Abstract: In the present study, the oleaginous fungus
Mortierella alpina CBS 754.68 was screened for arachidonic
acidproduction using inexpensive agricultural by-products as
substrate. Four oilcakes were analysed to choose the best substrate
among them. Sunflower oilcake was the most effective substrate for
ARA production followed by soybean, colza and olive oilcakes. In
the next step, seven variables including substrate particle size,
moisture content, time, temperature, yeast extract supply, glucose
supply and glutamate supply were surveyed and effective variables
for ARA production were determined using a Plackett-Burman
screening design. Analysis results showed that time (12 days),
substrate particle size (1-1.4 mm) and temperature (20ºC) were the
most effective variables for the highest level of ARA production
respectively.
Abstract: This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
Abstract: Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.
Abstract: The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.
Abstract: For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.
Abstract: It is important to retain customer satisfaction in
information technology services. When a service failure occurs,
companies need to take service recovery action to recover their
customer satisfaction. Although companies cannot avoid all problems
and complaints, they should try to make up. Therefore, service failure
and service recovery have become an important and challenging issue
for companies. In this paper, the literature and the problems in the
information technology services were reviewed. An integrated model
of profit driven for the service failure and service recovery was
established in view of the benefit of customer and enterprise.
Moreover, the interaction between service failure and service recovery
strategy was studied, the result of which verified the matching
principles of the service recovery strategy and the type of service
failure. In addition, the relationship between the cost of service
recovery and customer-s cumulative value of service after recovery
was analyzed with the model. The result attributes to managers in
deciding on appropriate resource allocations for recovery strategies.
Abstract: Riprap is mostly used to prevent erosion by flows
down the steep slopes in river engineering. A total of 53 stability tests
performed on angular riprap with a median stone size ranging from
15 to 278 mm and slope ranging from 1 to 40% are used in this study.
The existing equations for the prediction of medium size of angular
stones are checked for their accuracy using the available data.
Predictions of median size using these equations are not satisfactory
and results show deviation by more than ±20% from the observed
values. A multivariable power regression analysis is performed to
propose a new equation relating the median size with unit discharge,
bed slope, riprap thickness and coefficient of uniformity. The
proposed relationship satisfactorily predicts the median angular stone
size with ±20% error. Further, the required size of the rounded stone
is more than the angular stone for the same unit discharge and the
ratio increases with unit discharge and also with embankment slope
of the riprap.
Abstract: In this paper, zigbee communication based wireless energy surveillance system is presented. The proposed system consists of multiple energy surveillance devices and an energy surveillance monitor. Each different standby power-off value of electric device is set automatically by using learning function of energy surveillance device. Thus adaptive standby power-off function provides user convenience and it maximizes the energy savings. Also, power consumption monitoring function is helpful to reduce inefficient energy consumption in home. The zigbee throughput simulator is designed to evaluate minimum transmission power and maximum allowable information quantity in the proposed system. The test result of prototype has been satisfied all the requirements. The proposed system has confirmed that can be used as an intelligent energy surveillance system for energy savings in home or office.
Abstract: This paper presents the generation of bipolar square
wave pulses with characteristics that are suitable for liquid food
sterilization using a Cascaded H-bridge Multilevel Inverter (CHMI).
Bipolar square waves pulses have been reported as stable for a
longer time during the sterilization process with minimum heat
emission and increased efficiency. The CHMI allows the system to
produce bipolar square wave pulses and yielding high output voltage
without using a transformer while fulfilling the pulse requirements
for effective liquid food sterilization. This in turn can reduce power
consumption and cost of the overall liquid food sterilization system.
The simulation results have shown that pulses with peak output
voltage of 2.4 kV, pulse width of between 1 2s and 1 ms at
frequencies of 50 Hz and 100 Hz can be generated by a 7-level
CHMI. Results from the experimental set-up based on a 5-level
CHMI has indicated the potential of the proposed circuit in
producing bipolar square wave output pulses with peak values that
depends on the DC source level supplied to the CHMI modules,
pulse width of between 12.5 2s and 1 ms at frequencies of 50 Hz
and 100 Hz.
Abstract: Recently, much research has been conducted for
security for wireless sensor networks and ubiquitous computing.
Security issues such as authentication and data integrity are major
requirements to construct sensor network systems. Advanced
Encryption Standard (AES) is considered as one of candidate
algorithms for data encryption in wireless sensor networks. In this
paper, we will present the hardware architecture to implement low
power AES crypto module. Our low power AES crypto module has
optimized architecture of data encryption unit and key schedule unit
which could be applicable to wireless sensor networks. We also details
low power design methods used to design our low power AES crypto
module.
Abstract: Tuberculosis (TB) is a bacterial infectious disease caused by the obligate human pathogen, Mycobacterium tuberculosis. Multidrug-resistant tuberculosis (MDR-TB) is a global reality that threatens tuberculosis control. Resistance to antibiotic Rifampicin, occurs in 95% of cases through nucleotide substitutions in an 81-bp core region of the rpoB i.e; beta subunit of DNA dependant RNA polymerase. In this paper, we studied the Rifampicin-rpoB receptor interactions In silico. First, homology modeling was performed to obtain the three dimensional structure of Mycobacterium rpoB. Sixty analogs of Rifampicin were prepared using Marvin sketch software. Both original Rifampicin and the analogs were docked with rpoB and energy values were obtained. Out of sixty analogs, 43 analogs had lesser energy values than conventional Rifampicin and hence are predicted to have greater binding affinity to rpoB. Thus, this study offers a route for the development of Rifampicin analogs against multi drug resistant Mycobacterium rpoB.
Abstract: Purpose:This paper aims to gain insights to the influential factors of ERM adoptions by public listed firms in Malaysia. Findings:The two factors of financial leverage and auditor type were found to be significant influential factors for ERM adoption. In other words the findings indicated that firms with higher financial leverage and with a Big Four auditor are more likely to have a form of ERM framework in place. Originality/Value:Since there are relatively few studies conducted in this area and specially in developing economies like Malaysia, this study will broaden the scope of literature by providing novel empirical evidence.
Abstract: Since the last two decades, container transportation
system has been faced under increasing development. This fact
shows the importance of container transportation system as a key role
of container terminals to link between sea and land. Therefore, there
is a continuous need for the optimal use of equipment and facilities in
the ports. Regarding the complex structure of container ports, this
paper presents a simulation model that compares tow storage
strategies for storing containers in the yard. For this purpose, we
considered loading and unloading norm as an important criterion to
evaluate the performance of Shahid Rajaee container port. By
analysing the results of the model, it will be shown that using
marshalling yard policy instead of current storage system has a
significant effect on the performance level of the port and can
increase the loading and unloading norm up to 14%.
Abstract: Numerous facts evidence the increasing religiosity of
the population and the intensification of religious movements in
various countries in the last decade of the 20th century. The number
of international religious institutions and foundations; religious
movements; parties and sects operating worldwide is increasing as
well. Some ethnic and inter-state conflicts are obviously of a
religious origin. All of this make a number of analysts to conclude
that the religious factor is becoming an important part of international
life, including the formation and activities of terrorist organizations.
Most of all is said and written about Islam, the second, after
Christianity, world religions professed according to various estimates
by 1.5 bln. individuals in 127 countries.
Abstract: The Minimum Vertex Cover (MVC) problem is a classic
graph optimization NP - complete problem. In this paper a competent
algorithm, called Vertex Support Algorithm (VSA), is designed to
find the smallest vertex cover of a graph. The VSA is tested on a
large number of random graphs and DIMACS benchmark graphs.
Comparative study of this algorithm with the other existing methods
has been carried out. Extensive simulation results show that the VSA
can yield better solutions than other existing algorithms found in the
literature for solving the minimum vertex cover problem.
Abstract: In this research, the flow pattern influence on
performance of a micro PEMFC was investigated
experimentally. The investigation focused on the impacts of
bend angels and rib/channel dimensions of serpentine flow
channel pattern on the performance and investigated how they
improve the performance. The fuel cell employed for these
experiments was a micro single PEMFC with a membrane of
1.44 cm2 Nafion NRE-212. The results show that 60° and 120°
bend angles can provide the better performances at 20 and 40
sccm inlet flow rates comparing to that the conventional design.
Additionally, wider channel with narrower rib spacing gives
better performance. These results may be applied to develop
universal heuristics for the design of flow pattern of micro
PEMFC.
Abstract: The rate of nitrate adsorption by a nitrate selective ion
exchange resin was investigated in a well-stirred batch experiments.
The kinetic experimental data were simulated with diffusion models including external mass transfer, particle diffusion and chemical
adsorption. Particle pore volume diffusion and particle surface diffusion were taken into consideration separately and simultaneously
in the modeling. The model equations were solved numerically using the Crank-Nicholson scheme. An optimization technique was
employed to optimize the model parameters. All nitrate concentration
decay data were well described with the all diffusion models. The
results indicated that the kinetic process is initially controlled by external mass transfer and then by particle diffusion. The external
mass transfer coefficient and the coefficients of pore volume diffusion and surface diffusion in all experiments were close to each
other with the average value of 8.3×10-3 cm/S for external mass
transfer coefficient. In addition, the models are more sensitive to the
mass transfer coefficient in comparison with particle diffusion. Moreover, it seems that surface diffusion is the dominant particle
diffusion in comparison with pore volume diffusion.
Abstract: Mobile payments have been deployed by businesses for more than a decade. Customers use mobile payments if they trust in this relatively new payment method, have a belief and confidence in, as well as reliance on its services and applications. Despite its potential, the current literature shows that there is lack of customer trust in B2C mobile payments, and a lack of studies that determine the factors that influence their trust in these payments; which make these factors yet to be understood, especially in the Middle East region. Thus, this study aims to explore the factors that influence customer trust in mobile payments. The empirical data for this explorative study was collected by establishing four focus group sessions in the UAE. The results indicate that the explored significant factors can be classified into five main groups: customer characteristics, environmental (social and cultural) influences, provider characteristics, mobile-device characteristics, and perceived risks.
Abstract: The value of emission factor was calculated in the
older type of Diesel engine operating on an engine testing bench and
then compared with the parameters monitored under similar
conditions when the EnviroxTM additive was applied. It has been
found out that the additive based on CeO2 nanoparticles reduces
emission of NOx. The dependencies of NOx emissions on reduced
torque, engine power and revolutions have been observed as well.
Abstract: We present a hybrid architecture of recurrent neural
networks (RNNs) inspired by hidden Markov models (HMMs). We
train the hybrid architecture using genetic algorithms to learn and
represent dynamical systems. We train the hybrid architecture on a
set of deterministic finite-state automata strings and observe the
generalization performance of the hybrid architecture when presented
with a new set of strings which were not present in the training data
set. In this way, we show that the hybrid system of HMM and RNN
can learn and represent deterministic finite-state automata. We ran
experiments with different sets of population sizes in the genetic
algorithm; we also ran experiments to find out which weight
initializations were best for training the hybrid architecture. The
results show that the hybrid architecture of recurrent neural networks
inspired by hidden Markov models can train and represent dynamical
systems. The best training and generalization performance is
achieved when the hybrid architecture is initialized with random real
weight values of range -15 to 15.