Abstract: The sea waves carry thousands of GWs of power
globally. Although there are a number of different approaches to
harness offshore energy, they are likely to be expensive, practically
challenging, and vulnerable to storms. Therefore, this paper considers
using the near shore waves for generating mechanical and electrical
power. It introduces two new approaches, the wave manipulation and
using a variable duct turbine, for intercepting very wide wave fronts
and coping with the fluctuations of the wave height and the sea level,
respectively. The first approach effectively allows capturing much
more energy yet with a much narrower turbine rotor. The second
approach allows using a rotor with a smaller radius but captures
energy of higher wave fronts at higher sea levels yet preventing it
from totally submerging. To illustrate the effectiveness of the first
approach, the paper contains a description and the simulation results
of a scale model of a wave manipulator. Then, it includes the results
of testing a physical model of the manipulator and a single duct, axial
flow turbine in a wave flume in the laboratory. The paper also
includes comparisons of theoretical predictions, simulation results,
and wave flume tests with respect to the incident energy, loss in wave
manipulation, minimal loss, brake torque, and the angular velocity.
Abstract: In this paper we propose a computer-aided solution
with Genetic Algorithms in order to reduce the drafting of reports:
FMEA analysis and Control Plan required in the manufacture of the
product launch and improved knowledge development teams for
future projects. The solution allows to the design team to introduce
data entry required to FMEA. The actual analysis is performed using
Genetic Algorithms to find optimum between RPN risk factor and
cost of production. A feature of Genetic Algorithms is that they are
used as a means of finding solutions for multi criteria optimization
problems. In our case, along with three specific FMEA risk factors is
considered and reduce production cost. Analysis tool will generate
final reports for all FMEA processes. The data obtained in FMEA
reports are automatically integrated with other entered parameters in
Control Plan. Implementation of the solution is in the form of an
application running in an intranet on two servers: one containing
analysis and plan generation engine and the other containing the
database where the initial parameters and results are stored. The
results can then be used as starting solutions in the synthesis of other
projects. The solution was applied to welding processes, laser cutting
and bending to manufacture chassis for buses. Advantages of the
solution are efficient elaboration of documents in the current project
by automatically generating reports FMEA and Control Plan using
multiple criteria optimization of production and build a solid
knowledge base for future projects. The solution which we propose is
a cheap alternative to other solutions on the market using Open
Source tools in implementation.
Abstract: When neck pain is associated with pain, numbness, or
weakness in the arm, shoulder, or hand, further investigation is
needed as these are symptoms indicating pressure on one or more
nerve roots. Evaluation necessitates a neurologic examination and
imaging using an MRI/CT scan. A degenerating disc loses some
thickness and is less flexible, causing inter-vertebrae space to narrow.
A radiologist diagnoses an Intervertebral Disc Degeneration (IDD) by
localizing every inter-vertebral disc and identifying the pathology in
a disc based on its geometry and appearance. Accurate localizing is
necessary to diagnose IDD pathology. But, the underlying image
signal is ambiguous: a disc’s intensity overlaps the spinal nerve
fibres. Even the structure changes from case to case, with possible
spinal column bending (scoliosis). The inter-vertebral disc
pathology’s quantitative assessment needs accurate localization of the
cervical region discs. In this work, the efficacy of multilevel set
segmentation model, to segment cervical discs is investigated. The
segmented images are annotated using a simple distance matrix.
Abstract: Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.
Abstract: In a practical power system, the power plants are not
located at the same distance from the center of loads and their fuel
costs are different. Also, under normal operating conditions, the
generation capacity is more than the total load demand and losses.
Thus, there are many options for scheduling generation. In an
interconnected power system, the objective is to find the real and
reactive power scheduling of each power plant in such a way as to
minimize the operating cost. This means that the generator’s real and
reactive powers are allowed to vary within certain limits so as to meet
a particular load demand with minimum fuel cost. This is called
optimal power flow problem. In this paper, Economic Load Dispatch
(ELD) of real power generation is considered. Economic Load
Dispatch (ELD) is the scheduling of generators to minimize total
operating cost of generator units subjected to equality constraint of
power balance within the minimum and maximum operating limits of
the generating units. In this paper, genetic algorithms are considered.
ELD solutions are found by solving the conventional load flow
equations while at the same time minimizing the fuel costs.
Abstract: Structural Equation Modeling (SEM) was used to test
a hypothesized model explaining Malaysian hypermarket customers’
perceptions of brand trust (BT), customer perceived value (CPV) and
perceived service quality (PSQ) on building their brand loyalty
(CBL) and generating positive word-of-mouth communication
(WOM). Self-administered questionnaires were used to collect data
from 374 Malaysian hypermarket customers from Mydin, Tesco,
Aeon Big and Giant in Kuala Lumpur, a metropolitan city of
Malaysia. The data strongly supported the model exhibiting that BT,
CPV and PSQ are prerequisite factors in building customer brand
loyalty, while PSQ has the strongest effect on prediction of customer
brand loyalty compared to other factors. Besides, the present study
suggests the effect of the aforementioned factors via customer brand
loyalty strongly contributes to generate positive word of mouth
communication.
Abstract: Chrome tannery wastewater causes serious environmental hazard due to its high pollution potential. As a result, rigorous treatment is necessary for abatement of pollution from this type of wastewater. There are many research studies on chrome tannery wastewater treatment in the field of physical, chemical, and biological methods. In general, biological treatment process is found ineffective for direct application because of adverse effects by toxic chromium, sulphide, chloride etc. However, biological methods were employed mainly for a few sub processes generating significant amount of organic matter and without chromium, chlorides etc. In this context the present paper reviews the characteristics feature and pollution potential of wastewater generated from chrome tannery units and treatment of the same. The different biological processes used earlier and their chronological development for treatment of the chrome tannery wastewater are thoroughly reviewed in this paper. In this regard, the scope of hybrid bioreactor - an advanced technology option has also been explored, as this kind of treatment is well suited for the wastewater having inhibitory substances.
Abstract: Generating random numbers are mainly used to create
secret keys or random sequences. It can be carried out by various
techniques. In this paper we present a very simple and efficient
pseudo random number generator (PRNG) based on chaotic maps
and S-Box tables. This technique adopted two main operations one to
generate chaotic values using two logistic maps and the second to
transform them into binary words using random S-Box tables.
The simulation analysis indicates that our PRNG possessing
excellent statistical and cryptographic properties.
Abstract: Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
Abstract: A new concept of response system is proposed for
filling the gap that exists in reducing vulnerability during immediate
response to natural disasters. Real Time Early Response Systems
(RTERSs) incorporate real time information as feedback data for
closing control loop and for generating real time situation assessment.
A review of the state of the art on works that fit the concept of
RTERS is presented, and it is found that they are mainly focused on
manmade disasters. At the same time, in response phase of natural
disaster management many works are involved in creating early
warning systems, but just few efforts have been put on deciding what
to do once an alarm is activated. In this context a RTERS arises as a
useful tool for supporting people in their decision making process
during natural disasters after an event is detected, and also as an
innovative context for applying well-known automation technologies
and automatic control concepts and tools.
Abstract: The object of the present paper is to investigate several
general families of bilinear and bilateral generating functions with
different argument for the Gauss’ hypergeometric polynomials.
Abstract: Adsorption of a boron nitride nanotube (BNNT) was
examined toward ethylacetylene (C4H6) molecule by using density
functional theory (DFT) calculations at the B3LYP/6-31G (d) level,
and it was found that the adsorption energy (Ead) of ethylacetylene
the pristine nanotubes is about -1.60kcal/mol. But when nanotube has
been doped with Si and Al atoms, the adsorption energy of
ethylacetylene molecule was increased. Calculation showed that
when the nanotube is doping by Al, the adsorption energy is about -
24.19kcal/mol and also the amount of HOMO/LUMO energy gap
(Eg) will reduce significantly. Boron nitride nanotube is a suitable
adsorbent for ethylacetylene and can be used in separation processes
ethylacetylene. It is seem that nanotube (BNNT) is a suitable
semiconductor after doping, and the doped BNNT in the presence of
ethylacetylene an electrical signal is generating directly and therefore
can potentially be used for ethylacetylene sensors.
Abstract: In this paper we describe the Levenvberg-Marquardt
(LM) algorithm for identification and equalization of CDMA
signals received by an antenna array in communication channels.
The synthesis explains the digital separation and equalization of
signals after propagation through multipath generating intersymbol
interference (ISI). Exploiting discrete data transmitted and three
diversities induced at the reception, the problem can be composed
by the Block Component Decomposition (BCD) of a tensor of
order 3 which is a new tensor decomposition generalizing the
PARAFAC decomposition. We optimize the BCD decomposition by
Levenvberg-Marquardt method gives encouraging results compared to
classical alternating least squares algorithm (ALS). In the equalization
part, we use the Minimum Mean Square Error (MMSE) to perform
the presented method. The simulation results using the LM algorithm
are important.
Abstract: e-Service has moved from the usual manual and
traditional way of rendering services to electronic service provision
for the public and there are several reasons for implementing these
services, Airline ticketing have gone from its manual traditional way
to an intelligent web-driven service of purchasing. Many companies
have seen their profits doubled through the use of online services in
their operation and a typical example is Hewlett Packard (HP) which
is rapidly transforming their after sales business into a profit
generating e-service business unit.
This paper will examine the various challenges confronting e-
Service adoption and implementation in Nigeria and also analyse
lessons learnt from e-Service adoption and implementation in Asia to
see how it could be useful in Nigeria which is a lower middle income
country. From the analysis of the online survey data, it has been
identified that the public in Nigeria are much aware of e-Services but
successful adoption and implementation have been the problems
faced.
Abstract: Knowledge management is considered as an important
factor in improving health care services. KM facilitates the transfer of
existing knowledge and the development of new knowledge in
hospitals. This paper reviews practices adopted by doctors in Kuwait
for capturing, sharing, and generating knowledge. It also discusses
the perceived impact of KM practices on performance of hospitals.
Based on a survey of 277 doctors, the study found that KM practices
among doctors in the sampled hospitals were not very effective. Little
attention was paid to the main activities that support the transfer of
expertise among doctors in hospitals. However, as predicted by
previous studies, good km practices were perceived by doctors to
have a positive impact on performance of hospitals. It was concluded
that through effective KM practices hospitals could improve the
services they provide. Documentation of best practices and capturing
of lessons learnt for re-use of knowledge could help transform the
hospitals into learning organizations.
Abstract: The objective of the Economic Dispatch(ED) Problems
of electric power generation is to schedule the committed generating
units outputs so as to meet the required load demand at minimum
operating cost while satisfying all units and system equality and
inequality constraints. This paper presents a new method of ED
problems utilizing the Max-Min Ant System Optimization.
Historically, traditional optimizations techniques have been used,
such as linear and non-linear programming, but within the past
decade the focus has shifted on the utilization of Evolutionary
Algorithms, as an example Genetic Algorithms, Simulated Annealing
and recently Ant Colony Optimization (ACO). In this paper we
introduce the Max-Min Ant System based version of the Ant System.
This algorithm encourages local searching around the best solution
found in each iteration. To show its efficiency and effectiveness, the
proposed Max-Min Ant System is applied to sample ED problems
composed of 4 generators. Comparison to conventional genetic
algorithms is presented.
Abstract: Assertion-Based software testing has been shown to
be a promising tool for generating test cases that reveal program
faults. Because the number of assertions may be very large for
industry-size programs, one of the main concerns to the applicability
of assertion-based testing is the amount of search time required to
explore a large number of assertions. This paper presents a new
approach for assertions exploration during the process of Assertion-
Based software testing. Our initial exterminations with the proposed
approach show that the performance of Assertion-Based testing may
be improved, therefore, making this approach more efficient when
applied on programs with large number of assertions.
Abstract: Heightened concerns over the amount of carbon
emitted from coal-related processes are generating shifts to the
application of biomass. In co-gasification, where coal is gasified
along with biomass, the biomass may be fed together with coal (cofeeding)
or an independent biomass gasifier needs to be integrated
with the coal gasifier. The main aim of this work is to evaluate the
biomass introduction methods in coal co-gasification. This includes
the evaluation of biomass concentration input (B0 to B100) and its
gasification performance. A process model is developed and
simulated in Aspen HYSYS, where both coal and biomass are
modelled according to its ultimate analysis. It was found that the
syngas produced increased with increasing biomass content for both
co-feeding and independent schemes. However, the heating values
and heat duties decreases with biomass concentration as more CO2
are produced from complete combustion.
Abstract: The liver is the strongest regenerating organ of the
organism, and even with 2/3 surgically removed, it can regenerate
completely. Hence liver cirrhosis may only develop when the
regenerating system is off.
We present the results of a comparative study of structural and
functional characteristics of rat liver tissue under the conditions of
toxic liver cirrhosis development, induced by carbon tetrachloride,
and its prevention/treatment by natural compounds with antioxidant
and immune stimulating action. Studies were made on Wister rats,
weighing 120~140 g. Grape seeds extracts, separately and in
combination with well-known anticirrhotic drug ursodeoxycholic
acid (Urdoxa), have demonstrated effectiveness in prevention of liver
cirrhosis development and its treatment.
Abstract: Thanks to informational technologies development
every sphere of economics is becoming more and more datacentralized
as people are generating huge datasets containing
information on any aspect of their life. Applying research of such
data to human resources management allows getting scarce statistics
on labor market state including salary expectations and potential
employees’ typical career behavior, and this information can become
a reliable basis for management decisions.
The following article presents results of career behavior research
based on freely accessible resume data. Information used for study is
much wider than one usually uses in human resources surveys. That
is why there is enough data for statistically significant results even
for subgroups analysis.