Abstract: The task of face recognition has been actively
researched in recent years. This paper provides an up-to-date review of major human face recognition research. We first present an
overview of face recognition and its applications. Then, a literature review of the most recent face recognition techniques is presented.
Description and limitations of face databases which are used to test
the performance of these face recognition algorithms are given. A
brief summary of the face recognition vendor test (FRVT) 2002, a
large scale evaluation of automatic face recognition technology, and
its conclusions are also given. Finally, we give a summary of the research results.
Abstract: This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Abstract: The technological concepts such as wireless hospital
and portable cardiac telemetry system require the development of
physiological signal acquisition devices to be easily integrated into
the hospital database. In this paper we present the low cost, portable
wireless ECG acquisition hardware that transmits ECG signals to a
dedicated computer.The front end of the system obtains and
processes incoming signals, which are then transmitted via a
microcontroller and wireless Bluetooth module. A monitoring
purpose Bluetooth based end user application integrated with patient
database management module is developed for the computers. The
system will act as a continuous event recorder, which can be used to
follow up patients who have been resuscitatedfrom cardiac arrest,
ventricular tachycardia but also for diagnostic purposes for patients
with arrhythmia symptoms. In addition, cardiac information can be
saved into the patient-s database of the hospital.
Abstract: As more people from non-technical backgrounds
are becoming directly involved with large-scale ontology
development, the focal point of ontology research has shifted
from the more theoretical ontology issues to problems
associated with the actual use of ontologies in real-world,
large-scale collaborative applications. Recently the National
Science Foundation funded a large collaborative ontology
development project for which a new formal ontology model,
the Ontology Abstract Machine (OAM), was developed to
satisfy some unique functional and data representation
requirements. This paper introduces the OAM model and the
related algorithms that enable maintenance of an ontology that
supports node-based user access. The successful software
implementation of the OAM model and its subsequent
acceptance by a large research community proves its validity
and its real-world application value.
Abstract: Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.
Abstract: Maize and Indian mustard are significant crops in
semi-arid climate zones of India. Improved water management
requires precise scheduling of irrigation, which in turn requires an
accurate computation of daily crop evapotranspiration (ETc). Daily
crop evapotranspiration comes as a product of reference
evapotranspiration (ET0) and the growth stage specific crop
coefficients modified for daily variation. The first objective of
present study is to develop crop coefficients Kc for Maize and Indian
mustard. The estimated values of Kc for maize at the four crop
growth stages (initial, development, mid-season, and late season) are
0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc
values at the four growth stages are 0.3, 0.6, 1.12, and 0.35,
respectively. The second objective of the study is to compute daily
crop evapotranspiration from ET0 and crop coefficients. Average
daily ETc of maize varied from about 2.5 mm/d in the early growing
period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3
mm/d and it occurred 64 days after sowing at the reproductive growth
stage when leaf area index was 4.54. In the case of Indian mustard,
average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season
and achieves a peak value of 2.12 mm/d on 56 days after sowing.
Improved schedules of irrigation have been simulated based on daily
crop evapo-transpiration and field measured data. Simulation shows a
close match between modeled and field moisture status prevalent
during crop season.
Abstract: This paper presents a multi-objective order allocation
planning problem with the consideration of various real-world
production features. A novel hybrid intelligent optimization model,
integrating a multi-objective memetic optimization process, a Monte
Carlo simulation technique and a heuristic pruning technique, is
proposed to handle this problem. Experiments based on industrial data
are conducted to validate the proposed model. Results show that (1)
the proposed model can effectively solve the investigated problem by
providing effective production decision-making solutions, which
outperformsan NSGA-II-based optimization process and an industrial
method.
Abstract: In a liberalized electricity market, it is not surprising
that different customers require different power quality (PQ) levels at
different price. Power quality related to several power disturbances is
described by many parameters, so how to define a comprehensive
hierarchy evaluation system of power quality (PQCHES) has become
a concerned issue. In this paper, based on four electromagnetic
compatibility (EMC) levels, the numerical range of each power
disturbance is divided into five grades (Grade I –Grade V), and the
“barrel principle" of power quality is used for the assessment of
overall PQ performance with only one grade indicator. A case study
based on actual monitored data of PQ shows that the site PQ grade
indicates the electromagnetic environment level and also expresses the
characteristics of loads served by the site.
The shortest plank principle of PQ barrel is an incentive
mechanism, which can combine with the rewards/penalty mechanism
(RPM) of consumed energy “on quality demand", to stimulate utilities
to improve the overall PQ level and also stimulate end-user more
“smart" under the infrastructure of future SmartGrid..
Abstract: In this paper an approaches for increasing the
effectiveness of error detection in computer network channels with
Pulse-Amplitude Modulation (PAM) has been proposed. Proposed
approaches are based on consideration of special feature of errors,
which are appearances in line with PAM. The first approach consists
of CRC modification specifically for line with PAM. The second
approach is base of weighted checksums using. The way for
checksum components coding has been developed. It has been shown
that proposed checksum modification ensure superior digital data
control transformation reliability for channels with PAM in compare
to CRC.
Abstract: Chronic hepatitis B can evolve to cirrhosis and liver
cancer. Interferon is the only effective treatment, for carefully selected
patients, but it is very expensive. Some of the selection criteria are
based on liver biopsy, an invasive, costly and painful medical procedure.
Therefore, developing efficient non-invasive selection systems,
could be in the patients benefit and also save money. We investigated
the possibility to create intelligent systems to assist the Interferon
therapeutical decision, mainly by predicting with acceptable accuracy
the results of the biopsy. We used a knowledge discovery in integrated
medical data - imaging, clinical, and laboratory data. The resulted
intelligent systems, tested on 500 patients with chronic hepatitis
B, based on C5.0 decision trees and boosting, predict with 100%
accuracy the results of the liver biopsy. Also, by integrating the other
patients selection criteria, they offer a non-invasive support for the
correct Interferon therapeutic decision. To our best knowledge, these
decision systems outperformed all similar systems published in the
literature, and offer a realistic opportunity to replace liver biopsy in
this medical context.
Abstract: This paper proposes an innovative methodology for
Acceptance Sampling by Variables, which is a particular category of
Statistical Quality Control dealing with the assurance of products
quality. Our contribution lies in the exploitation of machine learning
techniques to address the complexity and remedy the drawbacks of
existing approaches. More specifically, the proposed methodology
exploits Artificial Neural Networks (ANNs) to aid decision making
about the acceptance or rejection of an inspected sample. For any
type of inspection, ANNs are trained by data from corresponding
tables of a standard-s sampling plan schemes. Once trained, ANNs
can give closed-form solutions for any acceptance quality level and
sample size, thus leading to an automation of the reading of the
sampling plan tables, without any need of compromise with the
values of the specific standard chosen each time. The proposed
methodology provides enough flexibility to quality control engineers
during the inspection of their samples, allowing the consideration of
specific needs, while it also reduces the time and the cost required for
these inspections. Its applicability and advantages are demonstrated
through two numerical examples.
Abstract: We study the performance of compressed beamforming
weights feedback technique in generalized triangular decomposition
(GTD) based MIMO system. GTD is a beamforming technique that
enjoys QoS flexibility. The technique, however, will perform at its
optimum only when the full knowledge of channel state information
(CSI) is available at the transmitter. This would be impossible in
the real system, where there are channel estimation error and limited
feedback. We suggest a way to implement the quantized beamforming
weights feedback, which can significantly reduce the feedback data,
on GTD-based MIMO system and investigate the performance of
the system. Interestingly, we found that compressed beamforming
weights feedback does not degrade the BER performance of the
system at low input power, while the channel estimation error
and quantization do. For comparison, GTD is more sensitive to
compression and quantization, while SVD is more sensitive to the
channel estimation error. We also explore the performance of GTDbased
MU-MIMO system, and find that the BER performance starts
to degrade largely at around -20 dB channel estimation error.
Abstract: This paper investigates the optimization problem of
multi-product aggregate production planning (APP) with fuzzy data.
From a comprehensive viewpoint of conserving the fuzziness of input
information, this paper proposes a method that can completely
describe the membership function of the performance measure. The
idea is based on the well-known Zadeh-s extension principle which
plays an important role in fuzzy theory. In the proposed solution
procedure, a pair of mathematical programs parameterized by
possibility level a is formulated to calculate the bounds of the
optimal performance measure at a . Then the membership function of
the optimal performance measure is constructed by enumerating
different values of a . Solutions obtained from the proposed method
contain more information, and can offer more chance to achieve the
feasible disaggregate plan. This is helpful to the decision-maker in
practical applications.
Abstract: In the previous multi-solid models,¤ò approach is
used for the calculation of fugacity in the liquid phase. For the first
time, in the proposed multi-solid thermodynamic model,γ approach
has been used for calculation of fugacity in the liquid mixture.
Therefore, some activity coefficient models have been studied that
the results show that the predictive Wilson model is more appropriate
than others. The results demonstrate γ approach using the predictive
Wilson model is in more agreement with experimental data than the
previous multi-solid models. Also, by this method, generates a new
approach for presenting stability analysis in phase equilibrium
calculations. Meanwhile, the run time in γ approach is less than the
previous methods used ¤ò approach. The results of the new model
present 0.75 AAD % (Average Absolute Deviation) from the
experimental data which is less than the results error of the previous
multi-solid models obviously.
Abstract: Biological reactions of individuals of a testing animal
to toxic substance are unique and can be used as an indication of the
existing of toxic substance. However, to distinguish such phenomenon
need a very complicate system and even more complicate to analyze
data in 3 dimensional. In this paper, a system to evaluate in vitro
biological activities to acute toxicity of stochastic self-affine
non-stationary signal of 3D goldfish swimming by using fractal
analysis is introduced. Regular digital camcorders are utilized by
proposed algorithm 3DCCPC to effectively capture and construct 3D
movements of the fish. A Critical Exponent Method (CEM) has been
adopted as a fractal estimator. The hypothesis was that the swimming
of goldfish to acute toxic would show the fractal property which
related to the toxic concentration. The experimental results supported
the hypothesis by showing that the swimming of goldfish under the
different toxic concentration has fractal properties. It also shows that
the fractal dimension of the swimming related to the pH value of FD Ôëê
0.26pH + 0.05. With the proposed system, the fish is allowed to swim
freely in all direction to react to the toxic. In addition, the trajectories
are precisely evaluated by fractal analysis with critical exponent
method and hence the results exhibit with much higher degree of
confidence.
Abstract: To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
correlated.
Abstract: Higher productivity and less cost in the ship
manufacturing process are required to maintain the international
competitiveness of morden manufacturing industries. In shipbuilding,
however, the Engineering To Order (ETO) production method and
production process is very difficult. Thus, designs change frequently.
In accordance with production, planning should be set up according
to scene changes. Therefore, fixed production planning is very
difficult. Thus, a scheduler must first make sketchy plans, then
change the plans based on the work progress and modifications.
Thus, data sharing in a shipbuilding block assembly shop is very
important. In this paper, we proposed to scheduling method
applicable to the shipbuilding industry and decision making support
system through web based visualization system.
Abstract: In this paper a novel scheme for watermarking digital
audio during its compression to MPEG-1 Layer III format is
proposed. For this purpose we slightly modify some of the selected
MDCT coefficients, which are used during MPEG audio
compression procedure. Due to the possibility of modifying different
MDCT coefficients, there will be different choices for embedding the
watermark into audio data, considering robustness and transparency
factors. Our proposed method uses a genetic algorithm to select the
best coefficients to embed the watermark. This genetic selection is
done according to the parameters that are extracted from the
perceptual content of the audio to optimize the robustness and
transparency of the watermark. On the other hand the watermark
security is increased due to the random nature of the genetic
selection. The information of the selected MDCT coefficients that
carry the watermark bits, are saves in a database for future extraction
of the watermark. The proposed method is suitable for online MP3
stores to pursue illegal copies of musical artworks. Experimental
results show that the detection ratio of the watermarks at the bitrate
of 128kbps remains above 90% while the inaudibility of the
watermark is preserved.
Abstract: This paper proposes a novel game theoretical
technique to address the problem of data object replication in largescale
distributed computing systems. The proposed technique draws
inspiration from computational economic theory and employs the
extended Vickrey auction. Specifically, players in a non-cooperative
environment compete for server-side scarce memory space to
replicate data objects so as to minimize the total network object
transfer cost, while maintaining object concurrency. Optimization of
such a cost in turn leads to load balancing, fault-tolerance and
reduced user access time. The method is experimentally evaluated
against four well-known techniques from the literature: branch and
bound, greedy, bin-packing and genetic algorithms. The experimental
results reveal that the proposed approach outperforms the four
techniques in both the execution time and solution quality.
Abstract: In hydrocyclones, the particle separation efficiency is
limited by the suspended fine particles, which are discharged with the
coarse product in the underflow. It is well known that injecting water
in the conical part of the cyclone reduces the fine particle fraction in
the underflow. This paper presents a mathematical model that
simulates the water injection in the conical component. The model
accounts for the fluid flow and the particle motion. Particle
interaction, due to hindered settling caused by increased density and
viscosity of the suspension, and fine particle entrainment by settling
coarse particles are included in the model. Water injection in the
conical part of the hydrocyclone is performed to reduce fine particle
discharge in the underflow. The model demonstrates the impact of
the injection rate, injection velocity, and injection location on the
shape of the partition curve. The simulations are compared with
experimental data of a 50-mm cyclone.