Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.
Abstract: The measurement of anesthetic depth is necessary in
anesthesiology. NN10 is very simple method among the RR intervals
analysis methods. NN10 parameter means the numbers of above the 10
ms intervals of the normal to normal RR intervals.
Bispectrum analysis is defined as 2D FFT. EEG signal reflected the
non-linear peristalsis phenomena according to the change brain
function. After analyzing the bispectrum of the 2 dimension, the most
significant power spectrum density peaks appeared abundantly at the
specific area in awakening and anesthesia state. These points are
utilized to create the new index since many peaks appeared at the
specific area in the frequency coordinate. The measured range of an
index was 0-100. An index is 20-50 at an anesthesia, while the index is
90-60 at the awake.
In this paper, the relation between NN10 parameter using ECG and
bisepctrum index using EEG is observed to estimate the depth of
anesthesia during anesthesia and then we estimated the utility of the
anesthetic.
Abstract: techniques are examined to overcome the
performance degradation caused by the channel dispersion using
slow frequency hopping (SFH) with dynamic frequency hopping
(DFH) pattern adaptation. In DFH systems, the frequency slots are
selected by continuous quality monitoring of all frequencies available
in a system and modification of hopping patterns for each individual
link based on replacing slots which its signal to interference ratio
(SIR) measurement is below a required threshold. Simulation results
will show the improvements in BER obtained by DFH in comparison
with matched frequency hopping (MFH), random frequency hopping
(RFH) and multi-carrier code division multiple access (MC-CDMA)
in multipath slowly fading dispersive channels using a generalized
bandpass two-path transfer function model, and will show the
improvement obtained according to the threshold selection.
Abstract: This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.
Abstract: In this work we evaluate the possibility of predicting
the emotional state of a person based on the EEG. We investigate
the problem of classifying valence from EEG signals during
the presentation of affective pictures, utilizing the "frontal EEG
asymmetry" phenomenon. To distinguish positive and negative
emotions, we applied the Common Spatial Patterns algorithm.
In contrast to our expectations, the affective pictures did not
reliably elicit changes in frontal asymmetry. The classifying task
thereby becomes very hard as reflected by the poor classifier
performance. We suspect that the masking of the source of the
brain activity related to emotions, coming mostly from deeper
structures in the brain, and the insufficient emotional engagement
are among main reasons why it is difficult to predict the emotional
state of a person.
Abstract: Characterization of radio communication signals aims
at automatic recognition of different characteristics of radio signals in
order to detect their modulation type, the central frequency, and the
level. Our purpose is to apply techniques used in image processing in
order to extract pertinent characteristics. To the single analysis, we
add several rules for checking the consistency of hypotheses using
fuzzy logic. This allows taking into account ambiguity and
uncertainty that may remain after the extraction of individual
characteristics. The aim is to improve the process of radio
communications characterization.
Abstract: In real-field applications, the correct determination of voice segments highly improves the overall system accuracy and minimises the total computation time. This paper presents reliable measures of speech compression by detcting the end points of the speech signals prior to compressing them. The two different compession schemes used are the Global threshold and the Level- Dependent threshold techniques. The performance of the proposed method is tested wirh the Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error parameter measures.
Abstract: Histogram equalization is often used in image enhancement, but it can be also used in auto exposure. However, conventional histogram equalization does not work well when many pixels are concentrated in a narrow luminance range.This paper proposes an auto exposure method based on 2-way histogram equalization. Two cumulative distribution functions are used, where one is from dark to bright and the other is from bright to dark. In this paper, the proposed auto exposure method is also designed and implemented for image signal processors with full-HD images.
Abstract: Blood pulse is an important human physiological signal commonly used for the understanding of the individual physical health. Current methods of non-invasive blood pulse sensing require direct contact or access to the human skin. As such, the performances of these devices tend to vary with time and are subjective to human body fluids (e.g. blood, perspiration and skin-oil) and environmental contaminants (e.g. mud, water, etc). This paper proposes a simulation model for the novel method of non-invasive acquisition of blood pulse using the disturbance created by blood flowing through a localized magnetic field. The simulation model geometry represents a blood vessel, a permanent magnet, a magnetic sensor, surrounding tissues and air in 2-dimensional. In this model, the velocity and pressure fields in the blood stream are described based on Navier-Stroke equations and the walls of the blood vessel are assumed to have no-slip condition. The blood assumes a parabolic profile considering a laminar flow for blood in major artery near the skin. And the inlet velocity follows a sinusoidal equation. This will allow the computational software to compute the interactions between the magnetic vector potential generated by the permanent magnet and the magnetic nanoparticles in the blood. These interactions are simulated based on Maxwell equations at the location where the magnetic sensor is placed. The simulated magnetic field at the sensor location is found to assume similar sinusoidal waveform characteristics as the inlet velocity of the blood. The amplitude of the simulated waveforms at the sensor location are compared with physical measurements on human subjects and found to be highly correlated.
Abstract: An optical fiber Fabry-Perot interferometer (FFPI) is
proposed and demonstrated for dynamic measurements in a
mechanical vibrating target. A polishing metal with a low reflectance
value adhered to a mechanical vibrator was excited via a function
generator at various excitation frequencies. Output interference
fringes were generated by modulating the reference and sensing
signal at the output arm. A fringe-counting technique was used for
interpreting the displacement information on the dedicated computer.
The fiber interferometer has been found the capability of the
displacement measurements of 1.28 μm – 96.01 μm. A commercial
displacement sensor was employed as a reference sensor for
investigating the measurement errors from the fiber sensor. A
maximum percentage measurement error of approximately 1.59 %
was obtained.
Abstract: In this paper we compare the response of linear and
nonlinear neural network-based prediction schemes in prediction of
received Signal-to-Interference Power Ratio (SIR) in Direct
Sequence Code Division Multiple Access (DS/CDMA) systems. The
nonlinear predictor is Multilayer Perceptron MLP and the linear
predictor is an Adaptive Linear (Adaline) predictor. We solve the
problem of complexity by using the Minimum Mean Squared Error
(MMSE) principle to select the optimal predictors. The optimized
Adaline predictor is compared to optimized MLP by employing
noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an
urban environment. The results show that the Adaline predictor can
estimates SIR with the same error as MLP when the user has the
velocity of 5 km/h and 60 km/h but by increasing the velocity up-to
120 km/h the mean squared error of MLP is two times more than
Adaline predictor. This makes the Adaline predictor (with lower
complexity) more suitable than MLP for closed-loop power control
where efficient and accurate identification of the time-varying
inverse dynamics of the multi path fading channel is required.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.
Abstract: In this paper, we propose a novel frequency offset
estimation scheme for orthogonal frequency division multiplexing
(OFDM) systems. By correlating the OFDM signals within the coherence
phase bandwidth and employing a threshold in the frequency
offset estimation process, the proposed scheme is not only robust to
the timing offset but also has a reduced complexity compared with
that of the conventional scheme. Moreover, a timing offset estimation
scheme is also proposed as the next stage of the proposed frequency
offset estimation. Numerical results show that the proposed scheme
can estimate frequency offset with lower computational complexity
and does not require additional memory while maintaining the same
level of estimation performance.
Abstract: In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.
Abstract: The more recent satellite projects/programs makes
extensive usage of real – time embedded systems. 16 bit processors
which meet the Mil-Std-1750 standard architecture have been used in
on-board systems. Most of the Space Applications have been written
in ADA. From a futuristic point of view, 32 bit/ 64 bit processors are
needed in the area of spacecraft computing and therefore an effort is
desirable in the study and survey of 64 bit architectures for space
applications. This will also result in significant technology
development in terms of VLSI and software tools for ADA (as the
legacy code is in ADA).
There are several basic requirements for a special processor for
this purpose. They include Radiation Hardened (RadHard) devices,
very low power dissipation, compatibility with existing operational
systems, scalable architectures for higher computational needs,
reliability, higher memory and I/O bandwidth, predictability, realtime
operating system and manufacturability of such processors.
Further on, these may include selection of FPGA devices, selection
of EDA tool chains, design flow, partitioning of the design, pin
count, performance evaluation, timing analysis etc.
This project deals with a brief study of 32 and 64 bit processors
readily available in the market and designing/ fabricating a 64 bit
RISC processor named RISC MicroProcessor with added
functionalities of an extended double precision floating point unit
and a 32 bit signal processing unit acting as co-processors. In this
paper, we emphasize the ease and importance of using Open Core
(OpenSparc T1 Verilog RTL) and Open “Source" EDA tools such as
Icarus to develop FPGA based prototypes quickly. Commercial tools
such as Xilinx ISE for Synthesis are also used when appropriate.
Abstract: Crosstalk is the major limiting issue in very high bit-rate digital subscriber line (VDSL) systems in terms of bit-rate or service coverage. At the central office side, joint signal processing accompanied by appropriate power allocation enables complex multiuser processors to provide near capacity rates. Unfortunately complexity grows with the square of the number of lines within a binder, so by taking into account that there are only a few dominant crosstalkers who contribute to main part of crosstalk power, the canceller structure can be simplified which resulted in a much lower run-time complexity. In this paper, a multiuser power control scheme, namely iterative waterfilling, is combined with previously proposed partial crosstalk cancellation approaches to demonstrate the best ever achieved performance which is verified by simulation results.
Abstract: An improved processing description to be employed in biosonar signal processing in a cochlea model is proposed and examined. It is compared to conventional models using a modified discrimination analysis and both are tested. Their performances are evaluated with echo data captured from natural targets (trees).Results indicate that the phase characteristics of low-pass filters employed in the echo processing have a significant effect on class separability for this data.
Abstract: Application of projective geometry to the theory of two-ports and cascade circuits with a load change is considered. The equations linking the input and output of a two-port are interpreted as projective transformations which have the invariant as a cross-ratio of four points. This invariant has place for all regime parameters in all parts of a cascade circuit. This approach allows justifying the definition of a regime and its change, to calculate a circuit without explicitly finding the aparameters, to transmit accurately an analogue signal through the unstable two-port.