Abstract: Many organizations bring e-Learning to use as a tool
in their training and human development department. It is getting
more popular because it is easy to access to get knowledge all the
time and also it provides a rich content, which can develop the
employees’ skill efficiently. This study is focused on the factors that
affect using e-Learning efficiently, so it will make job satisfaction
increasing. The questionnaires were sent to employees in large
commercial banks, which use e-Learning located in Bangkok, the
results from multiple linear regression analysis showed that
employee’s characteristics, characteristics of e-Learning, learning and
growth have influence on job satisfaction.
Abstract: Many issues about the relationship between auditors in
auditing practices with its stakeholders often heard. It appears in
perspectives of bringing out the variety of phenomena affecting from
the audit practice of greed and not appreciating from the
independency of the audit profession and professional code of ethics.
It becomes a logical consequence in practicing of capitalism in
accounting. The main purpose of this article would like to uncover
the existing auditing practices in Indonesia, especially in Java that
associated with a strong influence of Javanese culture with reluctant
/”shy", politely, "legowo (gratefully accepted)", "ngemong"
(friendly), "not mentholo" (lenient), "tepo seliro" (tolerance),
"ngajeni" (respectful), "acquiescent" and also reveals its relationships
with Non Javanese culture in facing the conflict of interest in
practical of auditing world. The method used by interpretive
approach that emphasizes the role of language, interpret and
understand and see social reality as something other than a label,
name or concept. Global practices in auditing of each country have
particular cultures that affect the standard set by those regulatory
standards results the adaptation of IAS. The majority of parties in
Indonesia is dominated by Javanese racial regulators, so Java culture
is embedded in every audit practices and those conditions in Java
leads auditors in having similar behaviour, sometimes interfere with
standard Java code of conduct must be executed by an auditor.
Auditors who live in Java have the characters of Javanese culture that
is hard to avoid in the audit practice. However, practically, the
auditors still are relevant in their profession.
Abstract: The mechanics of rip currents are complex, involving
interactions between waves, currents, water levels and the bathymetry,
that present particular challenges for numerical models. Here,
the effects of a grid-spacing dependent horizontal mixing on the
wave-current interactions are studied. Near the shore, wave rays
diverge from channels towards bar crests because of refraction by
topography and currents, in a way that depends on the rip current
intensity which is itself modulated by the horizontal mixing. At
low resolution with the grid-spacing dependent horizontal mixing,
the wave motion is the same for both coupling modes because the
wave deviation by the currents is weak. In high resolution case,
however, classical results are found with the stabilizing effect of
the flow by feedback of waves on currents. Lastly, wave-current
interactions and the horizontal mixing strongly affect the intensity
of the three-dimensional rip velocity.
Abstract: Company managers are always looking for more and
more opportunities to succeed in today's fiercely competitive market.
To maintain your place among the successful companies on the
market today or to come up with a revolutionary business idea is
much more difficult than before. Each new or improved method, tool,
or approach that can improve the functioning of business processes or
even of the entire system is worth checking and verification. The use
of simulation in the design of manufacturing systems and their
management in practice is one of the ways without increased risk,
which makes it possible to find the optimal parameters of
manufacturing processes and systems. The paper presents an example
of use of simulation for solution of the bottleneck problem in the
concrete company.
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: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
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: The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
Abstract: Solenoid operated electromagnetic control valve
(ECV) playing an important role for car’s air conditioning control
system. ECV is used in external variable displacement swash plate
type compressor and controls the entire air conditioning system by
means of a pulse width modulation (PWM) input signal supplying
from an external source (controller). Complete form of ECV contains
number of internal features like valve body, core, valve guide,
plunger, guide pin, plunger spring, bellows etc. While designing the
ECV; dimensions of different internal items must meet the standard
requirements as it is quite challenging. In this research paper,
especially the dimensioning of ECV body and its three pressure ports
through which the air/refrigerant passes are considered. Here internal
leakage test analysis of ECV body is being carried out from its
discharge port (Pd) to crankcase port (Pc) when the guide valve is
placed inside it. The experiments have made both in ordinary and
digital system using different assumptions and thereafter compare the
results.
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: In this work, we study the behavior of introducing
atomic size vacancy in a graphene nanoribbon superlattice. Our
investigations are based on the density functional theory (DFT) with
the Local Density Approximation in Atomistix Toolkit (ATK). We
show that, in addition to its shape, the position of vacancy has a
major impact on the electrical properties of a graphene nanoribbon
superlattice. We show that the band gap of an armchair graphene
nanoribbon may be tuned by introducing an appropriate periodic
pattern of vacancies. The band gap changes in a zig-zag manner
similar to the variation of band gap of a graphene nanoribbon by
changing its width.
Abstract: Digital image correlation (DIC) is a contactless fullfield
displacement and strain reconstruction technique commonly
used in the field of experimental mechanics. Comparing with
physical measuring devices, such as strain gauges, which only
provide very restricted coverage and are expensive to deploy widely,
the DIC technique provides the result with full-field coverage and
relative high accuracy using an inexpensive and simple experimental
setup. It is very important to study the natural patterns effect on the
DIC technique because the preparation of the artificial patterns is
time consuming and hectic process. The objective of this research is
to study the effect of using images having natural pattern on the
performance of DIC. A systematical simulation method is used to
build simulated deformed images used in DIC. A parameter (subset
size) used in DIC can have an effect on the processing and accuracy
of DIC and even cause DIC to failure. Regarding to the picture
parameters (correlation coefficient), the higher similarity of two
subset can lead the DIC process to fail and make the result more
inaccurate. The pictures with good and bad quality for DIC methods
have been presented and more importantly, it is a systematic way to
evaluate the quality of the picture with natural patterns before they
install the measurement devices.
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: In this paper, model order reduction method is used
for approximation in linear and nonlinearity aspects in some
experimental data. This method can be used for obtaining offline
reduced model for approximation of experimental data and can
produce and follow the data and order of system and also it can
match to experimental data in some frequency ratios. In this study,
the method is compared in different experimental data and influence
of choosing of order of the model reduction for obtaining the best and
sufficient matching condition for following the data is investigated in
format of imaginary and reality part of the frequency response curve
and finally the effect and important parameter of number of order
reduction in nonlinear experimental data is explained further.
Abstract: Performance of different filtering approaches depends
on modeling of dynamical system and algorithm structure. For
modeling and smoothing the data the evaluation of posterior
distribution in different filtering approach should be chosen carefully.
In this paper different filtering approaches like filter KALMAN,
EKF, UKF, EKS and smoother RTS is simulated in some trajectory
tracking of path and accuracy and limitation of these approaches are
explained. Then probability of model with different filters is
compered and finally the effect of the noise variance to estimation is
described with simulations results.
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: 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.