Abstract: Graph decompositions are vital in the study of combinatorial design theory. Given two graphs G and H, an H-decomposition of G is a partition of the edge set of G into disjoint isomorphic copies of H. An n-sun is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper we have proved that the complete graph of order 2n, K2n can be decomposed into n-2 n-suns, a Hamilton cycle and a perfect matching, when n is even and for odd case, the decomposition is n-1 n-suns and a perfect matching. For an odd order complete graph K2n+1, delete the star subgraph K1, 2n and the resultant graph K2n is decomposed as in the case of even order. The method of building n-suns uses Walecki's construction for the Hamilton decomposition of complete graphs. A spanning tree decomposition of even order complete graphs is also discussed using the labeling scheme of n-sun decomposition. A complete bipartite graph Kn, n can be decomposed into n/2 n-suns when n/2 is even. When n/2 is odd, Kn, n can be decomposed into (n-2)/2 n-suns and a Hamilton cycle.
Abstract: The present work represents an investigation of the
hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein
isolate (PuOC PI) by pepsin. To examine the effectiveness and
suitability of pepsin towards PuOC PI the kinetic parameters for
pepsin on PuOC PI were determined and then, the hydrolysis process
was studied using Response Surface Methodology (RSM). The
hydrolysis was carried out at temperature of 30°C and pH 3.00. Time
and initial enzyme/substrate ratio (E/S) at three levels were selected
as the independent parameters. The degree of hydrolysis, DH, was
mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3
mA/mg proteins. Since the proposed second-order polynomial model
showed good fit with the experimental data (R2 = 0.9822), the
obtained mathematical model could be used for monitoring the
hydrolysis of PuOC PI by pepsin, under studied experimental
conditions, varying the time and initial E/S. To achieve the highest
value of DH (39.13 %), the obtained optimum conditions for time
and initial E/S were 30 min and 1.024 mA/mg proteins.
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: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: Autism spectrum disorder is characterized by
abnormalities in social communication, language abilities and
repetitive behaviors. The present study focused on some grammatical
deficits in autistic children. We evaluated the impairment of correct
use of different Persian verb tenses in autistic children-s speech. Two
standardized Language Test were administered then gathered data
were analyzed. The main result of this study was significant
difference between the mean scores of correct responses to present
tense in comparison with past tense in Persian language. This study
demonstrated that tense is severely impaired in autistic children-s
speech. Our findings indicated those autistic children-s production of
simple present/ past tense opposition to be better than production of
future and past periphrastic forms (past perfect, present perfect, past
progressive).
Abstract: Obesity is frequent attendant phenomenon of patients
with endocrinological disease. Between BMI and endocrinological
diseases is close correlation. In thesis we focused on the allocation of
hormone concentration – PTH and TSH, CHOL a mineral element Ca
in a blood serum. The examined group was formed by 100
respondents (women) aged 36 – 83 years, who were divided into two
groups – control group (CG), group with diagnosed endocrine disease
(DED). The concentration of PTH and TSH, Ca and CHOL was
measured through the medium of analyzers Cobas e411 (Japan);
Cobas Integra 400 (Switzerland). At individuals was measured body
weight as well as stature and thereupon from those data we
enumerated BMI. On the basis of Student T-test in biochemical
parameter of PTH and Ca we found out significantly meaningful
difference (p
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Stirred tanks have applications in many chemical
processes where mixing is important for the overall performance of
the system. In present work 5%v of the tank is filled by solid particles
with diameter of 700 m that Rushton Turbine and Propeller impeller
is used for stirring. An Eulerian-Eulerian Multi Fluid Model coupled
and for modeling rotating of impeller, moving reference frame
(MRF) technique was used and standard-k- model was selected for
turbulency. Flow field, radial velocity and axial distribution of solid
for both of impellers was investigation and comparison. Comparisons
of simulation results between Rushton Turbine and propeller impeller
shows that final quality of solid-liquid slurry in different rotating
speed for propeller impeller is better than the Rushton Turbine.
Abstract: This paper describes a research project on Year 3 primary school students in Malaysia in their use of computer-based video game to enhance learning of multiplication facts (tables) in the Mathematics subject. This study attempts to investigate whether video games could actually contribute to positive effect on children-s learning or otherwise. In conducting this study, the researchers assume a neutral stand in the investigation as an unbiased outcome of the study would render reliable response to the impact of video games in education which would contribute to the literature of technology-based education as well as impact to the pedagogical aspect of formal education. In order to conduct the study, a subject (Mathematics) with a specific topic area in the subject (multiplication facts) is chosen. The study adopts a causal-comparative research to investigate the impact of the inclusion of a computer-based video game designed to teach multiplication facts to primary level students. Sample size is 100 students divided into two i.e., A: conventional group and B conventional group aided by video games. The conventional group (A) would be taught multiplication facts (timetables) and skills conventionally. The other group (B) underwent the same lessons but with supplementary activity: a computer-based video game on multiplication which is called Timez-Attack. Analysis of marks accrued from pre-test will be compared to post- test using comparisons of means, t tests, and ANOVA tests to investigate the impact of computer games as an added learning activity. The findings revealed that video games as a supplementary activity to classroom learning brings significant and positive effect on students- retention and mastery of multiplication tables as compared to students who rely only upon formal classroom instructions.
Abstract: Many non-conventional adsorbent have been studied
as economic alternative to commercial activated carbon and mostly
agricultural waste have been introduced such as rubber leaf powder
and hazelnut shell. Microwave Incinerated Rice Husk Ash
(MIRHA), produced from the rice husk is one of the low-cost
materials that were used as adsorbent of heavy metal. The aim of
this research was to study the feasibility of using MIRHA500 and
MIRHA800 as adsorbent for the removal of Cu(II) metal ions from
aqueous solutions by the batch studies. The adsorption of Cu(II) into
MIRHA500 and MIRH800 favors Fruendlich isotherm and imply
pseudo – kinetic second order which applied chemisorptions
Abstract: In this paper, using a model transformation approach a system of linear delay differential equations (DDEs) with multiple delays is converted to a non-delayed initial value problem. The variational iteration method (VIM) is then applied to obtain the approximate analytical solutions. Numerical results are given for several examples involving scalar and second order systems. Comparisons with the classical fourth-order Runge-Kutta method (RK4) verify that this method is very effective and convenient.
Abstract: The effect of a chiral bianisotropic substrate on the
complex resonant frequency of a rectangular microstrip resonator has
been studied on the basis of the integral equation formulation. The
analysis is based on numerical resolution of the integral equation
using Galerkin procedure for moment method in the spectral domain.
This work aim first to study the effect of the chirality of a
bianisotopic substrate upon the resonant frequency and the half
power bandwidth, second the effect of a magnetic anisotropy via an
asymptotic approach for very weak substrate upon the resonant
frequency and the half power bandwidth has been investigated. The
obtained results are compared with previously published work [11-9],
they were in good agreement.
Abstract: In this paper, we evaluate the performance of some wavelet based coding algorithms such as 3D QT-L, 3D SPIHT and JPEG2K. In the first step we achieve an objective comparison between three coders, namely 3D SPIHT, 3D QT-L and JPEG2K. For this purpose, eight MRI head scan test sets of 256 x 256x124 voxels have been used. Results show superior performance of 3D SPIHT algorithm, whereas 3D QT-L outperforms JPEG2K. The second step consists of evaluating the robustness of 3D SPIHT and JPEG2K coding algorithm over wireless transmission. Compressed dataset images are then transmitted over AWGN wireless channel or over Rayleigh wireless channel. Results show the superiority of JPEG2K over these two models. In fact, it has been deduced that JPEG2K is more robust regarding coding errors. Thus we may conclude the necessity of using corrector codes in order to protect the transmitted medical information.
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: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
Abstract: The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.
Abstract: This paper describes a study of geometrically
nonlinear free vibration of thin circular functionally graded (CFGP)
plates resting on Winkler elastic foundations. The material properties
of the functionally graded composites examined here are assumed to
be graded smoothly and continuously through the direction of the
plate thickness according to a power law and are estimated using the
rule of mixture. The theoretical model is based on the classical Plate
theory and the Von-Kármán geometrical nonlinearity assumptions.
An homogenization procedure (HP) is developed to reduce the
problem considered here to that of isotropic homogeneous circular
plates resting on Winkler foundation. Hamilton-s principle is applied
and a multimode approach is derived to calculate the fundamental
nonlinear frequency parameters which are found to be in a good
agreement with the published results. On the other hand, the
influence of the foundation parameters on the nonlinear fundamental
frequency has also been analysed.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: Grid computing is a high performance computing
environment to solve larger scale computational applications. Grid
computing contains resource management, job scheduling, security
problems, information management and so on. Job scheduling is a
fundamental and important issue in achieving high performance in
grid computing systems. However, it is a big challenge to design an
efficient scheduler and its implementation. In Grid Computing, there
is a need of further improvement in Job Scheduling algorithm to
schedule the light-weight or small jobs into a coarse-grained or
group of jobs, which will reduce the communication time,
processing time and enhance resource utilization. This Grouping
strategy considers the processing power, memory-size and
bandwidth requirements of each job to realize the real grid system.
The experimental results demonstrate that the proposed scheduling
algorithm efficiently reduces the processing time of jobs in
comparison to others.
Abstract: A 2.4GHz (RF) down conversion Gilbert Cell mixer,
implemented in a 0.18-μm CMOS technology with a 1.8V supply, is
presented. Current bleeding (charge injection) technique has been
used to increase the conversion gain and the linearity of the mixer.
The proposed mixer provides 10.75 dB conversion gain ( C G ) with
14.3mw total power consumption. The IIP3 and 1-dB compression
point of the mixer are 8dbm and -4.6dbm respectively, at 300 MHz
IF frequencies. Comparing the current design against the
conventional mixer design, demonstrates better performance in the
conversion gain, linearity, noise figure and port-to-port isolation.