Abstract: The purpose of this study was to explore the
relationship between Burnout, Negative Affectivity, and
Organizational Citizenship Behavior (OCB) for social service
workers at two agencies serving homeless populations. Thirty two
subjects completed surveys. Significant correlations between major
variables and subscales were found.
Abstract: Automatic segmentation of skin lesions is the first step
towards development of a computer-aided diagnosis of melanoma.
Although numerous segmentation methods have been developed,
few studies have focused on determining the most discriminative
and effective color space for melanoma application. This paper
proposes a novel automatic segmentation algorithm using color space
analysis and clustering-based histogram thresholding, which is able to
determine the optimal color channel for segmentation of skin lesions.
To demonstrate the validity of the algorithm, it is tested on a set of 30
high resolution dermoscopy images and a comprehensive evaluation
of the results is provided, where borders manually drawn by four
dermatologists, are compared to automated borders detected by the
proposed algorithm. The evaluation is carried out by applying three
previously used metrics of accuracy, sensitivity, and specificity and
a new metric of similarity. Through ROC analysis and ranking the
metrics, it is shown that the best results are obtained with the X and
XoYoR color channels which results in an accuracy of approximately
97%. The proposed method is also compared with two state-ofthe-
art skin lesion segmentation methods, which demonstrates the
effectiveness and superiority of the proposed segmentation method.
Abstract: The paper discusses a computationally efficient
method for the design of prototype filters required for the
implementation of an M-band cosine modulated filter bank. The
prototype filter is formulated as an optimum interpolated FIR filter.
The optimum interpolation factor requiring minimum number of
multipliers is used. The model filter as well as the image suppressor
will be designed using the Kaiser window. The method will seek to
optimize a single parameter namely cutoff frequency to minimize the
distortion in the overlapping passband.
Abstract: This paper deals with the localization of the wideband sources. We develop a new approach for estimating the wide band sources parameters. This method is based on the high order statistics of the recorded data in order to eliminate the Gaussian components from the signals received on the various hydrophones.In fact the noise of sea bottom is regarded as being Gaussian. Thanks to the coherent signal subspace algorithm based on the cumulant matrix of the received data instead of the cross-spectral matrix the wideband correlated sources are perfectly located in the very noisy environment. We demonstrate the performance of the proposed algorithm on the real data recorded during an underwater acoustics experiments.
Abstract: This paper presents a useful sub-pixel image
registration method using line segments and a sub-pixel edge detector.
In this approach, straight line segments are first extracted from gray
images at the pixel level before applying the sub-pixel edge detector.
Next, all sub-pixel line edges are mapped onto the orientation-distance
parameter space to solve for line correspondence between images.
Finally, the registration parameters with sub-pixel accuracy are
analytically solved via two linear least-square problems. The present
approach can be applied to various fields where fast registration with
sub-pixel accuracy is required. To illustrate, the present approach is
applied to the inspection of printed circuits on a flat panel. Numerical
example shows that the present approach is effective and accurate
when target images contain a sufficient number of line segments,
which is true in many industrial problems.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: Post growth annealing of solution grown ZnO
nanowire array is performed under controlled oxygen ambience. The
role of annealing over surface defects and their consequence on
dark/photo-conductivity and photosensitivity of nanowire array is
investigated. Surface defect properties are explored using various
measurement tools such as contact angle, photoluminescence, Raman
spectroscopy and XPS measurements. The contact angle of the NW
films reduces due to oxygen annealing and nanowire film surface
changes from hydrophobic (96°) to hydrophilic (16°). Raman and
XPS spectroscopy reveal that oxygen annealing improves the crystal
quality of the nanowire films. The defect band emission intensity
(relative to band edge emission, ID/IUV) reduces from 1.3 to 0.2 after
annealing at 600 °C at 10 SCCM flow of oxygen. An order
enhancement in dark conductivity is observed in O2 annealed
samples, while photoconductivity is found to be slightly reduced due
to lower concentration of surface related oxygen defects.
Abstract: Moisture is an important consideration in many
aspects ranging from irrigation, soil chemistry, golf course, corrosion
and erosion, road conditions, weather predictions, livestock feed
moisture levels, water seepage etc. Vegetation and crops always
depend more on the moisture available at the root level than on
precipitation occurrence. In this paper, design of an instrument is
discussed which tells about the variation in the moisture contents of
soil. This is done by measuring the amount of water content in soil by
finding the variation in capacitance of soil with the help of a
capacitive sensor. The greatest advantage of soil moisture sensor is
reduced water consumption. The sensor is also be used to set lower
and upper threshold to maintain optimum soil moisture saturation and
minimize water wilting, contributes to deeper plant root growth
,reduced soil run off /leaching and less favorable condition for insects
and fungal diseases. Capacitance method is preferred because, it
provides absolute amount of water content and also measures water
content at any depth.
Abstract: In this paper, we probe into the traffic assignment problem by the chromosome-learning-based path finding method in simulation, which is to model the driver' behavior in the with-in-a-day process. By simply making a combination and a change of the traffic route chromosomes, the driver at the intersection chooses his next route. The various crossover and mutation rules are proposed with extensive examples.
Abstract: Shear-layer instabilities of a pulsed stack-issued
transverse jet were studied experimentally in a wind tunnel. Jet
pulsations were induced by means of acoustic excitation. Streak
pictures of the smoke-flow patterns illuminated by the laser-light sheet
in the median plane were recorded with a high-speed digital camera.
Instantaneous velocities of the shear-layer instabilities in the flow were
digitized by a hot-wire anemometer. By analyzing the streak pictures
of the smoke-flow visualization, three characteristic flow modes,
synchronized flapping jet, transition, and synchronized shear-layer
vortices, are identified in the shear layer of the pulsed stack-issued
transverse jet at various excitation Strouhal numbers. The shear-layer
instabilities of the pulsed stack-issued transverse jet are synchronized
by acoustic excitation except for transition mode. In transition flow
mode, the shear-layer vortices would exhibit a frequency that would be
twice as great as the acoustic excitation frequency.
Abstract: Compacted clay liners (CCLs) are the main materials
used in waste disposal landfills due to their low permeability. In this
study, the effect on the shear resistant of clays with inorganic salt
solutions as permeate fluid was experimentally investigated. For this
purpose, NaCl inorganic salt solution at concentrations of 2, 5, 10%
and deionized water were used. Laboratory direct shear and Vane
shear tests were conducted on three compacted clays with low,
medium and high plasticity. Results indicated that the solutions type
and its concentration affect the shear properties of the mixture. In the
light of this study, the influence magnitude of these inorganic salts in
varies concentrations in different clays were determined and more
suitable compacted clay with the compare of plasticity were found.
Abstract: This paper is a survey of current component-based
software technologies and the description of promotion and
inhibition factors in CBSE. The features that software components
inherit are also discussed. Quality Assurance issues in componentbased
software are also catered to. The feat research on the quality
model of component based system starts with the study of what the
components are, CBSE, its development life cycle and the pro &
cons of CBSE. Various attributes are studied and compared keeping
in view the study of various existing models for general systems and
CBS. When illustrating the quality of a software component an apt
set of quality attributes for the description of the system (or
components) should be selected. Finally, the research issues that can
be extended are tabularized.
Abstract: In this study, the numerical solution of unsteady flow
between two concentric rotating spheres with suction and blowing at
their boundaries is presented. The spheres are rotating about a
common axis of rotation while their angular velocities are constant.
The Navier-Stokes equations are solved by employing the finite
difference method and implicit scheme. The resulting flow patterns
are presented for various values of the flow parameters including
rotational Reynolds number Re , and a blowing/suction Reynolds
number Rew . Viscous torques at the inner and the outer spheres are
calculated, too. It is seen that increasing the amount of suction and
blowing decrease the size of eddies generated in the annulus.
Abstract: In research on natural ventilation, and passive cooling
with forced convection, is essential to know how heat flows in a solid
object and the pattern of temperature distribution on their surfaces,
and eventually how air flows through and convects heat from the
surfaces of steel under roof. This paper presents some results from
running the computational fluid dynamic program (CFD) by
comparison between natural ventilation and forced convection within
roof attic that is received directly from solar radiation. The CFD
program for modeling air flow inside roof attic has been modified to
allow as two cases. First case, the analysis under natural ventilation,
is closed area in roof attic and second case, the analysis under forced
convection, is opened area in roof attic. These extend of all cases to
available predictions of variations such as temperature, pressure, and
mass flow rate distributions in each case within roof attic. The
comparison shows that this CFD program is an effective model for
predicting air flow of temperature and heat transfer coefficient
distribution within roof attic. The result shows that forced convection
can help to reduce heat transfer through roof attic and an around area
of steel core has temperature inner zone lower than natural
ventilation type. The different temperature on the steel core of roof
attic of two cases was 10-15 oK.
Abstract: Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.
Abstract: In this paper, we present a novel approach to location
system under indoor environment. The key idea of our work is
accurate distance estimation with cricket-based location system using
A* algorithm. We also use magnetic sensor for detecting obstacles in
indoor environment. Finally, we suggest how this system can be used
in various applications such as asset tracking and monitoring.
Abstract: Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.
Abstract: Web usage mining algorithms have been widely
utilized for modeling user web navigation behavior. In this study we
advance a model for mining of user-s navigation pattern. The model
makes user model based on expectation-maximization (EM)
algorithm.An EM algorithm is used in statistics for finding maximum
likelihood estimates of parameters in probabilistic models, where the
model depends on unobserved latent variables. The experimental
results represent that by decreasing the number of clusters, the log
likelihood converges toward lower values and probability of the
largest cluster will be decreased while the number of the clusters
increases in each treatment.
Abstract: Detection of incipient abnormal events is important to
improve safety and reliability of machine operations and reduce losses
caused by failures. Improper set-ups or aligning of parts often leads to
severe problems in many machines. The construction of prediction
models for predicting faulty conditions is quite essential in making
decisions on when to perform machine maintenance. This paper
presents a multivariate calibration monitoring approach based on the
statistical analysis of machine measurement data. The calibration
model is used to predict two faulty conditions from historical reference
data. This approach utilizes genetic algorithms (GA) based variable
selection, and we evaluate the predictive performance of several
prediction methods using real data. The results shows that the
calibration model based on supervised probabilistic principal
component analysis (SPPCA) yielded best performance in this work.
By adopting a proper variable selection scheme in calibration models,
the prediction performance can be improved by excluding
non-informative variables from their model building steps.
Abstract: This article proposes an Ant Colony Optimization
(ACO) metaheuristic to minimize total makespan for scheduling a set
of jobs and assign workers for uniformly related parallel machines.
An algorithm based on ACO has been developed and coded on a
computer program Matlab®, to solve this problem. The paper
explains various steps to apply Ant Colony approach to the problem
of minimizing makespan for the worker assignment & jobs
scheduling problem in a parallel machine model and is aimed at
evaluating the strength of ACO as compared to other conventional
approaches. One data set containing 100 problems (12 Jobs, 03
machines and 10 workers) which is available on internet, has been
taken and solved through this ACO algorithm. The results of our
ACO based algorithm has shown drastically improved results,
especially, in terms of negligible computational effort of CPU, to
reach the optimal solution. In our case, the time taken to solve all 100
problems is even lesser than the average time taken to solve one
problem in the data set by other conventional approaches like GA
algorithm and SPT-A/LMC heuristics.