jordan hotels scenario, service quality is
a vital competitive policy to keep customer support and build great
base. Hotels are trying to win customer loyalty by providing enhanced
quality services. This paper attempts to examine the impact of tourism
service quality dimension in the Jordanian five star hotels. A total of
322 surveys were administrated to tourists who were staying at three
branches Marriott hotel in Jordan. The results show that dimensions of
service quality such as empathy, reliability, responsiveness and
tangibility significantly predict customer loyalty. Specifically, among
the dimension of tourism service quality, the most significant predictor
of customer loyalty is tangibility. This paper implies that five star
hotels in Jordan should also come forward and try their best to present
better tourism service quality to win back their customers- loyalty.
Abstract: In this study is presented a general methodology to
predict the performance of a continuous near-critical fluid extraction
process to remove compounds from aqueous solutions using hollow
fiber membrane contactors. A comprehensive 2D mathematical
model was developed to study Porocritical extraction process. The
system studied in this work is a membrane based extractor of ethanol
and acetone from aqueous solutions using near-critical CO2.
Predictions of extraction percentages obtained by simulations have
been compared to the experimental values reported by Bothun et al.
[5]. Simulations of extraction percentage of ethanol and acetone
show an average difference of 9.3% and 6.5% with the experimental
data, respectively. More accurate predictions of the extraction of
acetone could be explained by a better estimation of the transport
properties in the aqueous phase that controls the extraction of this
solute.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.
Abstract: Salinity is a measure of the amount of salts in the
water. Total Dissolved Solids (TDS) as salinity parameter are often
determined using laborious and time consuming laboratory tests, but
it may be more appropriate and economical to develop a method
which uses a more simple soil salinity index. Because dissolved ions
increase salinity as well as conductivity, the two measures are
related. The aim of this research was determine of constant
coefficients for predicting of Total Dissolved Solids (TDS) based on
Electrical Conductivity (EC) with Statistics of Correlation
coefficient, Root mean square error, Maximum error, Mean Bias
error, Mean absolute error, Relative error and Coefficient of residual
mass. For this purpose, two experimental areas (S1, S2) of Khuzestan
province-IRAN were selected and four treatments with three
replications by series of double rings were applied. The treatments
were included 25cm, 50cm, 75cm and 100cm water application. The
results showed the values 16.3 & 12.4 were the best constant
coefficients for predicting of Total Dissolved Solids (TDS) based on
EC in Pilot S1 and S2 with correlation coefficient 0.977 & 0.997 and
191.1 & 106.1 Root mean square errors (RMSE) respectively.
Abstract: This paper presents the possibilities of using Weibull statistical distribution in modeling the distribution of defects in ERP systems. There follows a case study, which examines helpdesk records of defects that were reported as the result of one ERP subsystem upgrade. The result of the applied modeling is in modeling the reliability of the ERP system from a user perspective with estimated parameters like expected maximum number of defects in one day or predicted minimum of defects between two upgrades. Applied measurement-based analysis framework is proved to be suitable in predicting future states of the reliability of the observed ERP subsystems.
Abstract: Several valve stiction models have been proposed in the literature to help understand and study the behavior of sticky valves. In this paper, an alternative black-box modeling approach based on Neural Network (NN) is presented. It is shown that with proper network type and optimum model structures, the performance of the developed NN stiction model is comparable to other established method. The resulting NN model is also tested for its robustness against the uncertainty in the stiction parameter values. Predictive mode operation also shows excellent performance of the proposed model for multi-steps ahead prediction.
Abstract: The three steps of the standard one-way nested grid
for a regional scale of the third generation WAve Model Cycle 4
(WAMC4) is scrutinized. The model application is enabled to solve
the energy balance equation on a coarse resolution grid in order to
produce boundary conditions for a smaller area by the nested grid
technique. In the present study, the model takes a full advantage of the
fine resolution of wind fields in space and time produced by the available
U.S. Navy Global Atmospheric Prediction System (NOGAPS)
model with 1 degree resolution. The nested grid application of the
model is developed in order to gradually increase the resolution from
the open ocean towards the South China Sea (SCS) and the Gulf of
Thailand (GoT) respectively. The model results were compared with
buoy observations at Ko Chang, Rayong and Huahin locations which
were obtained from the Seawatch project. In addition, the results were
also compared with Satun based weather station which was provided
from Department of Meteorology, Thailand. The data collected from
this station presented the significant wave height (Hs) reached 12.85
m. The results indicated that the tendency of the Hs from the model
in the spherical coordinate propagation with deep water condition in
the fine grid domain agreed well with the Hs from the observations.
Abstract: This paper proposes transient angle stability
agents to enhance power system stability. The proposed transient
angle stability agents divided into two strategy agents. The
first strategy agent is a prediction agent that will predict power
system instability. According to the prediction agent-s output,
the second strategy agent, which is a control agent, is automatically
calculating the amount of active power reduction that can
stabilize the system and initiating a control action. The control
action considered is turbine fast valving. The proposed strategies
are applied to a realistic power system, the IEEE 50-
generator system. Results show that the proposed technique can
be used on-line for power system instability prediction and control.
Abstract: Environmental considerations have become an integral part of developmental thinking and decision making in many countries. It is growing rapidly in importance as a discipline of its own. Preventive approaches have been used at the evolutional process of environmental management as a broad and dynamic system for dealing with pollution and environmental degradation. In this regard, Environmental Assessment as an activity for identification and prediction of project’s impacts carried out in the world and its legal significance dates back to late 1960. In Iran, according to the Article 2 of Environmental Protection Act, Environmental Impact Assessment (EIA) should be prepared for seven categories of project. This article has been actively implementing by Department of Environment at 1997. World Bank in 1989 attempted to introducing application of Environmental Assessment for making decision about projects which are required financial assistance in developing countries. So, preparing EIA for obtaining World Bank loan was obligated. Alborz Project is one of the World Bank Projects in Iran which is environmentally significant. Seven out of ten W.B safeguard policies were considered at this project. In this paper, Alborz project, objectives, safeguard policies and role of environmental management will be elaborated
Abstract: A fuzzy predictive pursuit guidance is proposed as an
alternative to the conventional methods. The purpose of this scheme
is to obtain a stable and fast guidance. The noise effects must be
reduced in homing missile guidance to get an accurate control. An
aerodynamic missile model is simulated first and a fuzzy predictive
pursuit control algorithm is applied to reduce the noise effects. The
performance of this algorithm is compared with the performance of
the classical proportional derivative control. Stability analysis of the
proposed guidance method is performed and compared with the
stability properties of other guidance methods. Simulation results
show that the proposed method provides the satisfying performance.
Abstract: A theoretical study of the rigidities of slabs with
circular voids oriented in the longitudinal and in the transverse
direction is discussed. Equations are presented for predicting the
bending and torsional rigidities of the voided slabs. This paper
summarizes the results of an extensive literature search and initial
review of the current methods of analyzing voided slab. The various
methods of calculating the equivalent plate parameters, which are
necessary for two-dimensional analysis, are also reviewed. Static
deflections on voided slabs are shown to be in good agreement with
proposed equation.
Abstract: The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.
Abstract: Model Predictive Control (MPC) is an established control
technique in a wide range of process industries. The reason for
this success is its ability to handle multivariable systems and systems
having input, output or state constraints. Neverthless comparing to
PID controller, the implementation of the MPC in miniaturized
devices like Field Programmable Gate Arrays (FPGA) and microcontrollers
has historically been very small scale due to its complexity in
implementation and its computation time requirement. At the same
time, such embedded technologies have become an enabler for future
manufacturing enterprisers as well as a transformer of organizations
and markets. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and applied
control technique in the industrial engineering. In this paper, we
propose an efficient firmware for the implementation of constrained
MPC in the performed STM32 microcontroller using interior point
method. Indeed, performances study shows good execution speed
and low computational burden. These results encourage to develop
predictive control algorithms to be programmed in industrial standard
processes. The PID anti windup controller was also implemented in
the STM32 in order to make a performance comparison with the
MPC. The main features of the proposed constrained MPC framework
are illustrated through two examples.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: Developing a stable early warning system (EWS)
model that is capable to give an accurate prediction is a challenging
task. This paper introduces k-nearest neighbour (k-NN) method
which never been applied in predicting currency crisis before with the
aim of increasing the prediction accuracy. The proposed k-NN
performance depends on the choice of a distance that is used where in
our analysis; we take the Euclidean distance and the Manhattan as a
consideration. For the comparison, we employ three other methods
which are logistic regression analysis (logit), back-propagation neural
network (NN) and sequential minimal optimization (SMO). The
analysis using datasets from 8 countries and 13 macro-economic
indicators for each country shows that the proposed k-NN method
with k = 4 and Manhattan distance performs better than the other
methods.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible thermal multi-component gas
mixture flows in pipes. The set of the mass, momentum and enthalpy
conservation equations for gas phase is solved. Thermo-physical
properties of multi-component gas mixture are calculated by solving
the Equation of State (EOS) model. The Soave-Redlich-Kwong
(SRK-EOS) model is chosen. Gas mixture viscosity is calculated on
the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical
analysis on rapid decompression in conventional dry gases is
performed by using the proposed mathematical model. The model is
validated on measured values of the decompression wave speed in
dry natural gas mixtures. All predictions show excellent agreement
with the experimental data at high and low pressure. The presented
model predicts the decompression in dry natural gas mixtures much
better than GASDECOM and OLGA codes, which are the most
frequently-used codes in oil and gas pipeline transport service.