Abstract: Conventional educational practices, do not offer all
the required skills for teachers to successfully survive in today’s
workplace. Due to poor professional training, a big gap exists across
the curriculum plan and the teacher practices in the classroom. As
such, raising the quality of teaching through ICT-enabled training and
professional development of teachers should be an urgent priority.
‘Mobile Learning’, in that vein, is an increasingly growing field of
educational research and practice across schools and work places. In
this paper, we propose a novel Mobile learning system that allows the
users to learn through an intelligent mobile learning in cooperatively
every-time and every-where. The system will reduce the training cost
and increase consistency, efficiency, and data reliability. To establish
that our system will display neither functional nor performance
failure, the evaluation strategy is based on formal observation of
users interacting with system followed by questionnaires and
structured interviews.
Abstract: Bacterial strains capable of degradation of malathion
from the domestic sewage were isolated by an enrichment culture
technique. Three bacterial strains were screened and identified as
Acinetobacter baumannii (AFA), Pseudomonas aeruginosa (PS1),
and Pseudomonas mendocina (PS2) based on morphological,
biochemical identification and 16S rRNA sequence analysis.
Acinetobacter baumannii AFA was the most efficient malathion
degrading bacterium, so used for further biodegradation study. AFA
was able to grow in mineral salt medium (MSM) supplemented with
malathion (100 mg/l) as a sole carbon source, and within 14 days,
84% of the initial dose was degraded by the isolate measured by high
performance liquid chromatography. Strain AFA could also degrade
other organophosphorus compounds including diazinon, chlorpyrifos
and fenitrothion. The effect of different culture conditions on the
degradation of malathion like inoculum density, other carbon or
nitrogen sources, temperature and shaking were examined.
Degradation of malathion and bacterial cell growth were accelerated
when culture media were supplemented with yeast extract, glucose
and citrate. The optimum conditions for malathion degradation by
strain AFA were; an inoculum density of 1.5x 10^12CFU/ml at 30°C
with shaking. A specific polymerase chain reaction primers were
designed manually using multiple sequence alignment of the
corresponding carboxylesterase enzymes of Acinetobacter species.
Sequencing result of amplified PCR product and phylogenetic
analysis showed low degree of homology with the other
carboxylesterase enzymes of Acinetobacter strains, so we suggested
that this enzyme is a novel esterase enzyme. Isolated bacterial strains
may have potential role for use in bioremediation of malathion
contaminated.
Abstract: This study examines several critical dimensions of eservice
quality overlooked in the existing literature and proposes a
model and instrument framework for measuring customer perceived
e-service quality in the banking sector. The initial design was derived
from a pool of instrument dimensions and their items from the
existing literature review by content analysis. Based on focused
group discussion, nine dimensions were extracted. An exploratory
factor analysis approach was applied to data from a survey of 323
respondents. The instrument has been designed specifically for the
banking sector. Research data was collected from bank customers
who use electronic banking in a developing economy. A nine-factor
instrument has been proposed to measure the e-service quality. The
instrument has been checked for reliability. The validity and sample
place limited the applicability of the instrument across economies and
service categories. Future research must be conducted to check the
validity. This instrument can help bankers in developing economies
like India to measure the e-service quality and make improvements.
The present study offers a systematic procedure that provides insights
on to the conceptual and empirical comprehension of customer
perceived e-service quality and its constituents.
Abstract: In medical imaging, segmentation of different areas of
human body like bones, organs, tissues, etc. is an important issue.
Image segmentation allows isolating the object of interest for further
processing that can lead for example to 3D model reconstruction of
whole organs. Difficulty of this procedure varies from trivial for
bones to quite difficult for organs like liver. The liver is being
considered as one of the most difficult human body organ to segment.
It is mainly for its complexity, shape versatility and proximity of
other organs and tissues. Due to this facts usually substantial user
effort has to be applied to obtain satisfactory results of the image
segmentation. Process of image segmentation then deteriorates from
automatic or semi-automatic to fairly manual one. In this paper,
overview of selected available software applications that can handle
semi-automatic image segmentation with further 3D volume
reconstruction of human liver is presented. The applications are being
evaluated based on the segmentation results of several consecutive
DICOM images covering the abdominal area of the human body.
Abstract: Fracture in hot precision forging of engine valves was
investigated in this paper. The entire valve forging procedure was
described and the possible cause of the fracture was proposed. Finite
Element simulation was conducted for the forging process, with
commercial Finite Element code DEFORMTM. The effects of
material properties, the effect of strain rate and temperature were
considered in the FE simulation. Two fracture criteria were discussed
and compared, based on the accuracy and reliability of the FE
simulation results. The selected criterion predicted the fracture
location and shows the trend of damage increasing with good
accuracy, which matches the experimental observation. Additional
modification of the punch shapes was proposed to further reduce the
tendency of fracture in forging. Finite Element comparison shows a
great potential of such application in the mass production.
Abstract: An attempt has been made in the present
communication to elucidate the efficacy of robust ANOVA methods
to analyse horticultural field experimental data in the presence of
outliers. Results obtained fortify the use of robust ANOVA methods
as there was substantiate reduction in error mean square, and hence
the probability of committing Type I error, as compared to the regular
approach.
Abstract: This research study is an exploration of the selfdirected
professional development of teachers who teach in public
schools in an era of democracy and educational change in South
Africa. Amidst an ever-changing educational system, the teachers in
this study position themselves as self-directed teacher-learners where
they adopt particular learning practices which enable change within
the broader discourses of public schooling. Life-story interviews
were used to enter into the private and public spaces of five teachers
which offer glimpses of how particular systems shaped their
identities, and how the meanings of self-directed teacher-learner
shaped their learning practices. Through the Multidimensional
Framework of Analysis and Interpretation the teachers’ stories were
analysed through three lenses: restorying the field texts - the self
through story; the teacher-learner in relation to social contexts, and
practices of self-directed learning. This study shows that as teacherlearners
learn for change through self-directed learning practices,
they develop their agency as transformative intellectuals, which is
necessary for the reworking of South African public schools.
Abstract: The study is a review of the literature concerning the
consequences of non-standard monetary policy, which are used by
central banks during unconventional periods, threatening banking
sector instability. In particular, the attention was paid to the effects of
non-standard monetary policy tools for financial markets. However,
the empirical evidence about their effects and real consequences for
financial markets is still not final. The main aim of the study is to
survey consequences of standard and non-standard monetary policy
instruments, implemented during the global financial crisis in the
United States, United Kingdom and euro area, with particular
attention to the results for the stabilization of global financial
markets. The study consists mainly of the empirical review,
indicating the impact of the implementation of these tools for
financial markets. The following research methods were used in the
study: literature studies, including domestic and foreign literature,
cause and effect analysis and statistical analysis.
Abstract: In this paper a real-time obstacle avoidance approach
for both autonomous and non-autonomous dynamical systems (DS) is
presented. In this approach the original dynamics of the controller
which allow us to determine safety margin can be modulated.
Different common types of DS increase the robot’s reactiveness in
the face of uncertainty in the localization of the obstacle especially
when robot moves very fast in changeable complex environments.
The method is validated by simulation and influence of different
autonomous and non-autonomous DS such as important
characteristics of limit cycles and unstable DS. Furthermore, the
position of different obstacles in complex environment is explained.
Finally, the verification of avoidance trajectories is described through
different parameters such as safety factor.
Abstract: In this paper, Bayesian online inference in models of
data series are constructed by change-points algorithm, which
separated the observed time series into independent series and study
the change and variation of the regime of the data with related
statistical characteristics. variation of statistical characteristics of time
series data often represent separated phenomena in the some
dynamical system, like a change in state of brain dynamical reflected
in EEG signal data measurement or a change in important regime of
data in many dynamical system. In this paper, prediction algorithm
for studying change point location in some time series data is
simulated. It is verified that pattern of proposed distribution of data
has important factor on simpler and smother fluctuation of hazard
rate parameter and also for better identification of change point
locations. Finally, the conditions of how the time series distribution
effect on factors in this approach are explained and validated with
different time series databases for some dynamical system.
Abstract: In this paper, we considered and applied parametric
modeling for some experimental data of dynamical system. In this
study, we investigated the different distribution of output
measurement from some dynamical systems. Also, with variance
processing in experimental data we obtained the region of
nonlinearity in experimental data and then identification of output
section is applied in different situation and data distribution. Finally,
the effect of the spanning the measurement such as variance to
identification and limitation of this approach is explained.
Abstract: Background and aim: It has not been well studied
whether fentanyl-thiopental (FT) is effective and safe for PSA in
orthopedic procedures in Emergency Department (ED). The aim of
this trial was to evaluate the effectiveness of intravenous FT versus
fentanyl-midazolam (FM) in patients who suffered from shoulder
dislocation or distal radial fracture-dislocation.
Methods: In this randomized double-blinded study, Seventy-six
eligible patients were entered the study and randomly received
intravenous FT or FM. The success rate, onset of action and recovery
time, pain score, physicians’ satisfaction and adverse events were
assessed and recorded by treating emergency physicians. The
statistical analysis was intention to treat.
Results: The success rate after administrating loading dose in FT
group was significantly higher than FM group (71.7% vs. 48.9%,
p=0.04); however, the ultimate unsuccessful rate after 3 doses of
drugs in the FT group was higher than the FM group (3 to 1) but it
did not reach to significant level (p=0.61). Despite near equal onset
of action time in two study group (P=0.464), the recovery period in
patients receiving FT was markedly shorter than FM group
(P
Abstract: This paper presents an evolutionary algorithm for
solving multi-objective optimization problems-based artificial neural
network (ANN). The multi-objective evolutionary algorithm used in
this study is genetic algorithm while ANN used is radial basis
function network (RBFN). The proposed algorithm named memetic
elitist Pareto non-dominated sorting genetic algorithm-based RBFN
(MEPGAN). The proposed algorithm is implemented on medical
diseases problems. The experimental results indicate that the
proposed algorithm is viable, and provides an effective means to
design multi-objective RBFNs with good generalization capability
and compact network structure. This study shows that MEPGAN
generates RBFNs coming with an appropriate balance between
accuracy and simplicity, comparing to the other algorithms found in
literature.
Abstract: At certain depths during large diameter displacement
pile driving, rebound well over 0.25 inches was experienced,
followed by a small permanent-set during each hammer blow. High
pile rebound (HPR) soils may stop the pile driving and results in a
limited pile capacity. In some cases, rebound leads to pile damage,
delaying the construction project, and the requiring foundations
redesign. HPR was evaluated at seven Florida sites, during driving of
square precast, prestressed concrete piles driven into saturated, fine
silty to clayey sands and sandy clays. Pile Driving Analyzer (PDA)
deflection versus time data recorded during installation, was used to
develop correlations between cone penetrometer (CPT) pore-water
pressures, pile displacements and rebound. At five sites where piles
experienced excessive HPR with minimal set, the pore pressure
yielded very high positive values of greater than 20 tsf. However, at
the site where the pile rebounded, followed by an acceptable
permanent-set, the measured pore pressure ranged between 5 and 20
tsf. The pore pressure exhibited values of less than 5 tsf at the site
where no rebound was noticed. In summary, direct correlations
between CPTu pore pressure and rebound were produced, allowing
identification of soils that produce HPR.
Abstract: In Brazil, neonatal mortality rate is considered
incompatible with the country development conditions, and has been
a Public Health concern. Reduction in infant mortality rates has also
been part of the Millennium Development Goals, a commitment
made by countries, members of the Organization of United Nations
(OUN), including Brazil. Fetal mortality rate is considered a highly
sensitive indicator of health care quality. Suitable actions, such as
good quality and access to health services may contribute positively
towards reduction in these fetal and neonatal rates. With appropriate
antenatal follow-up and health care during gestation and delivery,
some death causes could be reduced or even prevented by means of
early diagnosis and intervention, as well as changes in risk factors
and interventions. Objectives: To study the quality of maternal and
infant health care based on fetal and neonatal mortality, as well as the
possible actions to prevent those deaths in Botucatu (Brazil).
Methods: Classification of prevention according to the International
Classification of Diseases and the modified Wigglesworth´s
classification. In order to evaluate adequacy, indicators of quality of
antenatal and delivery care were established by the authors. Results:
Considering fetal deaths, 56.7% of them occurred before delivery,
which reveals possible shortcomings in antenatal care, and 38.2% of
them were a result of intra- labor changes, which could be prevented
or reduced by adequate obstetric management. These findings were
different from those in the group of early neonatal deaths which were
also studied. Adequacy of health services showed that antenatal and
childbirth care was appropriate for 24% and 33.3% of pregnant
women, respectively, which corroborates the results of prevention.
These results revealed that shortcomings in obstetric and antenatal
care could be the causes of deaths in the study. Early and late
neonatal deaths have similar characteristics: 76% could be prevented
or reduced mainly by adequate newborn care (52.9%) and adequate
health care for gestational women (11.7%). When adequacy of care
was evaluated, childbirth and newborn care was adequate in 25.8%
and antenatal care was adequate in 16.1%. In conclusion, direct
relationship was found between adequacy and quality of care
rendered to pregnant women and newborns, and fetal and infant
mortality. Moreover, our findings highlight that deaths could be
prevented by an adequate obstetric and neonatal management.
Abstract: Text mining techniques are generally applied for
classifying the text, finding fuzzy relations and structures in data
sets. This research provides plenty text mining capabilities. One
common application is text classification and event extraction,
which encompass deducing specific knowledge concerning incidents
referred to in texts. The main contribution of this paper is the
clarification of a concept graph generation mechanism, which is based
on a text classification and optimal fuzzy relationship extraction.
Furthermore, the work presented in this paper explains the application
of fuzzy relationship extraction and branch and bound (BB) method
to simplify the texts.
Abstract: In and around Erode District, it is estimated that more
than 1250 chemical and allied textile processing fabric industries are
affected, partially closed and shut off for various reasons such as poor
management, poor supplier performance, lack of planning for
productivity, fluctuation of output, poor investment, waste analysis,
labor problems, capital/labor ratio, accumulation of stocks, poor
maintenance of resources, deficiencies in the quality of fabric, low
capacity utilization, age of plant and equipment, high investment and
input but low throughput, poor research and development, lack of
energy, workers’ fear of loss of jobs, work force mix and work ethic.
The main objective of this work is to analyze the existing conditions
in textile fabric sector, validate the break even of Total Productivity
(TP), analyze, design and implement fuzzy sets and mathematical
programming for improvement of productivity and quality
dimensions in the fabric processing industry. It needs to be
compatible with the reality of textile and fabric processing industries.
The highly risk events from productivity and quality dimension were
found by fuzzy systems and results are wrapped up among the textile
fabric processing industry.
Abstract: Leukaemia is a blood cancer disease that contributes
to the increment of mortality rate in Malaysia each year. There are
two main categories for leukaemia, which are acute and chronic
leukaemia. The production and development of acute leukaemia cells
occurs rapidly and uncontrollable. Therefore, if the identification of
acute leukaemia cells could be done fast and effectively, proper
treatment and medicine could be delivered. Due to the requirement of
prompt and accurate diagnosis of leukaemia, the current study has
proposed unsupervised pixel segmentation based on clustering
algorithm in order to obtain a fully segmented abnormal white blood
cell (blast) in acute leukaemia image. In order to obtain the
segmented blast, the current study proposed three clustering
algorithms which are k-means, fuzzy c-means and moving k-means
algorithms have been applied on the saturation component image.
Then, median filter and seeded region growing area extraction
algorithms have been applied, to smooth the region of segmented
blast and to remove the large unwanted regions from the image,
respectively. Comparisons among the three clustering algorithms are
made in order to measure the performance of each clustering
algorithm on segmenting the blast area. Based on the good sensitivity
value that has been obtained, the results indicate that moving kmeans
clustering algorithm has successfully produced the fully
segmented blast region in acute leukaemia image. Hence, indicating
that the resultant images could be helpful to haematologists for
further analysis of acute leukaemia.
Abstract: Prior to quantifying the variables of the information
model for using school terminology in Croatia's region of Dalmatia
from 1884 to 2014, the most relevant model variables had to be
determined: historical circumstances, standard of living, education
system, linguistic situation, and media. The research findings show
that there was no significant transfer of the 1884 school terms into
1949 usage; likewise, the 1949 school terms were not widely used in
2014. On the other hand, the research revealed that the meaning of
school terms changed over the decades. The quantification of the
variables will serve as the groundwork for creating an information
model for using school terminology in Dalmatia from 1884 to 2014
and for defining direct growth rates in further research.
Abstract: Motion Tracking and Stereo Vision are complicated,
albeit well-understood problems in computer vision. Existing
softwares that combine the two approaches to perform stereo motion
tracking typically employ complicated and computationally expensive
procedures. The purpose of this study is to create a simple and
effective solution capable of combining the two approaches. The
study aims to explore a strategy to combine the two techniques
of two-dimensional motion tracking using Kalman Filter; and depth
detection of object using Stereo Vision. In conventional approaches
objects in the scene of interest are observed using a single camera.
However for Stereo Motion Tracking; the scene of interest is
observed using video feeds from two calibrated cameras. Using two
simultaneous measurements from the two cameras a calculation for
the depth of the object from the plane containing the cameras is made.
The approach attempts to capture the entire three-dimensional spatial
information of each object at the scene and represent it through a
software estimator object. In discrete intervals, the estimator tracks
object motion in the plane parallel to plane containing cameras and
updates the perpendicular distance value of the object from the plane
containing the cameras as depth. The ability to efficiently track
the motion of objects in three-dimensional space using a simplified
approach could prove to be an indispensable tool in a variety of
surveillance scenarios. The approach may find application from high
security surveillance scenes such as premises of bank vaults, prisons
or other detention facilities; to low cost applications in supermarkets
and car parking lots.