Abstract: On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.
Abstract: Realistic 3D face model is more precise in representing
pose, illumination, and expression of face than 2D face model so that it
can be utilized usefully in various applications such as face recognition,
games, avatars, animations, and etc.
In this paper, we propose a 3D face modeling method based on 3D
dense morphable shape model. The proposed 3D modeling method
first constructs a 3D dense morphable shape model from 3D face scan
data obtained using a 3D scanner. Next, the proposed method extracts
and matches facial landmarks from 2D image sequence containing a
face to be modeled, and then reconstructs 3D vertices coordinates of
the landmarks using a factorization-based SfM technique. Then, the
proposed method obtains a 3D dense shape model of the face to be
modeled by fitting the constructed 3D dense morphable shape model
into the reconstructed 3D vertices. Also, the proposed method makes a
cylindrical texture map using 2D face image sequence. Finally, the
proposed method generates a 3D face model by rendering the 3D dense
face shape model using the cylindrical texture map. Through building
processes of 3D face model by the proposed method, it is shown that
the proposed method is relatively easy, fast and precise.
Abstract: Electronic commerce is growing rapidly with on-line
sales already heading for hundreds of billion dollars per year. Due to
the huge amount of money transferred everyday, an increased
security level is required. In this work we present the architecture of
an intelligent speaker verification system, which is able to accurately
verify the registered users of an e-commerce service using only their
voices as an input. According to the proposed architecture, a
transaction-based e-commerce application should be complemented
by a biometric server where customer-s unique set of speech models
(voiceprint) is stored. The verification procedure requests from the
user to pronounce a personalized sequence of digits and after
capturing speech and extracting voice features at the client side are
sent back to the biometric server. The biometric server uses pattern
recognition to decide whether the received features match the stored
voiceprint of the customer who claims to be, and accordingly grants
verification. The proposed architecture can provide e-commerce
applications with a higher degree of certainty regarding the identity
of a customer, and prevent impostors to execute fraudulent
transactions.
Abstract: Plackett-Burman statistical screening of media
constituents and operational conditions for extracellular lipase
production from isolate Trichoderma viride has been carried out in
submerged fermentation. This statistical design is used in the early
stages of experimentation to screen out unimportant factors from a
large number of possible factors. This design involves screening of
up to 'n-1' variables in just 'n' number of experiments. Regression
coefficients and t-values were calculated by subjecting the
experimental data to statistical analysis using Minitab version 15.
The effects of nine process variables were studied in twelve
experimental trials. Maximum lipase activity of 7.83 μmol /ml /min
was obtained in the 6th trail. Pareto chart illustrates the order of
significance of the variables affecting the lipase production. The
present study concludes that the most significant variables affecting
lipase production were found to be palm oil, yeast extract, K2HPO4,
MgSO4 and CaCl2.
Abstract: Active research is underway on virtual touch screens
that complement the physical limitations of conventional touch
screens. This paper discusses a virtual touch screen that uses a
multi-layer perceptron to recognize and control three-dimensional
(3D) depth information from a time of flight (TOF) camera. This
system extracts an object-s area from the image input and compares it
with the trajectory of the object, which is learned in advance, to
recognize gestures. The system enables the maneuvering of content in
virtual space by utilizing human actions.
Abstract: In this paper, a new Genetic Algorithm (GA) based
methodology is proposed to optimize the Degree of Hybridization
(DOH) in a passenger parallel hybrid car. At first step, target
parameters for the vehicle are decided and then using ADvanced
VehIcle SimulatOR (ADVISOR) software, the variation pattern of
these target parameters, across the different DOHs, is extracted. At
the next step, a suitable cost function is defined and is optimized
using GA. In this paper, also a new technique has been proposed for
deciding the number of battery modules for each DOH, which leads
to a great improvement in the vehicle performance. The proposed
methodology is so simple, fast and at the same time, so efficient.
Abstract: In this paper methodology to exploit creeping wave
for body area network BAN communication reliability are described.
Creeping wave propagation effects are visualized & analyzed.
During this work Dipole, IA antennas various antennas were
redesigned using existing designs and their propagation
characteristics were verified for optimum performance when used on
BANs. These antennas were then applied on body shapes-including
rectangular, spherical and cylindrical so that all the effects of actual
human body can be taken nearly into account. Parametric simulation
scheme was devised so that on Body channel characterization can be
visualized at front, curved and back region. In the next phase
multiple inputs multiple output MIMO scheme was introduced where
virtual antennas were used in order to diminish the effects of
antennas on the propagation of waves. Results were, extracted and
analyzed at different heights. Finally based on comparative
measurement and analysis it was concluded that on body propagation
can be exploited to gain spatial diversity.
Abstract: In this study, we present an advanced detection
technique for mass type breast cancer based on texture information
of organs. The proposed method detects the cancer areas in three
stages. In the first stage, the midpoints of mass area are determined
based on AHE (Adaptive Histogram Equalization). In the second
stage, we set the threshold coefficient of homogeneity by using
MLE (Maximum Likelihood Estimation) to compute the uniformity
of texture. Finally, mass type cancer tissues are extracted from the
original image. As a result, it was observed that the proposed
method shows an improved detection performance on dense breast
tissues of Korean women compared with the existing methods. It is
expected that the proposed method may provide additional
diagnostic information for detection of mass-type breast cancer.
Abstract: Nigella sativa L. is an aromatic plant belonging to the
family Ranunculaceae. It has been used traditionally, especially in the
middle East and India, for the treatment of asthma, cough, bronchitis,
headache, rheumatism, fever, influenza and eczema. Several
biological activities have been reported in Nigella sativa seeds,
including antioxidant. In this context we tried to estimate the
antioxidant activity of various extracts prepared from Nigella sativa
seeds, methanolic extract (ME), chloroformic extract (CE), hexanic
extract (HE : fixed oil), ethyl acetate extract (EAE) water extract
(WE). The Folin-Ciocalteu assay showed that CE and EAE contained
high level of phenolic compounds 81.31 and 72.43μg GAE/mg of
extract respectively. Similarly, the CE and EAE exhibited the highest
DPPH radical scavenging activity, with IC50 values of 106.56μg/ml
and 121.62μg/ml respectively. In addition, CE and HE showed the
most scavenging activity against superoxide radical generated in the
PMS-NADH-NBT system with respective IC50 values of 361.86
μg/ml and 371.80 μg/ml, which is comparable to the activity of the
standard antioxidant BHT (344.59 μg/ml). Ferrous ion chelating
capacity assay showed that WE, EAE and ME are the most active
with 40.57, 39.70 and 22.02 mg EDTA-E/g of extract. The inhibition
of linoleic acid/ß-carotene coupled oxidation was estimated by ßcarotene
bleaching assay, this showed a highest relative antioxidant
activity with CE and EAE (69.82% of inhibition). The antioxidant
activities of the methanolic extract and the fixed oil are confirmed by
an in vivo assay in mice, the daily oral administration of methanolic
extract (500 and 800 mg/kg/day) and fixed oil (2 and 4 ml/kg/day)
during 21 days, resulted in a significant enhancement of the blood
total antioxidant capacity (measured by KRL test) and the plasmatic
antioxidant capacity towards DPPH radical.
Abstract: This paper considers a robust recovery of sparse frequencies
from partial phase-only measurements. With the proposed
method, sparse frequencies can be reconstructed, which makes full
use of the sparse distribution in the Fourier representation of the
complex-valued time signal. Simulation experiments illustrate the
proposed method-s advantages over conventional methods in both
noiseless and additive white Gaussian noise cases.
Abstract: As the world changes more rapidly, the demand for update information for resource management, environment monitoring, planning are increasing exponentially. Integration of Remote Sensing with GIS technology will significantly promote the ability for addressing these concerns. This paper presents an alternative way of update GIS applications using image processing and high resolution images. We show a method of high-resolution image segmentation using graphs and morphological operations, where a preprocessing step (watershed operation) is required. A morphological process is then applied using the opening and closing operations. After this segmentation we can extract significant cartographic elements such as urban areas, streets or green areas. The result of this segmentation and this extraction is then used to update GIS applications. Some examples are shown using aerial photography.
Abstract: Information Retrieval has the objective of studying
models and the realization of systems allowing a user to find the
relevant documents adapted to his need of information. The
information search is a problem which remains difficult because the
difficulty in the representing and to treat the natural languages such
as polysemia. Intentional Structures promise to be a new paradigm to
extend the existing documents structures and to enhance the different
phases of documents process such as creation, editing, search and
retrieval. The intention recognition of the author-s of texts can reduce
the largeness of this problem. In this article, we present intentions
recognition system is based on a semi-automatic method of
extraction the intentional information starting from a corpus of text.
This system is also able to update the ontology of intentions for the
enrichment of the knowledge base containing all possible intentions
of a domain. This approach uses the construction of a semi-formal
ontology which considered as the conceptualization of the intentional
information contained in a text. An experiments on scientific
publications in the field of computer science was considered to
validate this approach.
Abstract: Carbon tetrachloride (CCl4) is a well-known
hepatotoxin and exposure to this chemical is known to induce
oxidative stress and causes liver injury by the formation of free
radicals. Flacourtia indica commonly known as 'Baichi' has been
reported as an effective remedy for the treatment of a variety of
diseases. The objective of this study was to investigate the
hepatoprotective activity of aqueous extract of leaves of Flacourtia
indica against CCl4 induced hepatotoxicity. Animals were pretreated
with the aqueous extract of Flacourtia indica (250 & 500 mg/kg
body weight) for one week and then challenged with CCl4 (1.5 ml/kg
bw) in olive oil (1:1, v/v) on 7th day. Serum marker enzymes (ALP,
AST, ALT, Total Protein & Total Bilirubin) and TBARS level
(Marker for oxidative stress) were estimated in all the study groups.
Alteration in the levels of biochemical markers of hepatic damage
like AST, ALT, ALP, Total Protein, Total Bilirubin and lipid
peroxides (TBARS) were tested in both CCl4 treated and extract
treated groups. CCl4 has enhanced the AST, ALT, ALP and the
Lipid peroxides (TBARS) in liver. Treatment of aqueous extract of
Flacourtia indica leaves (250 & 500 mg/kg) exhibited a significant
protective effect by altering the serum levels of AST, ALT, ALP,
Total Protein, Total Bilirubin and liver TBARS. These biochemical
observations were supported by histopathological study of liver
sections. From this preliminary study it has been concluded that the
aqueous extract of the leaves of Flacourtia indica protects liver
against oxidative damages and could be used as an effective protector
against CCl4 induced hepatic damage. Our findings suggested that
Flacourtia indica possessed good hepatoprotective activity
Abstract: In this paper we present a new method for over-height
vehicle detection in low headroom streets and highways using digital
video possessing. The accuracy and the lower price comparing to
present detectors like laser radars and the capability of providing
extra information like speed and height measurement make this
method more reliable and efficient. In this algorithm the features are
selected and tracked using KLT algorithm. A blob extraction
algorithm is also applied using background estimation and
subtraction. Then the world coordinates of features that are inside the
blobs are estimated using a noble calibration method. As, the heights
of the features are calculated, we apply a threshold to select overheight
features and eliminate others. The over-height features are
segmented using some association criteria and grouped using an
undirected graph. Then they are tracked through sequential frames.
The obtained groups refer to over-height vehicles in a scene.
Abstract: The extensive number of engineering drawing will be referred for planning process and the changes will produce a good engineering design to meet the demand in producing a new model. The advantage in reuse of engineering designs is to allow continuous product development to further improve the quality of product development, thus reduce the development costs. However, to retrieve the existing engineering drawing, it is time consuming, a complex process and are expose to errors. Engineering drawing file searching system will be proposed to solve this problem. It is essential for engineer and designer to have some sort of medium to enable them to search for drawing in the most effective way. This paper lays out the proposed research project under the area of information extraction in engineering drawing.
Abstract: A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Abstract: Uranium mining and processing in Brazil occur in a
northeastern area near to Caetité-BA. Several Non-Governmental
Organizations claim that uranium mining in this region is a pollutant
causing health risks to the local population,but those in charge of the
complex extraction and production of“yellow cake" for generating
fuel to the nuclear power plants reject these allegations. This study
aimed at identifying potential problems caused by mining to the
population of Caetité. In this, work,the concentrations of 238U, 232Th
and 40K radioisotopes in the teeth of the Caetité population were
determined by ICP-MS. Teeth are used as bioindicators of
incorporated radionuclides. Cumulative radiation doses in the
skeleton were also determined. The concentration values were below
0.008 ppm, and annual effective dose due to radioisotopes are below
to the reference values. Therefore, it is not possible to state that the
mining process in Caetité increases pollution or radiation exposure in
a meaningful way.
Abstract: Unified Speech Audio Coding (USAC), the latest MPEG standardization for unified speech and audio coding, uses a speech/audio classification algorithm to distinguish speech and audio segments of the input signal. The quality of the recovered audio can be increased by well-designed orchestra/percussion classification and subsequent processing. However, owing to the shortcoming of the system, introducing an orchestra/percussion classification and modifying subsequent processing can enormously increase the quality of the recovered audio. This paper proposes an orchestra/percussion classification algorithm for the USAC system which only extracts 3 scales of Mel-Frequency Cepstral Coefficients (MFCCs) rather than traditional 13 scales of MFCCs and use Iterative Dichotomiser 3 (ID3) Decision Tree rather than other complex learning method, thus the proposed algorithm has lower computing complexity than most existing algorithms. Considering that frequent changing of attributes may lead to quality loss of the recovered audio signal, this paper also design a modified subsequent process to help the whole classification system reach an accurate rate as high as 97% which is comparable to classical 99%.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.