Abstract: In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.
Abstract: The purpose of this study is mainly to predict collision
frequency on the horizontal tangents combined with vertical curves
using artificial neural network methods. The proposed ANN models
are compared with existing regression models. First, the variables
that affect collision frequency were investigated. It was found that
only the annual average daily traffic, section length, access density,
the rate of vertical curvature, smaller curve radius before and after
the tangent were statistically significant according to related
combinations. Second, three statistical models (negative binomial,
zero inflated Poisson and zero inflated negative binomial) were
developed using the significant variables for three alignment
combinations. Third, ANN models are developed by applying the
same variables for each combination. The results clearly show that
the ANN models have the lowest mean square error value than those
of the statistical models. Similarly, the AIC values of the ANN
models are smaller to those of the regression models for all the
combinations. Consequently, the ANN models have better statistical
performances than statistical models for estimating collision
frequency. The ANN models presented in this paper are
recommended for evaluating the safety impacts 3D alignment
elements on horizontal tangents.
Abstract: The purpose of this study was to analyze relationship
between gender, BMI, and lifestyle with bone mineral density
(BMD) of adolescent in urban areas . The place of this study in
Jakarta State University, Indonesia. The number of samples involved
as many as 200 people, consisting of 100 men and 100 women. BMD
was measured using Quantitative Ultrasound Bone Densitometry.
While the questionnaire used to collect data on age, gender, and
lifestyle (calcium intake, smoking habits, alcohol consumption, tea,
coffee, sports, and sun exposure). Mean age of men and women,
respectively as much as 20.7 ± 2.18 years and 21 ± 1.61 years. Mean
BMD values of men was 1.084 g/cm ² ± 0.11 while women was
0.976 g/cm ² ± 0.10. Men and women with normal BMD respectively
as much as 46.7% and 16.7%. Men and women affected by
osteopenia respectively as much as 50% and 80%. Men and women
affected by osteoporosis respectively as much as 3.3% and 3.3%.
Mean BMI of men and women, respectively as much as 21.4 ± 2.07
kg/m2 and 20.9 ± 2.06 kg/m2. Mean lifestyle score of men and
women , respectively as much as 71.9 ± 5.84 and 70.1 ± 5.67
(maximum score 100). Based on Spearman and Pearson Correlation
test, there were relationship significantly between gender and
lifestyle with BMD.
Abstract: Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.
Abstract: Stocking density is considered one of the important
factors affecting fish growth. But, information related to impact of
stocking density on growth performance of monosex tilapia population
under the ecological conditions of Gangetic plains in West Bengal,
India is limited. The aim of our study was to compare the growth
potential of monosex tilapia at various stocking densities and to
determine an ideal stocking density for culture of all-male monosex
fish. The males were isolated by examination of genital papilla region
and were stocked separately in 0.01 ha earthen ponds at different
stocking densities (5000, 10000, 15000, 20000, 25000 and 30000
fingerlings/ha). It was found that the highest weight, length, daily
weight gain, growth rate and protein content were observed for the
20000 fish/ha density class. Thus, culture of monosex tilapia at a
density of 20000 fish/ha can be considered ideal for augmented
production of the fish under Indian context.
Abstract: Different methods containing biometric algorithms are
presented for the representation of eigenfaces detection including
face recognition, are identification and verification. Our theme of this
research is to manage the critical processing stages (accuracy, speed,
security and monitoring) of face activities with the flexibility of
searching and edit the secure authorized database. In this paper we
implement different techniques such as eigenfaces vector reduction
by using texture and shape vector phenomenon for complexity
removal, while density matching score with Face Boundary Fixation
(FBF) extracted the most likelihood characteristics in this media
processing contents. We examine the development and performance
efficiency of the database by applying our creative algorithms in both
recognition and detection phenomenon. Our results show the
performance accuracy and security gain with better achievement than
a number of previous approaches in all the above processes in an
encouraging mode.
Abstract: An experiment was conducted on the comparative
study of drip and furrow irrigation methods at the farmer-s field in
Umar Kot. The total area under experiment about 4000m2 was
divided into two equal portions. One portion about 40m X 50m was
occupied by drip and the other portion about 40m X 50m by furrow
irrigation method. Soil at the experimental site was clay loam in
texture for 0-60cm depth; average dry bulk density and field capacity
was 1.16g/cm3 and 28.5% respectively. The results reveal that the
drip irrigation method saved 56.4% water and gave 22% more yield
as compared to that of furrow irrigation method. Higher water use
efficiency about 4.87 was obtained in drip irrigation method; whereas
lower water used efficiency about 1.66 was obtained in furrow
irrigation method. The present study suggests farming community to
adopt drip irrigation method instead of old traditional flooding
methods.
Abstract: Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.
Abstract: Segmentation is an important step in medical image
analysis and classification for radiological evaluation or computer
aided diagnosis. The CAD (Computer Aided Diagnosis ) of lung CT
generally first segment the area of interest (lung) and then analyze
the separately obtained area for nodule detection in order to
diagnosis the disease. For normal lung, segmentation can be
performed by making use of excellent contrast between air and
surrounding tissues. However this approach fails when lung is
affected by high density pathology. Dense pathologies are present in
approximately a fifth of clinical scans, and for computer analysis
such as detection and quantification of abnormal areas it is vital that
the entire and perfectly lung part of the image is provided and no
part, as present in the original image be eradicated. In this paper we
have proposed a lung segmentation technique which accurately
segment the lung parenchyma from lung CT Scan images. The
algorithm was tested against the 25 datasets of different patients
received from Ackron Univeristy, USA and AGA Khan Medical
University, Karachi, Pakistan.
Abstract: The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.
Abstract: In this work, we incorporated a quartic bond potential
into a coarse-grained bead-spring model to study lubricant adsorption
on a solid surface as well as depletion instability. The surface tension
density and the number density profiles were examined to verify the
solid-liquid and liquid-vapor interfaces during heat treatment. It was
found that both the liquid-vapor interfacial thickness and the
solid-vapor separation increase with the temperatureT* when T*is
below the phase transition temperature Tc
*. At high temperatures
(T*>Tc
*), the solid-vapor separation decreases gradually as the
temperature increases. In addition, we evaluated the lubricant weight
and bond loss profiles at different temperatures. It was observed that
the lubricant desorption is favored over decomposition and is the main
cause of the lubricant failure at the head disk interface in our
simulations.
Abstract: In nature, electromagnetic fields always appear like
atmosphere static electric field, the earth's static magnetic field and
the wide-rang frequency electromagnetic field caused by lightening.
However, besides natural electromagnetic fields (EMF), today human
beings are mostly exposed to artificial electromagnetic fields due to
technology progress and outspread use of electrical devices. To
evaluate nuisance of EMF, it is necessary to know field intensity for
every frequency which appears and compare it with allowed values.
Low frequency EMF-s around transmission and distribution lines are
time-varying quasi-static electromagnetic fields which have
conservative component of low frequency electrical field caused by
charges and eddy component of low frequency magnetic field caused
by currents. Displacement current or field delay are negligible, so
energy flow in quasi-static EMF involves diffusion, analog like heat
transfer. Electrical and magnetic field can be analyzed separately.
This paper analysis the numerical calculations in ELF-400 software
of EMF in distribution substation in shopping center. Analyzing the
results it is possible to specify locations exposed to the fields and
give useful suggestion to eliminate electromagnetic effect or reduce it
on acceptable level within the non-ionizing radiation norms and
norms of protection from EMF.
Abstract: Automatic reading of handwritten cheque is a computationally
complex process and it plays an important role in financial
risk management. Machine vision and learning provide a viable
solution to this problem. Research effort has mostly been focused
on recognizing diverse pitches of cheques and demand drafts with an
identical outline. However most of these methods employ templatematching
to localize the pitches and such schemes could potentially
fail when applied to different types of outline maintained by the
bank. In this paper, the so-called outline problem is resolved by
a cheque information tree (CIT), which generalizes the localizing
method to extract active-region-of-entities. In addition, the weight
based density plot (WBDP) is performed to isolate text entities and
read complete pitches. Recognition is based on texture features using
neural classifiers. Legal amount is subsequently recognized by both
texture and perceptual features. A post-processing phase is invoked
to detect the incorrect readings by Type-2 grammar using the Turing
machine. The performance of the proposed system was evaluated
using cheque and demand drafts of 22 different banks. The test data
consists of a collection of 1540 leafs obtained from 10 different
account holders from each bank. Results show that this approach
can easily be deployed without significant design amendments.
Abstract: We have defined two suites of metrics, which cover
static and dynamic aspects of component assembly. The static
metrics measure complexity and criticality of component assembly,
wherein complexity is measured using Component Packing Density
and Component Interaction Density metrics. Further, four criticality
conditions namely, Link, Bridge, Inheritance and Size criticalities
have been identified and quantified. The complexity and criticality
metrics are combined to form a Triangular Metric, which can be used
to classify the type and nature of applications. Dynamic metrics are
collected during the runtime of a complete application. Dynamic
metrics are useful to identify super-component and to evaluate the
degree of utilisation of various components. In this paper both static
and dynamic metrics are evaluated using Weyuker-s set of properties.
The result shows that the metrics provide a valid means to measure
issues in component assembly. We relate our metrics suite with
McCall-s Quality Model and illustrate their impact on product
quality and to the management of component-based product
development.
Abstract: Hydrogen is an important chemical in many industries
and it is expected to become one of the major fuels for energy
generation in the future. Unfortunately, hydrogen does not exist in its
elemental form in nature and therefore has to be produced from
hydrocarbons, hydrogen-containing compounds or water.
Above its critical point (374.8oC and 22.1MPa), water has lower
density and viscosity, and a higher heat capacity than those of
ambient water. Mass transfer in supercritical water (SCW) is
enhanced due to its increased diffusivity and transport ability. The
reduced dielectric constant makes supercritical water a better solvent
for organic compounds and gases. Hence, due to the aforementioned
desirable properties, there is a growing interest toward studies
regarding the gasification of organic matter containing biomass or
model biomass solutions in supercritical water.
In this study, hydrogen and biofuel production by the catalytic
gasification of 2-Propanol in supercritical conditions of water was
investigated. Pt/Al2O3and Ni/Al2O3were the catalysts used in the
gasification reactions. All of the experiments were performed under a
constant pressure of 25MPa. The effects of five reaction temperatures
(400, 450, 500, 550 and 600°C) and five reaction times (10, 15, 20,
25 and 30 s) on the gasification yield and flammable component
content were investigated.
Abstract: Irradiated material is a typical example of a complex
system with nonlinear coupling between its elements. During
irradiation the radiation damage is developed and this development
has bifurcations and qualitatively different kinds of behavior.
The accumulation of primary defects in irradiated crystals is
considered in frame work of nonlinear evolution of complex system.
The thermo-concentration nonlinear feedback is carried out as a
mechanism of self-oscillation development.
It is shown that there are two ways of the defect density evolution
under stationary irradiation. The first is the accumulation of defects;
defect density monotonically grows and tends to its stationary state
for some system parameters. Another way that takes place for
opportune parameters is the development of self-oscillations of the
defect density.
The stationary state, its stability and type are found. The
bifurcation values of parameters (environment temperature, defect
generation rate, etc.) are obtained. The frequency of the selfoscillation
and the conditions of their development is found and
rated. It is shown that defect density, heat fluxes and temperature
during self-oscillations can reach much higher values than the
expected steady-state values. It can lead to a change of typical
operation and an accident, e.g. for nuclear equipment.
Abstract: Experimental investigation of the effect of
hydrophobic injection on siloxane basis on the properties of oldfashioned
type of ceramic brick is presented in the paper. At the
experimental testing, the matrix density, total open porosity, pore size
distribution, sorptivity, water absorption coefficient, sorption and
desorption isotherms are measured for the original, as well as the
hydrophobic-injection treated brick. On the basis of measured data,
the functionality of the hydrophobic injection for the moisture ingress
prevention into the studied ceramic brick is assessed.
Abstract: A new secure knapsack cryptosystem based on the
Merkle-Hellman public key cryptosystem will be proposed in this
paper. Although it is common sense that when the density is low, the
knapsack cryptosystem turns vulnerable to the low-density attack. The
density d of a secure knapsack cryptosystem must be larger than
0.9408 to avoid low-density attack. In this paper, we investigate a
new Permutation Combination Algorithm. By exploiting this
algorithm, we shall propose a novel knapsack public-key cryptosystem.
Our proposed scheme can enjoy a high density to avoid the
low-density attack. The density d can also exceed 0.9408 to avoid
the low-density attack.
Abstract: This study carried out to determine the effect of plant
densities on some agronomic characteristics of four safflower cultivars in spring planting. The experiment was conducted at Yazd,
Iran- using a factorial in a randomized complete block design with four replications. Cultivars were including Arak, IL, Asteria and Local and plant densities were 10, 13.3, 20 and 40 plant/m2. Number
of seeds/head, number of heads/plant, HI, 1000-seed weight and seed yield significantly decreased as planting density increased. With increasing planting density, LAI, plant height, first branch height and
biological yield increased. The highest seed yield was obtained in 13.3 plant/m2 (2167 kg/ha). There were significant differences
between cultivars. Local cv. had higher seed yield than the other cultivars mainly due to higher heads/plant and seeds/head.
Abstract: Empirical force fields and density functional theory
(DFT) was used to study the binding energies and structures of
methylamine on the surface of activated carbons (ACs). This is a first
step in studying the adsorption of alkyl amines on the surface of
functionalized ACs. The force fields used were Dreiding (DFF),
Universal (UFF) and Compass (CFF) models. The generalized
gradient approximation with Perdew Wang 91 (PW91) functional
was used for DFT calculations. In addition to obtaining the aminecarboxylic
acid adsorption energies, the results were used to establish
reliability of the empirical models for these systems. CFF predicted a
binding energy of -9.227 (kcal/mol) which agreed with PW91 at -
13.17 (kcal/mol), compared to DFF 0 (kcal/mol) and UFF -0.72
(kcal/mol). However, the CFF binding energies for the amine to ester
and ketone disagreed with PW91 results. The structures obtained
from all models agreed with PW91 results.