Abstract: Acute kidney injury (AKI) is a new worldwide public
health problem. A diagnosis of this disease using creatinine is still a
problem in clinical practice. Therefore, a measurement of biomarkers
responsible for AKI has received much attention in the past couple
years. Cytokine interleukin-18 (IL-18) was reported as one of the
early biomarkers for AKI. The most commonly used method to
detect this biomarker is an immunoassay. This study used a planar
platform to perform an immunoassay using fluorescence for
detection. In this study, anti-IL-18 antibody was immobilized onto a
microscope slide using a covalent binding method. Make-up samples
were diluted at the concentration between 10 to 1000 pg/ml to create
a calibration curve. The precision of the system was determined
using a coefficient of variability (CV), which was found to be less
than 10%. The performance of this immunoassay system was
compared with the measurement from ELISA.
Abstract: Fast depth estimation from binocular vision is often
desired for autonomous vehicles, but, most algorithms could not easily
be put into practice because of the much time cost. We present an
image-processing technique that can fast estimate depth image from
binocular vision images. By finding out the lines which present the
best matched area in the disparity space image, the depth can be
estimated. When detecting these lines, an edge-emphasizing filter is
used. The final depth estimation will be presented after the smooth
filter. Our method is a compromise between local methods and global
optimization.
Abstract: In this paper, we present the design and experimental
evaluation of complementary energy path adiabatic logic (CEPAL)
based 1 bit full adder circuit. A simulative investigation on the
proposed full adder has been done using VIRTUOSO SPECTRE
simulator of cadence in 0.18μm UMC technology and its
performance has been compared with the conventional CMOS full
adder circuit. The CEPAL based full adder circuit exhibits the energy
saving of 70% to the conventional CMOS full adder circuit, at 100
MHz frequency and 1.8V operating voltage.
Abstract: We evaluated the effect of sensory (direct current
(DC), 600μA) and motor (monophasic current, pulse duration 300μs,
100 Hz, 2.5-3mA) intensities of cathodal electrical stimulation (ES)
current to release VEGF and biomechanical properties of wound. 54
male Sprague-dawley rats were randomly assigned into one control
and two experimental groups. A full thickness skin incision was
made on animals- dorsal region. The experimental groups received
ES for 1h/day and every other day. VEGF expression was measured
in skin on the 7th day after surgical incision and tensile strength was
measured on 21st day. On the 7th day, the values of skin VEGF in the
sensory group were significantly greater than those of the other
groups (p < 0.05). Sensory and Motor intensity stimulation, can not
improve the biomechanical properties of the repaired wounds.
It seems the mechanical environment induced by sensory and
motor intensity of electrical stimulation, could not simulate the role
of normal daily stress and strain to maturation of collagen fibers and
their cross links. Further work is needed to determine the relationship
between VEGF expression after ES and its effect on tensile strength
of healed wound.
Abstract: The charge-exchange xenon (CEX) ion generated by ion thruster can backflow to the surface of spacecraft and threaten to the safety of spacecraft operation. In order to evaluate the effects of the induced plasma environment in backflow regions on the spacecraft, we designed a spherical single Langmuir probe of 5.8cm in diameter for measuring low-density plasma parameters in backflow region of ion thruster. In practice, the tests are performed in a two-dimensional array (40cm×60cm) composed of 20 sites. The experiment results illustrate that the electron temperature ranges from 3.71eV to 3.96eV, with the mean value of 3.82eV and the standard deviation of 0.064eV. The electron density ranges from 8.30×1012/m3 to 1.66×1013/m3, with the mean value of 1.30×1013/m3 and the standard deviation of 2.15×1012/m3. All data is analyzed according to the “ideal" plasma conditions of Maxwellian distributions.
Abstract: This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.
Abstract: Fluids are used for heat transfer in many engineering
equipments. Water, ethylene glycol and propylene glycol are some
of the common heat transfer fluids. Over the years, in an attempt to
reduce the size of the equipment and/or efficiency of the process,
various techniques have been employed to improve the heat transfer
rate of these fluids. Surface modification, use of inserts and
increased fluid velocity are some examples of heat transfer
enhancement techniques. Addition of milli or micro sized particles
to the heat transfer fluid is another way of improving heat transfer
rate. Though this looks simple, this method has practical problems
such as high pressure loss, clogging and erosion of the material of
construction. These problems can be overcome by using nanofluids,
which is a dispersion of nanosized particles in a base fluid.
Nanoparticles increase the thermal conductivity of the base fluid
manifold which in turn increases the heat transfer rate. In this work,
the heat transfer enhancement using aluminium oxide nanofluid has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
Abstract: This paper presents key challenges reported by a
group of Australian undergraduate Physical Education students in
conducting a program for persons with an intellectual disability.
Strategies adopted to address these challenges are presented together
with representative feedback given by the Physical Education
students at the completion of the program. The significance of the
program’s findings is summarized.
Abstract: Light is one of the most important qualitative and
symbolic factors and has a special position in architecture and urban
development in regard to practical function. The main function of
light, either natural or artificial, is lighting up the environment and
the constructional forms which is called lighting. However, light is
used to redefine the urban spaces by architectural genius with regard
to three aesthetic, conceptual and symbolic factors. In architecture
and urban development, light has a function beyond lighting up the
environment, and the designers consider it as one of the basic
components. The present research aims at studying the function of
light and color in architectural view and their effects in buildings.
Abstract: Explosions may cause intensive damage to buildings
and sometimes lead to total and progressive destruction. Pressures
induced by explosions are one of the most destructive loads a
structure may experience. While designing structures for great
explosions may be expensive and impractical, engineers are looking
for methods for preventing destructions resulted from explosions. A
favorable structural system is a system which does not disrupt totally
due to local explosion, since such structures sustain less loss in
comparison with structural ones which really bear the load and
suddenly disrupt. Designing and establishing vital and necessary
installations in a way that it is resistant against direct hit of bomb and
rocket is not practical, economical, or expedient in many cases,
because the cost of construction and installation with such
specifications is several times more than the total cost of the related
equipment.
Abstract: Process capability index Cpk is the most widely
used index in making managerial decisions since it provides bounds
on the process yield for normally distributed processes. However,
existent methods for assessing process performance which
constructed by statistical inference may unfortunately lead to fine
results, because uncertainties exist in most real-world applications.
Thus, this study adopts fuzzy inference to deal with testing of Cpk .
A brief score is obtained for assessing a supplier’s process instead of
a severe evaluation.
Abstract: A mammography image is composed of low contrast area where the breast tissues and the breast abnormalities such as microcalcification can hardly be differentiated by the medical practitioner. This paper presents the application of active contour models (Snakes) for the segmentation of microcalcification in mammography images. Comparison on the microcalcifiation areas segmented by the Balloon Snake, Gradient Vector Flow (GVF) Snake, and Distance Snake is done against the true value of the microcalcification area. The true area value is the average microcalcification area in the original mammography image traced by the expert radiologists. From fifty images tested, the result obtained shows that the accuracy of the Balloon Snake, GVF Snake, and Distance Snake in segmenting boundaries of microcalcification are 96.01%, 95.74%, and 95.70% accuracy respectively. This implies that the Balloon Snake is a better segmentation method to locate the exact boundary of a microcalcification region.
Abstract: Addition of milli or micro sized particles to the heat
transfer fluid is one of the many techniques employed for improving
heat transfer rate. Though this looks simple, this method has
practical problems such as high pressure loss, clogging and erosion
of the material of construction. These problems can be overcome by
using nanofluids, which is a dispersion of nanosized particles in a
base fluid. Nanoparticles increase the thermal conductivity of the
base fluid manifold which in turn increases the heat transfer rate.
Nanoparticles also increase the viscosity of the basefluid resulting in
higher pressure drop for the nanofluid compared to the base fluid. So
it is imperative that the Reynolds number (Re) and the volume
fraction have to be optimum for better thermal hydraulic
effectiveness. In this work, the heat transfer enhancement using
aluminium oxide nanofluid using low and high volume fraction
nanofluids in turbulent pipe flow with constant wall temperature has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach. Nanofluid, up till
a volume fraction of 1% is found to be an effective heat transfer
enhancement technique. The Nusselt number (Nu) and friction factor
predictions for the low volume fractions (i.e. 0.02%, 0.1 and 0.5%)
agree very well with the experimental values of Sundar and Sharma
(2010). While, predictions for the high volume fraction nanofluids
(i.e. 1%, 4% and 6%) are found to have reasonable agreement with
both experimental and numerical results available in the literature.
So the computationally inexpensive single phase approach can be
used for heat transfer and pressure drop prediction of new nanofluids.
Abstract: Intellectual capital measurement is a central aspect of knowledge management. The measurement and the evaluation of intangible assets play a key role in allowing an effective management of these assets as sources of competitiveness. For these reasons, managers and practitioners need conceptual and analytical tools taking into account the unique characteristics and economic significance of Intellectual Capital. Following this lead, we propose an efficiency and productivity analysis of Intellectual Capital, as a determinant factor of the company competitive advantage. The analysis is carried out by means of Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). These techniques identify Bests Practice companies that have accomplished competitive advantage implementing successful strategies of Intellectual Capital management, and offer to inefficient companies development paths by means of benchmarking. The proposed methodology is employed on the Biotechnology industry in the period 2007-2010.
Abstract: This study aims to examine the determinants of
purchase intention in C2C e-commerce. Specifically the role of
instant messaging in the C2C e-commerce contextis investigated. In
addition to instant messaging, we brought in two antecedents of
purchase intention - trust and customer satisfaction - to establish a
theoretical research model. Structural equation modeling using
LISREL was used to analyze the data.We discussed the research
findings and suggested some implications for researchers and
practitioners.
Abstract: This study aimed to present the mechanical
performance evaluation of the dynamic hip screw (DHS) for
trochanteric fracture by means of finite element method. The
analyses were performed based on stainless steel and titanium
implant material definitions at various stages of bone healing and
including implant removal. The assessment of the mechanical
performance used two parameters, von Mises stress to evaluate the
strength of bone and implant and elastic strain to evaluate fracture
stability. The results show several critical aspects of dynamic hip
screw for trochanteric fracture stabilization. In the initial stage of
bone healing process, partial weight bearing should be applied to
avoid the implant failure. In the late stage of bone healing, stainless
steel implant should be removed.
Abstract: This paper presents an investigation of the power
penalties imposed by four-wave mixing (FWM) on G.652 (Single-
Mode Fiber - SMF), G.653 (Dispersion-Shifted Fiber - DSF), and
G.655 (Non-Zero Dispersion-Shifted Fiber - NZDSF) compliant
fibers, considering the DWDM grids suggested by the ITU-T
Recommendations G.692, and G.694.1, with uniform channel
spacing of 100, 50, 25, and 12.5 GHz. The mathematical/numerical
model assumes undepleted pumping, and shows very clearly the
deleterious effect of FWM on the performance of DWDM systems,
measured by the signal-to-noise ratio (SNR). The results make it
evident that non-uniform channel spacing is practically mandatory
for WDM systems based on DSF fibers.
Abstract: Software effort estimation is the process of predicting
the most realistic use of effort required to develop or maintain
software based on incomplete, uncertain and/or noisy input. Effort
estimates may be used as input to project plans, iteration plans,
budgets. There are various models like Halstead, Walston-Felix,
Bailey-Basili, Doty and GA Based models which have already used
to estimate the software effort for projects. In this study Statistical
Models, Fuzzy-GA and Neuro-Fuzzy (NF) Inference Systems are
experimented to estimate the software effort for projects. The
performances of the developed models were tested on NASA
software project datasets and results are compared with the Halstead,
Walston-Felix, Bailey-Basili, Doty and Genetic Algorithm Based
models mentioned in the literature. The result shows that the NF
Model has the lowest MMRE and RMSE values. The NF Model
shows the best results as compared with the Fuzzy-GA based hybrid
Inference System and other existing Models that are being used for
the Effort Prediction with lowest MMRE and RMSE values.