Abstract: All the software engineering researches and best
industry practices aim at providing software products with high
degree of quality and functionality at low cost and less time. These
requirements are addressed by the Component Based Software
Engineering (CBSE) as well. CBSE, which deals with the software
construction by components’ assembly, is a revolutionary extension
of Software Engineering. CBSE must define and describe processes
to assure timely completion of high quality software systems that are
composed of a variety of pre built software components. Though
these features provide distinct and visible benefits in software design
and programming, they also raise some challenging problems. The
aim of this work is to summarize the pertinent issues and
considerations in CBSE to make an understanding in forms of
concepts and observations that may lead to development of newer
ways of dealing with the problems and challenges in CBSE.
Abstract: Microalgae Meyerella planktonica is a potential
biofuel source because it can grow in bulk in either autotrophic or
heterotrophic condition. However, the quantitative growth of this
algal type is still low as it tends to precipitates on the bottom.
Besides, the lipid concentration is still low when grown in
autotrophic condition. In contrast, heterotrophic condition can
enhance the lipid concentration. The combination of autotrophic
condition and agitation treatment was conducted to increase the
density of the culture. On the other hand, a heterotrophic condition
was set up to raise the lipid production. A two-stage experiment
was applied to increase the density at the first step and to increase
the lipid concentration in the next step. The autotrophic condition
resulted higher density but lower lipid concentration compared to
heterotrophic one. The agitation treatment produced higher density
in both autotrophic and heterotrophic conditions. The two-stage
experiment managed to enhance the density during the autotrophic
stage and the lipid concentration during the heterotrophic stage.
The highest yield was performed by using 0.4% v/v glycerol as a
carbon source (2.9±0.016 x 10^6 cells w/w) attained 7 days after the
heterotrophic stage began. The lipid concentration was stable
starting from day 7.
Abstract: Typically, virtual communities exhibit the well-known
phenomenon of participation inequality, which means that only a
small percentage of users is responsible of the majority of
contributions. However, the sustainability of the community requires
that the group of active users must be continuously nurtured with new
users that gain expertise through a participation process. This paper
analyzes the time evolution of Open Source Software (OSS)
communities, considering users that join/abandon the community
over time and several topological properties of the network when
modeled as a social network. More specifically, the paper analyzes
the role of those users rejoining the community and their influence in
the global characteristics of the network.
Abstract: Subspace channel estimation methods have been
studied widely, where the subspace of the covariance matrix is
decomposed to separate the signal subspace from noise subspace. The
decomposition is normally done by using either the eigenvalue
decomposition (EVD) or the singular value decomposition (SVD) of
the auto-correlation matrix (ACM). However, the subspace
decomposition process is computationally expensive. This paper
considers the estimation of the multipath slow frequency hopping
(FH) channel using noise space based method. In particular, an
efficient method is proposed to estimate the multipath time delays by
applying multiple signal classification (MUSIC) algorithm which is
based on the null space extracted by the rank revealing LU (RRLU)
factorization. As a result, precise information is provided by the
RRLU about the numerical null space and the rank, (i.e., important
tool in linear algebra). The simulation results demonstrate the
effectiveness of the proposed novel method by approximately
decreasing the computational complexity to the half as compared
with RRQR methods keeping the same performance.
Abstract: This paper provides a quantitative measure of the
time-varying multiunit neuronal spiking activity using an entropy
based approach. To verify the status embedded in the neuronal activity
of a population of neurons, the discrete wavelet transform (DWT) is
used to isolate the inherent spiking activity of MUA. Due to the
de-correlating property of DWT, the spiking activity would be
preserved while reducing the non-spiking component. By evaluating
the entropy of the wavelet coefficients of the de-noised MUA, a
multiresolution Shannon entropy (MRSE) of the MUA signal is
developed. The proposed entropy was tested in the analysis of both
simulated noisy MUA and actual MUA recorded from cortex in rodent
model. Simulation and experimental results demonstrate that the
dynamics of a population can be quantified by using the proposed
entropy.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: The mechanisms underlying the association between
obesity and asthma may be related to a decreased immunological
tolerance induced by a defective function of regulatory T cells
(Tregs). The aim of this study is to establish the potential link
between these diseases and CD4+, CD25+ FoxP3+ Tregs as well as T
helper cells (Ths) in children. This is a prospective case control
study. Obese (n:40), asthmatic (n:40), asthmatic obese (n:40) and
healthy children (n:40), who don't have any acute or chronic diseases,
were included in this study. Obese children were evaluated according
to WHO criteria. Asthmatic patients were chosen based on GINA
criteria. Parents were asked to fill up the questionnaire. Informed
consent forms were taken. Blood samples were marked with CD4+,
CD25+ and FoxP3+ in order to determine Tregs and Ths by flow
cytometric method. Statistical analyses were performed. p≤0.05 was
chosen as meaningful threshold. Tregs exhibiting anti-inflammatory
nature were significantly lower in obese (0,16%; p≤0,001), asthmatic
(0,25%; p≤0,01) and asthmatic obese (0,29%; p≤0,05) groups than
the control group (0,38%). Ths were counted higher in asthma group
than the control (p≤0,01) and obese (p≤0,001) groups. T cell
immunity plays important roles in obesity and asthma pathogeneses.
Decreased numbers of Tregs found in obese, asthmatic and asthmatic
obese children may help to elucidate some questions in
pathophysiology of these diseases. For HOMA-IR levels, any
significant difference was not noted between control and obese
groups, but statistically higher values were found for obese
asthmatics. The values obtained in all groups were found to be below
the critical cut off points. This finding has made the statistically
significant difference observed between Tregs of obese, asthmatic,
obese asthmatic and control groups much more valuable. These
findings will be useful in diagnosis and treatment of these disorders
and future studies are needed. The production and propagation of
Tregs may be promising in alternative asthma and obesity treatments.
Abstract: Background - The TrendCare Patient Dependency
System is currently used by a large number of maternity Services
across Australia, New Zealand and Singapore. In 2012, 2013 and
2014 validation studies were initiated in all three countries to validate
the acuity tools used for women in labour, and postnatal mothers and
babies. This paper will present the findings of the validation study.
Aim - The aim of this study was to; identify if the care hours
provided by the TrendCare acuity system was an accurate reflection
of the care required by women and babies; obtain evidence of
changes required to acuity indicators and/or category timings to
ensure the TrendCare acuity system remains reliable and valid across
a range of maternity care models in three countries.
Method - A non-experimental action research methodology was
used across maternity services in four District Health Boards in New
Zealand, a large tertiary and a large secondary maternity service in
Singapore and a large public maternity service in Australia.
Standardised data collection forms and timing devices were used to
collect midwife contact times, with women and babies included in the
study. Rejection processes excluded samples when care was not
completed/rationed, and contact timing forms were incomplete. The
variances between actual timed midwife/mother/baby contact and the
TrendCare acuity category times were identified and investigated.
Results - Thirty two (88.9%) of the 36 TrendCare acuity category
timings, fell within the variance tolerance levels when compared to
the actual timings recorded for midwifery care. Four (11.1%)
TrendCare categories provided less minutes of care than the actual
timings and exceeded the variance tolerance level. These were all
night shift category timings. Nine postnatal categories were not able
to be compared as the sample size for these categories was
statistically insignificant. 100% of labour ward TrendCare categories
matched actual timings for midwifery care, all falling within the
variance tolerance levels.
The actual time provided by core midwifery staff to assist lead
maternity carer (LMC) midwives in New Zealand labour wards
showed a significant deviation to previous studies. The findings of
the study demonstrated the need for additional time allocations in
TrendCare to accommodate an increased level of assistance given to
LMC midwives.
Conclusion - The results demonstrated the importance of regularly
validating the TrendCare category timings with actual timings of the
care hours provided. It was evident from the findings that variances
to models of care and length of stay in maternity units have increased
midwifery workloads on the night shift. The level of assistance
provided by the core labour ward staff to the LMC midwife has
increased substantially.
Outcomes - As a consequence of this study, changes were made to
the night duty TrendCare maternity categories, additional acuity
indicators were developed and times for assisting LMC midwives in
labour ward increased. The updated TrendCare version was delivered
to maternity services in 2014.
Abstract: Air-cooled Blast Furnace Slag Aggregate (BFSA) is
usually referred to as a material providing for unique properties of
concrete. On the other hand, negative influences are also presented in
many aspects. The freeze-thaw resistance of concrete is dependent on
many factors, including regional specifics and when a concrete mix is
specified it is still difficult to tell its exact freeze-thaw resistance due
to the different components affecting it. An important consideration
in working with BFSA is the granularity and whether slag is sorted or
not. The experimental part of the article represents a comparative
testing of concrete using both the sorted and unsorted BFSA through
the freeze-thaw resistance as an indicator of durability. Unsorted
BFSA is able to be successfully used for concretes as they are
specified for exposure class XF4 with providing that the type of
cement is precisely selected.
Abstract: This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.
Abstract: Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
Abstract: In medical investigations, uncertainty is a major
challenging problem in making decision for doctors/experts to
identify the diseases with a common set of symptoms and also has
been extensively increasing in medical diagnosis problems. The
theory of cross entropy for intuitionistic fuzzy sets (IFS) is an
effective approach in coping uncertainty in decision making for
medical diagnosis problem. The main focus of this paper is to
propose a new intuitionistic fuzzy cross entropy measure (IFCEM),
which aid in reducing the uncertainty and doctors/experts will take
their decision easily in context of patient’s disease. It is shown that
the proposed measure has some elegant properties, which
demonstrates its potency. Further, it is also exemplified in detail the
efficiency and utility of the proposed measure by using a real life
case study of diagnosis the disease in medical science.
Abstract: Significant quota of Municipal Electrical Energy
consumption is related to Decentralized Air Conditioning which is
mostly provided by evaporative coolers. So the aim is to optimize
design of air conditioners to increase their efficiencies. To achieve
this goal, results of practical standardized tests for 40 evaporative
coolers in different types collected and simultaneously results for
same coolers based on one of EER (Energy Efficiency Ratio)
modeling styles are figured out. By comparing experimental results
of different coolers standardized tests with modeling results,
preciseness of used model is assessed and after comparing gained
preciseness with international standards based on EER for cooling
capacity, aeration, and also electrical energy consumption, energy
label from A (most effective) to G (less effective) is classified; finally
needed methods to optimize energy consumption and coolers’
classification are provided.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: Incineration of municipal solid waste (MSW) is one of
the key scopes in the global clean energy strategy. A computational
fluid dynamics (CFD) model was established in order to reveal these
features of the combustion process in a fixed porous bed of MSW.
Transporting equations and process rate equations of the waste bed
were modeled and set up to describe the incineration process,
according to the local thermal conditions and waste property
characters. Gas phase turbulence was modeled using k-ε turbulent
model and the particle phase was modeled using the kinetic theory of
granular flow. The heterogeneous reaction rates were determined
using Arrhenius eddy dissipation and the Arrhenius-diffusion
reaction rates. The effects of primary air flow rate and temperature in
the burning process of simulated MSW are investigated
experimentally and numerically. The simulation results in bed are
accordant with experimental data well. The model provides detailed
information on burning processes in the fixed bed, which is otherwise
very difficult to obtain by conventional experimental techniques.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: In this paper, a direct power control (DPC)
strategies have been investigated in order to control a high
power AC/DC converter with time variable load. This converter
is composed of a three level three phase neutral point clamped
(NPC) converter as rectifier and an H-bridge four quadrant
current control converter. In the high power application,
controller not only must adjust the desire outputs but also
decrease the level of distortions which are injected to the network
from the converter. Regarding to this reason and nonlinearity
of the power electronic converter, the conventional controllers
cannot achieve appropriate responses. In this research, the
precise mathematical analysis has been employed to design the
appropriate controller in order to control the time variable
load. A DPC controller has been proposed and simulated using
Matlab/ Simulink. In order to verify the simulation result, a real
time simulator- OPAL-RT- has been employed. In this paper,
the dynamic response and stability of the high power NPC
with variable load has been investigated and compared with
conventional types using a real time simulator. The results proved
that the DPC controller is more stable and has more precise
outputs in comparison with conventional controller.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: In the present work, the dielectric properties of
Epoxy/MWCNT-muscovite HYBRID and MIXED composites based
on a ratio 30:70 were studied. The multi-wall carbon nanotubes
(MWCNT) were prepared using two methods: (a) MWCNTmuscovite
hybrids were synthesised by chemical vapour deposition
(CVD) and (b) physically mixing muscovite with MWCNT. The
effects of different preparation of the composites and filler loading
were evaluated. It was revealed that the dielectric constants of
HYBRID epoxy composites are slightly higher than MIXED epoxy
composites. It was also indicated that the dielectric constant increased
by increasing the MWCNT filler loading.