Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: In EFL programs, rating scales used in writing
assessment are often constructed by intuition. Intuition-based scales
tend to provide inaccurate and divisive ratings of learners’ writing
performance. Hence, following an empirical approach, this study
attempted to develop a rating scale for elementary-level writing at an
EFL program in Saudi Arabia. Towards this goal, 98 students’ essays
were scored and then coded using comprehensive taxonomy of
writing constructs and their measures. An automatic linear modeling
was run to find out which measures would best predict essay scores.
A nonparametric ANOVA, the Kruskal-Wallis test, was then used to
determine which measures could best differentiate among scoring
levels. Findings indicated that there were certain measures that could
serve as either good predictors of essay scores or differentiators
among scoring levels, or both. The main conclusion was that a rating
scale can be empirically developed using predictive and
discriminative statistical tests.
Abstract: Today’s modern interconnected power system is
highly complex in nature. In this, one of the most important
requirements during the operation of the electric power system is the
reliability and security. Power and frequency oscillation damping
mechanism improve the reliability. Because of power system
stabilizer (PSS) low speed response against of major fault such as
three phase short circuit, FACTs devise that can control the network
condition in very fast time, are becoming popular. But FACTs
capability can be seen in a major fault present when nonlinear models
of FACTs devise and power system equipment are applied. To realize
this aim, the model of multi-machine power system with FACTs
controller is developed in MATLAB/SIMULINK using Sim Power
System (SPS) blockiest. Among the FACTs device, Static
synchronous series compensator (SSSC) due to high speed changes
its reactance characteristic inductive to capacitive, is effective power
flow controller. Tuning process of controller parameter can be
performed using different method. But Genetic Algorithm (GA)
ability tends to use it in controller parameter tuning process. In this
paper firstly POD controller is used to power oscillation damping.
But in this station, frequency oscillation dos not has proper damping
situation. So FOD controller that is tuned using GA is using that
cause to damp out frequency oscillation properly and power
oscillation damping has suitable situation.
Abstract: A new relative efficiency in linear model in reference is
instructed into the linear weighted regression, and its upper and lower
bound are proposed. In the linear weighted regression model, for the
best linear unbiased estimation of mean matrix respect to the
least-squares estimation, two new relative efficiencies are given, and
their upper and lower bounds are also studied.
Abstract: This paper presents a 4-DOF nonlinear model of a
cracked de Laval rotor-stator system derived based on Energy
Principles. The model has been used to simulate coupled torsionallateral
response of the faulty system with multiple parametric
excitations; rotor-stator-rub, a breathing transverse crack, eccentric
mass and an axial force. Nonlinearity of a “breathing” crack is
incorporated in the model using a simple hinge mechanism suitable
for a shallow crack. Response of the system while passing via its
critical speed with intermittent rotor-stator rub is analyzed. Effects of
eccentricity with phase and acceleration are investigated. Features of
crack, rub and eccentricity in vibration response are explored for
condition monitoring. The presence of a crack and rub are observable
in the power spectrum despite excitations by an axial force and rotor
unbalance. Obtained results are consistent with existing literature and
could be adopted into rotor condition monitoring strategies.
Abstract: This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
Abstract: A total of 150 meat type chickens comprising 50 each
of Arbor Acre, Marshall and Ross were used for this study which
lasted for 10 weeks at the Federal University of Agriculture,
Abeokuta, Nigeria. Growth performance data were collected from the
third week through week 10 and data obtained were analysed using
the Generalized Linear Model Procedure. Heritability estimates (h2)
for body dimensions carried out on the chicken strains ranged from
low to high. Marshall broiler chicken strain had the highest h2 for
body weight 0.46±0.04, followed by Arbor Acre and Ross with h2
being 0.38±0.12 and 0.26±0.06, respectively. The repeatability
estimates for body weight in the three broiler strains were high, and it
ranged from 0.70 at week 4 to 0.88 at week 10. Relationships
between the body weight and linear body measurements in the broiler
chicken strains were positive and highly significant (p > 0.05).
Abstract: There are many drivers who feel right A pillar of Japanese right-hand-drive car preventing visibility on turning right or left at intersection. On the other hand, there is a report that almost pedestrian accident is caused by the delay of finding pedestrian by drivers and this is found by drivers’ eye movement. Thus, we developed the evaluation method of quantification using drivers’ eye movement data by least squares estimation and we applied this method to commercial vehicle and evaluation the visibility. It is suggested that visibility of vehicle can be quantified and estimated by linear model obtained from experimental eye fixation data and information of vehicle dimensions.
Abstract: In this work, the main problem considered is the
detection and the isolation of the actuator fault. A new formulation of
the linear system is generated to obtain the conditions of the actuator
fault diagnosis. The proposed method is based on the representation
of the actuator as a subsystem connected with the process system in
cascade manner. The designed formulation is generated to obtain the
conditions of the actuator fault detection and isolation. Detectability
conditions are expressed in terms of the invertibility notions. An
example and a comparative analysis with the classic formulation
illustrate the performances of such approach for simple actuator fault
diagnosis by using the linear model of nuclear reactor.
Abstract: Active Front Steering system (AFS) provides an electronically controlled superposition of an angle to the steering wheel angle. This additional degree of freedom enables a continuous and driving-situation dependent on adaptation of the steering characteristics. In an active steering system, there needs be no fixed relationship between the steering wheel and the angle of the road wheels. Not only can the effective steering ratio be varied with speed, for example, but also the road wheel angles can be controlled by a combination of driver and computer inputs. Features like steering comfort, effort and steering dynamics are optimized and stabilizing steering interventions can be performed. In contrast to the conventional stability control, the yaw rate was fed back to AFS controller and the stability performance was optimized with Sliding Mode control (SMC) method. In addition, tire uncertainties have been taken into account in SM controller to provide the control robustness. In this paper, 3-DOF nonlinear model is used to design the AFS controller and 8-DOF nonlinear model is used to model the controlled vehicle.
Abstract: In the following article we begin from a multi-parameter unstable nonlinear model of a Quadrotor. We design a control to stabilize and assure the attitude of the device, starting off a linearized system at the equilibrium point of the null angles of Euler (hover),
which provides us a control with limited capacities at small angles of rotation of the vehicle in three dimensions. In order to clear this obstacle, we propose the identification of models in different angles by means of simulations and the design of a controller specifically implemented for the identification task, that in future works will allow the development of controllers according to fast and agile angles of Euler for Quadrotor.
Abstract: Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, myocardial infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a myocardial infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a generalized linear model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.
Abstract: The aim of this study was to obtain the optimal conditions for biogas production from anaerobic digestion of organic fraction of municipal solid waste (OFMSW) using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The highest level of biogas produced was 53.4 L/Kg VS at optimum pH, substrate concentration and total organic carbon of 6.5, 99gTS/L and 20.32 g/L respectively.
Abstract: In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.
Abstract: Due to uncertainty of wind velocity, wind power generators don’t have deterministic output power. Utilizing wind power generation and thermal power plants together create new concerns for operation engineers of power systems. In this paper, a model is presented to implement the uncertainty of load and generated wind power which can be utilized in power system operation planning. Stochastic behavior of parameters is simulated by generating scenarios that can be solved by deterministic method. A mixed-integer linear programming method is used for solving deterministic generation scheduling problem. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. The results show affectivity of piecewise linear model in unit commitment problems. Also using linear programming causes a considerable reduction in calculation times and guarantees convergence to the global optimum. Neglecting the uncertainty of wind velocity causes higher cost assessment of generation scheduling.
Abstract: This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly Ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.
Abstract: Synthetic oily wastewaters were prepared from metal working fluids (MWF). Electrocoagulation experiments were performed under constant voltage application. The current, conductivity, pH, dissolved oxygen concentration and temperature were recorded on line at every 5 seconds during the experiments. Effects of applied voltage differences, electrode materials and distance between electrodes on removal efficiency have been investigated. According to the experimental results, the treatment of MWF wastewaters by iron electrodes rather than aluminum and stainless steel was much quicker; and the distance between electrodes should be less than 1cm. The electrocoagulation process was modeled by using block oriented approach and found out that it can be modeled as a single input and multiple output system. Modeling studies indicates that the electrocoagulation process has a nonlinear model structure.
Abstract: The national economy development affects the vehicle
ownership which ultimately increases fuel consumption. The rise of
the vehicle ownership is dominated by the increasing number of
motorcycles. This research aims to analyze and identify the
characteristics of fuel consumption, the city transportation system,
and to analyze the relationship and the effect of the city
transportation system on the fuel consumption. A multivariable
analysis is used in this study. The data analysis techniques include: a
Multivariate Multivariable Analysis by using the R software. More
than 84% of fuel on Java is consumed in metropolitan and large
cities. The city transportation system variables that strongly effect the
fuel consumption are population, public vehicles, private vehicles and
private bus. This method can be developed to control the fuel
consumption by considering the urban transport system and city
tipology. The effect can reducing subsidy on the fuel consumption,
increasing state economic.
Abstract: The Time-Domain Boundary Element Method (TDBEM)
is a well known numerical technique that handles quite
properly dynamic analyses considering infinite dimension media.
However, when these analyses are also related to nonlinear behavior,
very complex numerical procedures arise considering the TD-BEM,
which may turn its application prohibitive. In order to avoid this
drawback and model nonlinear infinite media, the present work
couples two BEM formulations, aiming to achieve the best of two
worlds. In this context, the regions expected to behave nonlinearly
are discretized by the Domain Boundary Element Method (D-BEM),
which has a simpler mathematical formulation but is unable to deal
with infinite domain analyses; the TD-BEM is employed as in the
sense of an effective non-reflexive boundary. An iterative procedure
is considered for the coupling of the TD-BEM and D-BEM, which is
based on a relaxed renew of the variables at the common interfaces.
Elastoplastic models are focused and different time-steps are allowed
to be considered by each BEM formulation in the coupled analysis.
Abstract: the data of Taiwanese 8th grader in the 4th cycle of
Trends in International Mathematics and Science Study (TIMSS) are
analyzed to examine the influence of the science teachers- preference
in experimental teaching on the relationships between the affective
variables ( the perceived usefulness of science, ease of using science
and science learning interest) and the academic achievement in science.
After dealing with the missing data, 3711 students and 145 science
teacher-s data were analyzed through a Hierarchical Linear Modeling
technique. The major objective of this study was to determine the role
of the experimental teaching moderates the relationship between
perceived usefulness and achievement.