Abstract: Photoplethysmography is a simple measurement of the
variation in blood volume in tissue. It detects the pulse signal of heart
beat as well as the low frequency signal of vasoconstriction and
vasodilation. The transmission type measurement is limited to only a
few specific positions for example the index finger that have a short
path length for light. The reflectance type measurement can be
conveniently applied on most parts of the body surface. This study
analyzed the factors that determine the quality of reflectance
photoplethysmograph signal including the emitter-detector distance,
wavelength, light intensity, and optical properties of skin tissue.
Light emitting diodes (LEDs) with four different visible
wavelengths were used as the light emitters. A phototransistor was
used as the light detector. A micro translation stage adjusts the
emitter-detector distance from 2 mm to 15 mm.
The reflective photoplethysmograph signals were measured on
different sites. The optimal emitter-detector distance was chosen to
have a large dynamic range for low frequency drifting without signal
saturation and a high perfusion index. Among these four wavelengths,
a yellowish green (571nm) light with a proper emitter-detection
distance of 2mm is the most suitable for obtaining a steady and reliable
reflectance photoplethysmograph signal
Abstract: A Matlab based software for logistic regression is developed to enhance the process of teaching quantitative topics and assist researchers with analyzing wide area of applications where categorical data is involved. The software offers an option of performing stepwise logistic regression to select the most significant predictors. The software includes a feature to detect influential observations in data, and investigates the effect of dropping or misclassifying an observation on a predictor variable. The input data may consist either as a set of individual responses (yes/no) with the predictor variables or as grouped records summarizing various categories for each unique set of predictor variables' values. Graphical displays are used to output various statistical results and to assess the goodness of fit of the logistic regression model. The software recognizes possible convergence constraints when present in data, and the user is notified accordingly.
Abstract: This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Abstract: Deep cold rolling (DCR) is a cold working process, which easily produces a smooth and work-hardened surface by plastic deformation of surface irregularities. In the present study, the influence of main deep cold rolling process parameters on the surface roughness and the hardness of AISI 4140 steel were studied by using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in terms of identifying the predominant factor amongst the selected parameters, their order of significance and setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. It was found that the ball diameter, rolling force, initial surface roughness and number of tool passes are the most pronounced parameters, which have great effects on the work piece-s surface during the deep cold rolling process. A simple, inexpensive and newly developed DCR tool, with interchangeable collet for using different ball diameters, was used throughout the experimental work presented in this paper.
Abstract: The main aim of this study was to examine whether
people understand indicative conditionals on the basis of syntactic
factors or on the basis of subjective conditional probability. The
second aim was to investigate whether the conditional probability of
q given p depends on the antecedent and consequent sizes or derives
from inductive processes leading to establish a link of plausible cooccurrence
between events semantically or experientially associated.
These competing hypotheses have been tested through a 3 x 2 x 2 x 2
mixed design involving the manipulation of four variables: type of
instructions (“Consider the following statement to be true", “Read the
following statement" and condition with no conditional statement);
antecedent size (high/low); consequent size (high/low); statement
probability (high/low). The first variable was between-subjects, the
others were within-subjects. The inferences investigated were Modus
Ponens and Modus Tollens. Ninety undergraduates of the Second
University of Naples, without any prior knowledge of logic or
conditional reasoning, participated in this study.
Results suggest that people understand conditionals in a syntactic
way rather than in a probabilistic way, even though the perception of
the conditional probability of q given p is at least partially involved in
the conditionals- comprehension. They also showed that, in presence
of a conditional syllogism, inferences are not affected by the
antecedent or consequent sizes. From a theoretical point of view these
findings suggest that it would be inappropriate to abandon the idea
that conditionals are naturally understood in a syntactic way for the
idea that they are understood in a probabilistic way.
Abstract: This study applied the Gaussian trajectory
transfer-coefficient model (GTx) to simulate the particulate matter
concentrations and the source apportionments at Nanzih Air Quality
Monitoring Station in southern Taiwan from November 2007 to
February 2008. The correlation coefficient between the observed and
the calculated daily PM10 concentrations is 0.5 and the absolute bias of
the PM10 concentrations is 24%. The simulated PM10 concentrations
matched well with the observed data. Although the emission rate of
PM10 was dominated by area sources (58%), the results of source
apportionments indicated that the primary sources for PM10 at Nanzih
Station were point sources (42%), area sources (20%) and then upwind
boundary concentration (14%). The obvious difference of PM10 source
apportionment between episode and non-episode days was upwind
boundary concentrations which contributed to 20% and 11% PM10
sources, respectively. The gas-particle conversion of secondary
aerosol and long range transport played crucial roles on the PM10
contribution to a receptor.
Abstract: This paper presents a low-voltage low-power differential linear transconductor with near rail-to-rail input swing. Based on the current-mirror OTA topology, the proposed transconductor combines the Flipped Voltage Follower (FVF) technique to linearize the transconductor behavior that leads to class- AB linear operation and the virtual transistor technique to lower the effective threshold voltages of the transistors which offers an advantage in terms of low supply requirement. Design of the OTA has been discussed. It operates at supply voltages of about ±0.8V. Simulation results for 0.18μm TSMC CMOS technology show a good input range of 1Vpp with a high DC gain of 81.53dB and a total harmonic distortion of -40dB at 1MHz for an input of 1Vpp. The main aim of this paper is to present and compare new OTA design with high transconductance, which has a potential to be used in low voltage applications.
Abstract: The aim of this work is to analyze a viscous flow in
the axisymmetric nozzle taken into account the mesh size both in the
free stream and into the boundary layer. The resolution of the Navier-
Stokes equations is realized by using the finite volume method to
determine the supersonic flow parameters at the exit of convergingdiverging
nozzle. The numerical technique uses the Flux Vector
Splitting method of Van Leer. Here, adequate time stepping
parameter, along with CFL coefficient and mesh size level is selected
to ensure numerical convergence. The effect of the boundary layer
thickness is significant at the exit of the nozzle. The best solution is
obtained with using a very fine grid, especially near the wall, where
we have a strong variation of velocity, temperature and shear stress.
This study enabled us to confirm that the determination of boundary
layer thickness can be obtained only if the size of the mesh is lower
than a certain value limits given by our calculations.
Abstract: Human always tried to create a suitable situation for their life according to environmental conditions. In fact, geography has an important role in the shape of our living area. Iran also as a four-season country has different climate type: hot and humid, hot and dry, mid and humid, and cold; therefore, we can find different architecture styles in Iran. Gilan-s traditional architecture is a suitable sample of sustainable construction in Iran. Because the main factors of every dwelling are the climatic, social, economic and cultural effects which demonstrate the interaction between environment and people settlement. This paper was determined the interaction between environmental factors and the rural dwellings in the Gilan province. Also, traditional village (city) of Masouleh as a rare sample of rural and sustainable architecture was introduced.
Abstract: The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.
Abstract: The aim of this paper is to provide a better
understanding of the implementation of Project Management
practices by UiTM contractors to ensure project success. A
questionnaire survey was administered to 120 UiTM contractors in
Malaysia. The purpose of this method was to gather information on
the contractors- project background and project management skills. It
was found that all of the contractors had basic knowledge and
understanding of project management skills. It is suggested that a
reasonable project plan and an appropriate organizational structure
are influential factors for project success. It is recommended that the
contractors need to have an effective program of work and up to date
information system are emphasized.
Abstract: In the micro and nano-technology industry, the
«clean-rooms» dedicated to manufacturing chip, are equipped with
the most sophisticated equipment-tools. There use a large number of
resources in according to strict specifications for an optimum
working and result. The distribution of «utilities» to the production is
assured by teams who use a supervision tool.
The studies show the interest to control the various parameters of
production or/and distribution, in real time, through a reliable and
effective supervision tool. This document looks at a large part of the
functions that the supervisor must assure, with complementary
functionalities to help the diagnosis and simulation that prove very
useful in our case where the supervised installations are complexed
and in constant evolution.
Abstract: The objective of the research is to study and compare
response surface designs: Central composite designs (CCD), Box-
Behnken designs (BBD), Small composite designs (SCD), Hybrid
designs, and Uniform shell designs (USD) over sets of reduced models
when the design is in a spherical region for 3 and 4 design variables.
The two optimality criteria ( D and G ) are considered which larger
values imply a better design. The comparison of design optimality
criteria of the response surface designs across the full second order
model and sets of reduced models for 3 and 4 factors based on the
two criteria are presented.
Abstract: This experiment was performed with the purpose of
investigating effect of additional blend of probiotics Saccharomyces
cerevisiae and Lactobacillus acidophilus on plasma fatty acid profiles
particularly conjugated linoleic acid (CLA) in growing goats fed corn
silage, and selected the optimal levels of the probiotics for further study.
Twenty-four growing crossbred (Thai native x Anglo-Nubian) goats that
weighed (14.2 ± 2.3) kg, aged about 6 months, were purchased and
allocated to 4 treatments according to Randomized Complete Block
Design (RCBD) with 6 goats in each treatment. The blocks were made by
weight into heavy, medium, and light goats and each of the treatments
contained two goats from each of the blocks. In the mean time, ruminal
average pH unaffected, but the NH3-N and also plasma urea nitrogen
(p0.05) were raised, but propionic
proportion (p0.05) were reduced in
concurrent with raise of acetic proportion and resultantly C2:C3 ratio
(p>0.05). On plasma fatty acid profiles, total saturated fatty acids
(p>0.05) was increased, and contrasted with decrease of C15:0
(p0.05), and C18-C22 polyunsaturated fatty acids
(p
Abstract: Municipal solid waste (MSW) comprises of a wide
range of heterogeneous materials generated by individual, household
or organization and may include food waste, garden wastes, papers,
textiles, rubbers, plastics, glass, ceramics, metals, wood wastes,
construction wastes but it is not limited to the above mentioned
fractions. The most common Municipal Solid Waste pretreatment
method in use is thermal pretreatment (incineration) and Mechanical
Biological pretreatment. This paper presents an overview of these
two pretreatment methods describing their benefits and laboratory
scale reactors that simulate landfill conditions were constructed in
order to compare emissions in terms of biogas production and
leachate contamination between untreated Municipal Solid Waste and
Mechanical Biological Pretreated waste. The findings of this study
showed that Mechanical Biological pretreatment of waste reduces the
emission level of waste and the benefit over the landfilling of
untreated waste is significant.
Abstract: The current of professional bicycle pedal-s
manufacturing model mostly used casting, forging, die-casting
processing methods, so the paper used 7075 aluminum alloy which is
to produce the bicycle parts most commonly, and employs the
rigid-plastic finite element (FE) DEFORMTM 3D software to simulate
and to analyze the professional bicycle pedal design. First we use Solid
works 2010 3D graphics software to design the professional bicycle
pedal of the mold and appearance, then import finite element (FE)
DEFORMTM 3D software for analysis. The paper used rigid-plastic
model analytical methods, and assuming mode to be rigid body. A
series of simulation analyses in which the variables depend on
different temperature of forging billet, friction factors, forging speed,
mold temperature are reveal to effective stress, effective strain, damage
and die radial load distribution for forging bicycle pedal. The analysis
results hope to provide professional bicycle pedal forming mold
references to identified whether suit with the finite element results for
high-strength design suitability of aluminum alloy.
Abstract: The lack of any centralized infrastructure in mobile ad
hoc networks (MANET) is one of the greatest security concerns in
the deployment of wireless networks. Thus communication in
MANET functions properly only if the participating nodes cooperate
in routing without any malicious intention. However, some of the
nodes may be malicious in their behavior, by indulging in flooding
attacks on their neighbors. Some others may act malicious by
launching active security attacks like denial of service. This paper
addresses few related works done on trust evaluation and
establishment in ad hoc networks. Related works on flooding attack
prevention are reviewed. A new trust approach based on the extent of
friendship between the nodes is proposed which makes the nodes to
co-operate and prevent flooding attacks in an ad hoc environment.
The performance of the trust algorithm is tested in an ad hoc network
implementing the Ad hoc On-demand Distance Vector (AODV)
protocol.
Abstract: A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.
Abstract: We have developed an analytic model for the radial pn-junction in a nanowire (NW) core-shell structure utilizing as a new
building block in different semiconductor devices. The potential distribution through the p-n-junction is calculated and the analytical expressions are derived to compute the depletion region widths. We
show that the widths of space charge layers, surrounding the core, are
the functions of core radius, which is the manifestation of so called classical size effect. The relationship between the depletion layer width and the built-in potential in the asymptotes of infinitely large
core radius transforms to square-root dependence specific for conventional planar p-n-junctions. The explicit equation is derived to
compute the capacitance of radial p-n-junction. The current-voltage behavior is also carefully determined taking into account the “short
base" effects.
Abstract: This study describes the relationship between motivation factors and academic performance among distance education students enrolled in a postgraduate nursing course. Students (n=96) participated in a survey that assesses student's motivational orientations from a cognitive perspective using a selfadministered questionnaire based on Pintrich-s Motivation Strategies for Learning Questionnaire (MLSQ). Results showed students- motivational factors are highest on task value (6.44, 0.71); followed by intrinsic goal orientation (6.20, 0.76), control beliefs (6.02, 0.89); extrinsic goal orientation (5.85, 1.13); self-efficacy for learning and performance (5.62, 0.84), and finally, test anxiety (4.21, 1.37). Weak positive correlations were found between academic performance and intrinsic goal orientation (r=0.13), extrinsic goal orientation (r=0.04), task value (r=0.09), control beliefs (r=0.02), and self-efficacy (r=0.05), while there was weak negative correlation with test anxiety (r=-0.04). Conclusions from the study indicate the need to focus on improving tasks and targeting intrinsic goal orientations of students to courses since these were positively correlated with academic performance and downplay the use of tests since these were negatively correlated with academic performance.