Abstract: In the normal operation conditions of a pico satellite,
conventional Unscented Kalman Filter (UKF) gives sufficiently good
estimation results. However, if the measurements are not reliable
because of any kind of malfunction in the estimation system, UKF
gives inaccurate results and diverges by time. This study, introduces
Robust Unscented Kalman Filter (RUKF) algorithms with the filter
gain correction for the case of measurement malfunctions. By the use
of defined variables named as measurement noise scale factor, the
faulty measurements are taken into the consideration with a small
weight and the estimations are corrected without affecting the
characteristic of the accurate ones. Two different RUKF algorithms,
one with single scale factor and one with multiple scale factors, are
proposed and applied for the attitude estimation process of a pico
satellite. The results of these algorithms are compared for different
types of measurement faults in different estimation scenarios and
recommendations about their applications are given.
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: Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.
Abstract: In this paper we consider the problem of change
detection and non stationary signals tracking. Using parametric
estimation of signals based on least square lattice adaptive filters we
consider for change detection statistical parametric methods using
likelihood ratio and hypothesis tests. In order to track signals
dynamics, we introduce a compensation procedure in the adaptive
estimation. This will improve the adaptive estimation performances
and fasten it-s convergence after changes detection.
Abstract: Direction of Arrival estimation refers to defining a mathematical function called a pseudospectrum that gives an indication of the angle a signal is impinging on the antenna array. This estimation is an efficient method of improving the quality of service in a communication system by focusing the reception and transmission only in the estimated direction thereby increasing fidelity with a provision to suppress interferers. This improvement is largely dependent on the performance of the algorithm employed in the estimation. Many DOA algorithms exists amongst which are MUSIC, Root-MUSIC and ESPRIT. In this paper, performance of these three algorithms is analyzed in terms of complexity, accuracy as assessed and characterized by the CRLB and memory requirements in various environments and array sizes. It is found that the three algorithms are high resolution and dependent on the operating environment and the array size.
Abstract: This paper presents the development of an MODAPTS based cost estimating system to help designers in estimating the manufacturing cost of a assembly products which is belonged from the workers in working fields. Competitiveness of manufacturing cost is getting harder because of the development of Information and telecommunication, but also globalization. Therefore, the accuracy of the assembly cost estimation is getting important. DFA and MODAPTS is useful method for measuring the working hour. But these two methods are used just as a timetable. Therefore, in this paper, we suggest the process of measuring the working hours by MODAPTS which includes the working field-s accurate information. In addition, we adduce the estimation method of accuracy assembly cost with the real information. This research could be useful for designers that can estimate the assembly cost more accurately, and also effective for the companies that which are concerned to reduce the product cost.
Abstract: this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.
Abstract: Estimating the lifetime distribution of computer networks in which nodes and links exist in time and are bound for failure is very useful in various applications. This problem is known to be NP-hard. In this paper we present efficient combinatorial approaches to Monte Carlo estimation of network lifetime distribution. We also present some simulation results.
Abstract: Skin color based tracking techniques often assume a
static skin color model obtained either from an offline set of library
images or the first few frames of a video stream. These models
can show a weak performance in presence of changing lighting or
imaging conditions. We propose an adaptive skin color model based
on the Gaussian mixture model to handle the changing conditions.
Initial estimation of the number and weights of skin color clusters
are obtained using a modified form of the general Expectation
maximization algorithm, The model adapts to changes in imaging
conditions and refines the model parameters dynamically using spatial
and temporal constraints. Experimental results show that the method
can be used in effectively tracking of hand and face regions.
Abstract: The zero truncated model is usually used in modeling
count data without zero. It is the opposite of zero inflated model.
Zero truncated Poisson and zero truncated negative binomial models
are discussed and used by some researchers in analyzing the
abundance of rare species and hospital stay. Zero truncated models
are used as the base in developing hurdle models. In this study, we
developed a new model, the zero truncated strict arcsine model,
which can be used as an alternative model in modeling count data
without zero and with extra variation. Two simulated and one real
life data sets are used and fitted into this developed model. The
results show that the model provides a good fit to the data. Maximum
likelihood estimation method is used in estimating the parameters.
Abstract: ELS is an important ground based hardware in the
loop simulator used for aerodynamics torque loading experiments
of the actuators under test. This work focuses on improvement of the
transient response of torque controller with parameters uncertainty
of Electrical Load Simulator (ELS).The parameters of load simulator
are estimated online and the model is updated, eliminating the model
error and improving the steady state torque tracking response of
torque controller. To improve the Transient control performance the
gain of robust term of SMC is updated online using fuzzy logic
system based on the amount of uncertainty in parameters of load
simulator. The states of load simulator which cannot be measured
directly are estimated using luenberger observer with update of new
estimated parameters. The stability of the control scheme is verified
using Lyapunov theorem. The validity of proposed control scheme is
verified using simulations.
Abstract: The computer modeling is carried out for parameter of
sensitivity of optoelectronic chemical and biosensors, using
phenomena of surface plasmon resonance (SPR). The physical model
of SPR-sensor-s is described with (or without) of modifications of
sensitive gold film surface by a dielectric layer. The variants of
increasing of sensitivity for SPR-biosensors, constructed on the
principle gold – dielectric – biomolecular layer are considered. Two
methods of mathematical treatment of SPR-curve are compared –
traditional, with estimation of sensor-s response as shift of the SPRcurve
minimum and proposed, for system with dielectric layer, using
calculating of the derivative in the point of SPR-curve half-width.
Abstract: Noise has adverse effect on human health and
comfort. Noise not only cause hearing impairment, but it also acts as
a causal factor for stress and raising systolic pressure. Additionally it
can be a causal factor in work accidents, both by marking hazards
and warning signals and by impeding concentration. Industry
workers also suffer psychological and physical stress as well as
hearing loss due to industrial noise. This paper proposes an approach
to enable engineers to point out quantitatively the noisiest source for
modification, while multiple machines are operating simultaneously.
The model with the point source and spherical radiation in a free field
was adopted to formulate the problem. The procedure works very
well in ideal cases (point source and free field). However, most of the
industrial noise problems are complicated by the fact that the noise is
confined in a room. Reflections from the walls, floor, ceiling, and
equipment in a room create a reverberant sound field that alters the
sound wave characteristics from those for the free field. So the model
was validated for relatively low absorption room at NIT Kurukshetra
Central Workshop. The results of validation pointed out that the
estimated sound power of noise sources under simultaneous
conditions were on lower side, within the error limits 3.56 - 6.35 %.
Thus suggesting the use of this methodology for practical
implementation in industry. To demonstrate the application of the
above analytical procedure for estimating the sound power of noise
sources under simultaneous operating conditions, a manufacturing
facility (Railway Workshop at Yamunanagar, India) having five
sound sources (machines) on its workshop floor is considered in this
study. The findings of the case study had identified the two most
effective candidates (noise sources) for noise control in the Railway
Workshop Yamunanagar, India. The study suggests that the
modification in the design and/or replacement of these two identified
noisiest sources (machine) would be necessary so as to achieve an
effective reduction in noise levels. Further, the estimated data allows
engineers to better understand the noise situations of the workplace
and to revise the map when changes occur in noise level due to a
workplace re-layout.
Abstract: This paper discusses a design of nonlinear observer by
a formal linearization method using an application of Chebyshev Interpolation
in order to facilitate processes for synthesizing a nonlinear
observer and to improve the precision of linearization.
A dynamic nonlinear system is linearized with respect to a linearization
function, and a measurement equation is transformed into
an augmented linear one by the formal linearization method which is
based on Chebyshev interpolation. To the linearized system, a linear
estimation theory is applied and a nonlinear observer is derived. To
show effectiveness of the observer design, numerical experiments
are illustrated and they indicate that the design shows remarkable
performances for nonlinear systems.
Abstract: Panoramic view generation has always offered
novel and distinct challenges in the field of image processing.
Panoramic view generation is nothing but construction of bigger
view mosaic image from set of partial images of the desired view.
The paper presents a solution to one of the problems of image
seascape formation where some of the partial images are color and
others are grayscale. The simplest solution could be to convert all
image parts into grayscale images and fusing them to get grayscale
image panorama. But in the multihued world, obtaining the colored
seascape will always be preferred. This could be achieved by picking
colors from the color parts and squirting them in grayscale parts of
the seascape. So firstly the grayscale image parts should be colored
with help of color image parts and then these parts should be fused to
construct the seascape image.
The problem of coloring grayscale images has no exact solution.
In the proposed technique of panoramic view generation, the job of
transferring color traits from reference color image to grayscale
image is done by palette based method. In this technique, the color
palette is prepared using pixel windows of some degrees taken from
color image parts. Then the grayscale image part is divided into pixel
windows with same degrees. For every window of grayscale image
part the palette is searched and equivalent color values are found,
which could be used to color grayscale window. For palette
preparation we have used RGB color space and Kekre-s LUV color
space. Kekre-s LUV color space gives better quality of coloring. The
searching time through color palette is improved over the exhaustive
search using Kekre-s fast search technique.
After coloring the grayscale image pieces the next job is fusion of
all these pieces to obtain panoramic view. For similarity estimation
between partial images correlation coefficient is used.
Abstract: An effort estimation model is needed for softwareintensive
projects that consist of hardware, embedded software or
some combination of the two, as well as high level software
solutions. This paper first focuses on functional decomposition
techniques to measure functional complexity of a computer system
and investigates its impact on system development effort. Later, it
examines effects of technical difficulty and design team capability
factors in order to construct the best effort estimation model. With
using traditional regression analysis technique, the study develops a
system development effort estimation model which takes functional
complexity, technical difficulty and design team capability factors as
input parameters. Finally, the assumptions of the model are tested.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: Using a texture database, a statistical estimation of
spring-back was conducted in this study on the basis of statistical
analysis. Both spring-back in bending deformation and experimental
data related to the crystal orientation show significant dispersion.
Therefore, a probabilistic statistical approach was established for the
proper quantification of these values. Correlation was examined
among the parameters F(x) of spring-back, F(x) of the buildup fraction
to three orientations after 92° bending, and F(x) at an as-received part
on the basis of the three-parameter Weibull distribution. Consequent
spring-back estimation using a texture database yielded excellent
estimates compared with experimental values.