Abstract: This study examines age and sex patterns of
children-s disability in the Parila union of Rajshahi, Bangladesh. For
this we assumed that (1) prevalence of disability patterns and its
severity in the middle childhood are higher than in the infancy or
latter childhood in the Parila union of Rajshahi, (2) prevalence of
disability patterns and its severity among the boys compared to girls
are higher in the study area of Bangladesh. In order to examine the
assumptions 102 samples, including their mothers were selected
based on snowball process and the respondents were individually
interviewed with semi-structured questionnaire method. The results
of the study suggest that disability patterns and its severity among the
male children were two-fold higher than the female children. In
addition, these patterns of children-s disability and its severity in the
middle childhood were also higher than in the infancy or latter
childhood. Further study should conduct how socio-structural factors
influence age and sex patterns of children-s disability patterns and its
severity in Bangladesh.
Abstract: The recognition of human faces, especially those with
different orientations is a challenging and important problem in image
analysis and classification. This paper proposes an effective scheme
for rotation invariant face recognition using Log-Polar Transform and
Discrete Cosine Transform combined features. The rotation invariant
feature extraction for a given face image involves applying the logpolar
transform to eliminate the rotation effect and to produce a row
shifted log-polar image. The discrete cosine transform is then applied
to eliminate the row shift effect and to generate the low-dimensional
feature vector. A PSO-based feature selection algorithm is utilized to
search the feature vector space for the optimal feature subset.
Evolution is driven by a fitness function defined in terms of
maximizing the between-class separation (scatter index).
Experimental results, based on the ORL face database using testing
data sets for images with different orientations; show that the
proposed system outperforms other face recognition methods. The
overall recognition rate for the rotated test images being 97%,
demonstrating that the extracted feature vector is an effective rotation
invariant feature set with minimal set of selected features.
Abstract: The performance of an image filtering system depends
on its ability to detect the presence of noisy pixels in the image. Most
of the impulse detection schemes assume the presence of salt and
pepper noise in the images and do not work satisfactorily in case of
uniformly distributed impulse noise. In this paper, a new algorithm is
presented to improve the performance of switching median filter in
detection of uniformly distributed impulse noise. The performance of
the proposed scheme is demonstrated by the results obtained from
computer simulations on various images.
Abstract: When binary decision diagrams are formed from
uniformly distributed Monte Carlo data for a large number of
variables, the complexity of the decision diagrams exhibits a
predictable relationship to the number of variables and minterms. In
the present work, a neural network model has been used to analyze the
pattern of shortest path length for larger number of Monte Carlo data
points. The neural model shows a strong descriptive power for the
ISCAS benchmark data with an RMS error of 0.102 for the shortest
path length complexity. Therefore, the model can be considered as a
method of predicting path length complexities; this is expected to lead
to minimum time complexity of very large-scale integrated circuitries
and related computer-aided design tools that use binary decision
diagrams.
Abstract: Digital watermarking is one of the techniques for
copyright protection. In this paper, a normalization-based robust
image watermarking scheme which encompasses singular value
decomposition (SVD) and discrete cosine transform (DCT)
techniques is proposed. For the proposed scheme, the host image is
first normalized to a standard form and divided into non-overlapping
image blocks. SVD is applied to each block. By concatenating the
first singular values (SV) of adjacent blocks of the normalized image,
a SV block is obtained. DCT is then carried out on the SV blocks to
produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency
band of a SVD-DCT block by imposing a particular
relationship between two pseudo-randomly selected DCT
coefficients. An adaptive frequency mask is used to adjust local
watermark embedding strength. Watermark extraction involves
mainly the inverse process. The watermark extracting method is blind
and efficient. Experimental results show that the quality degradation
of watermarked image caused by the embedded watermark is visually
transparent. Results also show that the proposed scheme is robust
against various image processing operations and geometric attacks.
Abstract: Understanding how airborne pathogens are
transported through hospital wards is essential for determining the
infection risk to patients and healthcare workers. This study utilizes
Computational Fluid Dynamics (CFD) simulations to explore
possible pathogen transport within a six-bed partitioned Nightingalestyle
hospital ward.
Grid independence of a ward model was addressed using the Grid
Convergence Index (GCI) from solutions obtained using three fullystructured
grids. Pathogens were simulated using source terms in
conjunction with a scalar transport equation and a RANS turbulence
model. Errors were found to be less than 4% in the calculation of air
velocities but an average of 13% was seen in the scalar field.
A parametric study of variations in the pathogen release point
illustrated that its distribution is strongly influenced by the local
velocity field and the degree of air mixing present.
Abstract: An investigation of noise in a micro stepping motor is
considered to study in this article. Because of the trend towards higher
precision and more and more small 3C (including Computer,
Communication and Consumer Electronics) products, the micro
stepping motor is frequently used to drive the micro system or the
other 3C products. Unfortunately, noise in a micro stepped motor is
too large to accept by the customs. To depress the noise of a micro
stepped motor, the dynamic characteristics in this system must be
studied. In this article, a Visual Basic (VB) computer program speed
controlled micro stepped motor in a digital camera is investigated.
Karman KD2300-2S non-contract eddy current displacement sensor,
probe microphone, and HP 35670A analyzer are employed to analyze
the dynamic characteristics of vibration and noise in a motor. The
vibration and noise measurement of different type of bearings and
different treatment of coils are compared. The rotating components,
bearings, coil, etc. of the motor play the important roles in producing
vibration and noise. It is found that the noise will be depressed about
3~4 dB and 6~7 dB, when substitutes the copper bearing with plastic
one and coats the motor coil with paraffin wax, respectively.
Abstract: Document image processing has become an
increasingly important technology in the automation of office
documentation tasks. During document scanning, skew is inevitably
introduced into the incoming document image. Since the algorithm
for layout analysis and character recognition are generally very
sensitive to the page skew. Hence, skew detection and correction in
document images are the critical steps before layout analysis. In this
paper, a novel skew detection method is presented for binary
document images. The method considered the some selected
characters of the text which may be subjected to thinning and Hough
transform to estimate skew angle accurately. Several experiments
have been conducted on various types of documents such as
documents containing English Documents, Journals, Text-Book,
Different Languages and Document with different fonts, Documents
with different resolutions, to reveal the robustness of the proposed
method. The experimental results revealed that the proposed method
is accurate compared to the results of well-known existing methods.
Abstract: The effect of moisture content and loading rate on
mechanical strength of 12 brown rice grain varieties was determined.
The results showed that the rupture force of brown rice grain
decreased by increasing the moisture content and loading rate. The
highest rupture force values was obtained at the moisture content of
8% (w.b.) and loading rate of 10 mm/min; while the lowest rupture
force corresponded to the moisture content of 14% (w.b.) and loading
rate of 15 mm/min. The 12 varieties were divided into three groups,
namely local short grain varieties, local long grain varieties and
improved long grain varieties. It was observed that the rupture
strength of the three groups were statistically different from each
other (P
Abstract: This paper discusses the causal explanation capability
of QRIOM, a tool aimed at supporting learning of organic chemistry
reactions. The development of the tool is based on the hybrid use of
Qualitative Reasoning (QR) technique and Qualitative Process
Theory (QPT) ontology. Our simulation combines symbolic,
qualitative description of relations with quantity analysis to generate
causal graphs. The pedagogy embedded in the simulator is to both
simulate and explain organic reactions. Qualitative reasoning through
a causal chain will be presented to explain the overall changes made
on the substrate; from initial substrate until the production of final
outputs. Several uses of the QPT modeling constructs in supporting
behavioral and causal explanation during run-time will also be
demonstrated. Explaining organic reactions through causal graph
trace can help improve the reasoning ability of learners in that their
conceptual understanding of the subject is nurtured.
Abstract: In illumination variant face recognition, existing
methods extracting face albedo as light normalized image may lead to
loss of extensive facial details, with light template discarded. To
improve that, a novel approach for realistic facial texture
reconstruction by combining original image and albedo image is
proposed. First, light subspaces of different identities are established
from the given reference face images; then by projecting the original
and albedo image into each light subspace respectively, texture
reference images with corresponding lighting are reconstructed and
two texture subspaces are formed. According to the projections in
texture subspaces, facial texture with normal light can be synthesized.
Due to the combination of original image, facial details can be
preserved with face albedo. In addition, image partition is applied to
improve the synthesization performance. Experiments on Yale B and
CMUPIE databases demonstrate that this algorithm outperforms the
others both in image representation and in face recognition.
Abstract: Structural representation and technology mapping of
a Boolean function is an important problem in the design of nonregenerative
digital logic circuits (also called combinational logic
circuits). Library aware function manipulation offers a solution to
this problem. Compact multi-level representation of binary networks,
based on simple circuit structures, such as AND-Inverter Graphs
(AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR
Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter
Graphs, Reduced Boolean Circuits [8] does exist in
literature. In this work, we discuss a novel and efficient graph
realization for combinational logic circuits, represented using a
NAND-NOR-Inverter Graph (NNIG), which is composed of only
two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells.
The networks are constructed on the basis of irredundant disjunctive
and conjunctive normal forms, after factoring, comprising terms with
minimum support. Construction of a NNIG for a non-regenerative
function in normal form would be straightforward, whereas for the
complementary phase, it would be developed by considering a virtual
instance of the function. However, the choice of best NNIG for a
given function would be based upon literal count, cell count and
DAG node count of the implementation at the technology
independent stage. In case of a tie, the final decision would be made
after extracting the physical design parameters.
We have considered AIG representation for reduced disjunctive
normal form and the best of OIG/AOG/AOIG for the minimized
conjunctive normal forms. This is necessitated due to the nature of
certain functions, such as Achilles- heel functions. NNIGs are found
to exhibit 3.97% lesser node count compared to AIGs and
OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells
than AIGs and OIG/AOG/AOIGs for the various samples considered.
We compare the power efficiency and delay improvement achieved
by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for
various case studies. In comparison with functionally equivalent,
irredundant and compact AIGs, NNIGs report mean savings in power
and delay of 43.71% and 25.85% respectively, after technology
mapping with a 0.35 micron TSMC CMOS process. For a
comparison with OIG/AOG/AOIGs, NNIGs demonstrate average
savings in power and delay by 47.51% and 24.83%. With respect to
device count needed for implementation with static CMOS logic
style, NNIGs utilize 37.85% and 33.95% lesser transistors than their
AIG and OIG/AOG/AOIG counterparts.
Abstract: In this paper, algorithm estimating the blood pressure
was proposed using the pulse transit time (PTT) as a more convenient
method of measuring the blood pressure. After measuring ECG and
pressure pulse, and photoplethysmography, the PTT was calculated
from the acquired signals. Thereafter, the system to indirectly measure
the systolic pressure and the diastolic pressure was composed using
the statistic method. In comparison between the blood pressure
indirectly measured by proposed algorithm estimating the blood
pressure and real blood pressure measured by conventional
sphygmomanometer, the systolic pressure indicates the mean error of
±3.24mmHg and the standard deviation of 2.53mmHg, while the
diastolic pressure indicates the satisfactory result, that is, the mean
error of ±1.80mmHg and the standard deviation of 1.39mmHg. These
results are satisfied with the regulation of ANSI/AAMI for
certification of sphygmomanometer that real measurement error value
should be within the mean error of ±5mmHg and the standard
deviation of 8mmHg. These results are suggest the possibility of
applying to portable and long time blood pressure monitoring system
hereafter.
Abstract: One of the most important areas of knowledge management studies is knowledge sharing. Measured in terms of number of scientific articles and organization-s applications, knowledge sharing stands as an example of success in the field. This paper reviews the related papers in the context of the underlying individual behavioral variables to providea direction framework for future research and writing.
Abstract: In many 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. Here we
consider partially monotone problems, where the target variable
depends monotonically on some of the predictor variables but not all.
We propose an approach to build partially monotone models based
on the convolution of monotone neural networks and kernel
functions. The results from simulations and a real case study on
house pricing show that our approach has significantly better
performance than partially monotone linear models. 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: Ten simply supported grossly underreinforced
tapered concrete beams of full size were tested upto complete
collapse under flexural effect .Out of 10 beams, 5 beams were
nonfibrous and the remaining beams contained fibres. The beams
had a variation in the tapered angle as 2°, 4°, 6°, 8° and 10°. The
concrete mix, conventional steel and the type of fibre used were
held constant. Flat corrugated steel fibres were utilized as
secondary reinforcement. The strength and stability parameters
were measured. It is established that the fibrous tapered beams can
be used economically in earthquake prone areas.
Abstract: From food consumption surveys has been found that potato consumption comparing to other European countries is one of the highest. Hence acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine acrylamide content and estimate intake of acrylamide from roasted potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile, and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. Time and temperature (210 ± 5°C) was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. estimated intake of acrylamide ranges from 0.012 to 0.496μgkg-1 BW per day.
Abstract: Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.
Abstract: The use of neural networks is popular in various
building applications such as prediction of heating load, ventilation
rate and indoor temperature. Significant is, that only few papers deal
with indoor carbon dioxide (CO2) prediction which is a very good
indicator of indoor air quality (IAQ). In this study, a data-driven
modelling method based on multilayer perceptron network for indoor
air carbon dioxide in an apartment building is developed.
Temperature and humidity measurements are used as input variables
to the network. Motivation for this study derives from the following
issues. First, measuring carbon dioxide is expensive and sensors
power consumptions is high and secondly, this leads to short
operating times of battery-powered sensors. The results show that
predicting CO2 concentration based on relative humidity and
temperature measurements, is difficult. Therefore, more additional
information is needed.
Abstract: Nowadays, quick technological changes force companies
to develop innovative products in an increasingly competitive
environment. Therefore, how to enhance the time of new product
development is very important. This design problem often lacks
the exact formula for getting it, and highly depends upon human
designers- past experiences. For these reasons, in this work, a Casebased
reasoning (CBR) system to assist in new product development
is proposed. When a case is recovered from the case base, the system
will take into account not only the attribute-s specific value and
how important it is. It will also take into account if the attribute
has a positive influence over the product development. Hence the
manufacturing time will be improved. This information will be
introduced as a new concept called “adaptability". An application to
this method for hearing instrument new design illustrates the proposed
approach.