Abstract: In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Abstract: This paper presents an improvement method of
the multiple pitch estimation algorithm using comb filters.
Conventionally the pitch was estimated by using parallel
-connected comb filters method (PCF). However, PCF has
problems which often fail in the pitch estimation when there is
the fundamental frequency of higher tone near harmonics of
lower tone. Therefore the estimation is assigned to a wrong
note when shared frequencies happen. This issue often occurs
in estimating octave 3 or more. Proposed method, for solving
the problem, estimates the pitch with every harmonic instead of
every octave. As a result, our method reaches the accuracy of
more than 80%.
Abstract: The demand for new telecommunication services requiring higher capacities, data rates and different operating modes have motivated the development of new generation multi-standard wireless transceivers. A multi-standard design often involves extensive system level analysis and architectural partitioning, typically requiring extensive calculations. In this research, a decimation filter design tool for wireless communication standards consisting of GSM, WCDMA, WLANa, WLANb, WLANg and WiMAX is developed in MATLAB® using GUIDE environment for visual analysis. The user can select a required wireless communication standard, and obtain the corresponding multistage decimation filter implementation using this toolbox. The toolbox helps the user or design engineer to perform a quick design and analysis of decimation filter for multiple standards without doing extensive calculation of the underlying methods.
Abstract: In this paper, a fractional-order FIR differentiator
design method using the differential evolution (DE) algorithm is
presented. In the proposed method, the FIR digital filter is designed to
meet the frequency response of a desired fractal-order differentiator,
which is evaluated in the frequency domain. To verify the design
performance, another design method considered in the time-domain is
also provided. Simulation results reveal the efficiency of the proposed
method.
Abstract: In this paper, the performance of two adaptive
observers applied to interconnected systems is studied. The
nonlinearity of systems can be written in a fractional form. The first
adaptive observer is an adaptive sliding mode observer for a Lipchitz
nonlinear system and the second one is an adaptive sliding mode
observer having a filtered error as a sliding surface. After comparing
their performances throughout the inverted pendulum mounted on a
car system, it was shown that the second one is more robust to
estimate the state.
Abstract: The mobile systems are powered by batteries.
Reducing the system power consumption is a key to increase its
autonomy. It is known that mostly the systems are dealing with time
varying signals. Thus, we aim to achieve power efficiency by smartly
adapting the system processing activity in accordance with the input
signal local characteristics. It is done by completely rethinking the
processing chain, by adopting signal driven sampling and processing.
In this context, a signal driven filtering technique, based on the level
crossing sampling is devised. It adapts the sampling frequency and
the filter order by analysing the input signal local variations. Thus, it
correlates the processing activity with the signal variations. It leads
towards a drastic computational gain of the proposed technique
compared to the classical one.
Abstract: In this research, a biofiltration process to remove
ammonia gas from gas stream using agricultural residue biofilter
medias is studied. The experiments were conducted in laboratoryscale
biofilter. The biofilter medias were a mixture of manure
fertilizer and bagasse at various ratios i.e., 1:3, 1:5 and 1:7. The
experiments were performed for a period of 40 days. The empty bed
retention time (EBRT) is 78s. The moisture content of biofilter media
was maintained at 45-60% using water. The results showed that the
agricultural residues (manure fertilizer and bagasse) are suitable as
biofilter media for ammonia gas removal in biofiltration process.
The maximum efficiency of ammonia gas removal is observed
from the 1:5 of manure fertilizer: bagasse ratio at 89.93%. The
biofiltration is more effective at low ammonia gas concentration. In
addition, the mixture ratio of biofilter media is not a significant factor
in biofiltration operation while the most significant factor for
biofiltration operation is the inlet ammonia gas concentration.
Abstract: This article presents a current-mode universal biquadratic filter. The proposed circuit can apparently provide standard functions of the biquad filter: low-pass, high-pass, bandpass, band-reject and all-pass functions. The circuit uses 4 current controlled transconductance amplifiers (CCTAs) and 2 grounded capacitors. In addition, the pole frequency and quality factor can be adjusted by electronic method by adjusting the bias currents of the CCTA. The proposed circuit uses only grounded capacitors without additional external resistors, the proposed circuit is considerably appropriate to further developing into an integrated circuit. The results of PSPICE simulation program are corresponding to the theoretical analysis.
Abstract: Legionella pneumophila is involved in more than 95%
cases of severe atypical pneumonia. Infection is mainly by
inhalation the indoor aerosols through the water-coolant systems.
Because some Legionella strains may be viable but not culturable,
therefore, Taq polymerase, DNA amplification and semi-nested-PCR
were carried out to detect Legionella-specific 16S-rDNA sequence.
For this purpose, 1.5 litter of water samples from 77 water-coolant
system were collected from four different hospitals, two nursing
homes and one student hostel in Kerman city of Iran, each in a brand
new plastic bottle during summer season of 2006 (from April to
August). The samples were filtered in the sterile condition through
the Millipore Membrane Filter. DNA was extracted from membrane
and used for PCR to detect Legionella spp. The PCR product was
then subjected to semi-nested PCR for detection of L. pneumophila.
Out of 77 water samples that were tested by PCR, 30 (39%) were
positive for most species of Legionella. However, L. pneumophila
was detected from 14 (18.2%) water samples by semi-nested PCR.
From the above results it can be concluded that water coolant
systems of different hospitals and nursing homes in Kerman city of
Iran are highly contaminated with L. pneumophila spp. and pose
serious concern. So, we recommend avoiding such type of coolant
system in the hospitals and nursing homes.
Abstract: This paper presents an effective traffic lights detection
method at the night-time. First, candidate blobs of traffic lights are
extracted from RGB color image. Input image is represented on the
dominant color domain by using color transform proposed by Ruta,
then red and green color dominant regions are selected as candidates.
After candidate blob selection, we carry out shape filter for noise
reduction using information of blobs such as length, area, area of
boundary box, etc. A multi-class classifier based on SVM (Support
Vector Machine) applies into the candidates. Three kinds of features
are used. We use basic features such as blob width, height, center
coordinate, area, area of blob. Bright based stochastic features are also
used. In particular, geometric based moment-s values between
candidate region and adjacent region are proposed and used to improve
the detection performance. The proposed system is implemented on
Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the
urban and rural road videos. Through the test, we show that the
proposed method using PF, BMF, and GMF reaches up to 93 % of
detection rate with computation time of in average 15 ms/frame.
Abstract: In recent years Operational Transconductance Amplifier based high frequency integrated circuits, filters and systems have been widely investigated. The usefulness of OTAs over conventional OP-Amps in the design of both first order and second order active filters are well documented. This paper discusses some of the tunability issues using the Matlab/Simulink® software which are previously unreported for any commercial OTA. Using the simulation results two first order voltage controlled all pass filters with phase tuning capability are proposed.
Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.
Abstract: In this paper, we proposed the direct method for converting
Finite-Impulse Response (FIR) filter with low nonzero tap
into Infinite-Impulse Response (IIR) filter using the pre-determined
table. The prony method is used by ghost cancellator which is IIR
approximation to FIR filter which is better performance than IIR and
have much larger calculation difference. The direct method for many
ghost combination with low nonzero tap of NTSC(National Television
System Committee) TV signal in Korea is described. The proposed
method is illustrated with an example.
Abstract: We present a discussion of three adaptive filtering
algorithms well known for their one-step termination property, in
terms of their relationship with the minimal residual method. These
algorithms are the normalized least mean square (NLMS), Affine
Projection algorithm (APA) and the recursive least squares algorithm
(RLS). The NLMS is shown to be a result of the orthogonality
condition imposed on the instantaneous approximation of the Wiener
equation, while APA and RLS algorithm result from orthogonality
condition in multi-dimensional minimal residual formulation. Further
analysis of the minimal residual formulation for the RLS leads to
a triangular system which also possesses the one-step termination
property (in exact arithmetic)
Abstract: Sensor networks are often deployed in unattended
environments, thus leaving these networks vulnerable to false data
injection attacks in which an adversary injects forged reports into the
network through compromised nodes, with the goal of deceiving the
base station or depleting the resources of forwarding nodes. Several
research solutions have been recently proposed to detect and drop such
forged reports during the forwarding process. Each design can provide
the equivalent resilience in terms of node compromising. However,
their energy consumption characteristics differ from each other. Thus,
employing only a single filtering scheme for a network is not a
recommendable strategy in terms of energy saving. It's very important
the threshold determination for message authentication to identify. We
propose the recursive contract net protocols which less energy level of
terminal node in wireless sensor network.
Abstract: This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.
Abstract: In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) in the discrete wavelet transforms is proposed. It is robust against watermarking attacks, which are commonly employed in literature. In addition, the watermarked image quality is also considered. We employ GA for the optimal localization and intensity of watermark. The watermark detection process can be performed without using the original audio signal. The experimental results demonstrate that watermark is inaudible and robust to many digital signal processing, such as cropping, low pass filter, additive noise.
Abstract: Extended Kalman Filter (EKF) is probably the most
widely used estimation algorithm for nonlinear systems. However,
not only it has difficulties arising from linearization but also many
times it becomes numerically unstable because of computer round off
errors that occur in the process of its implementation. To overcome
linearization limitations, the unscented transformation (UT) was
developed as a method to propagate mean and covariance
information through nonlinear transformations. Kalman filter that
uses UT for calculation of the first two statistical moments is called
Unscented Kalman Filter (UKF). Square-root form of UKF (SRUKF)
developed by Rudolph van der Merwe and Eric Wan to
achieve numerical stability and guarantee positive semi-definiteness
of the Kalman filter covariances. This paper develops another
implementation of SR-UKF for sequential update measurement
equation, and also derives a new UD covariance factorization filter
for the implementation of UKF. This filter is equivalent to UKF but
is computationally more efficient.
Abstract: In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.