Abstract: Over the last few decades, oilfield service rolling
equipment has significantly increased in weight, primarily because of
emissions regulations, which require larger/heavier engines, larger
cooling systems, and emissions after-treatment systems, in some
cases, etc. Larger engines cause more vibration and shock loads,
leading to failure of electronics and control systems.
If the vibrating frequency of the engine matches the system
frequency, high resonance is observed on structural parts and mounts.
One such existing automated control equipment system comprising
wire rope mounts used for mounting computers was designed
approximately 12 years ago. This includes the use of an industrialgrade
computer to control the system operation. The original
computer had a smaller, lighter enclosure. After a few years, a newer
computer version was introduced, which was 10 lbm heavier. Some
failures of internal computer parts have been documented for cases in
which the old mounts were used. Because of the added weight, there
is a possibility of having the two brackets impact each other under
off-road conditions, which causes a high shock input to the computer
parts. This added failure mode requires validating the existing mount
design to suit the new heavy-weight computer.
This paper discusses the modal finite element method (FEM)
analysis and experimental modal analysis conducted to study the
effects of vibration on the wire rope mounts and the computer. The
existing mount was modelled in ANSYS software, and resultant
mode shapes and frequencies were obtained. The experimental modal
analysis was conducted, and actual frequency responses were
observed and recorded.
Results clearly revealed that at resonance frequency, the brackets
were colliding and potentially causing damage to computer parts. To
solve this issue, spring mounts of different stiffness were modeled in
ANSYS software, and the resonant frequency was determined.
Increasing the stiffness of the system increased the resonant
frequency zone away from the frequency window at which the engine
showed heavy vibrations or resonance. After multiple iterations in
ANSYS software, the stiffness of the spring mount was finalized,
which was again experimentally validated.
Abstract: The recommended limit for cadmium concentration in
potable water is less than 0.005 mg/L. A continuous biosorption
process using indigenous red seaweed, Gracilaria corticata, was
performed to remove cadmium from the potable water. The process
was conducted under fixed conditions and the breakthrough curves
were achieved for three consecutive sorption-desorption cycles. A
modeling based on Artificial Neural Network (ANN) was employed
to fit the experimental breakthrough data. In addition, a simplified
semi empirical model, Thomas, was employed for this purpose. It
was found that ANN well described the experimental data (R2>0.99)
while the Thomas prediction were a bit less successful with R2>0.97.
The adjusted design parameters using the nonlinear form of Thomas
model was in a good agreement with the experimentally obtained
ones. The results approve the capability of ANN to predict the
cadmium concentration in potable water.
Abstract: Science and technology has a major impact on many
societal domains such as communication, medicine, food,
transportation, etc. However, this dominance of modern technology
can have a negative unintended impact on indigenous systems, and in
particular on indigenous foods. This problem serves as a motivation
to this study whose aim is to examine the perceptions of learners on
the usefulness of Information and Communication Technologies
(ICTs) for learning about indigenous foods. This aim will be
subdivided into two types of research objectives. The design and
identification of theories and models will be achieved using literature
content analysis. The objective on the empirical testing of such
theories and models will be achieved through the survey of
Hospitality studies learners from different schools in the iLembe and
Umgungundlovu Districts of the South African Kwazulu-Natal
province. SPSS is used to quantitatively analyze the data collected by
the questionnaire of this survey using descriptive statistics and
Pearson correlations after the assessment of the validity and the
reliability of the data. The main hypothesis behind this study is that
there is a connection between the demographics of learners, their
perceptions on the usefulness of ICTs for learning about indigenous
foods, and the following personality and eLearning related theories
constructs: Computer self-efficacy, Trust in ICT systems, and
Conscientiousness; as suggested by existing studies on learning
theories. This hypothesis was fully confirmed by the survey
conducted by this study except for the demographic factors where
gender and age were not found to be determinant factors of learners’
perceptions on the usefulness of ICTs for learning about indigenous
foods.
Abstract: The problematic of gender and socioeconomic status
biased differences in academic motivation patterns is discussed.
Gender identity is understood according to symbolic interactionism
perspective: as a result of reflected appraisals, social comparisons,
self-attributions, and identifications, shaped by social environment
and family context. The effects of socioeconomic status on academic
motivation are conceptualized according to Bourdieu’s habitus
concept, reflecting the role of unconscious and internalized cultural
signals, proper to low and high socioeconomic status family contexts.
Since families differ by various socioeconomic features, the
hypothesis about possible impact of parents’ socioeconomic status on
their children’s academic motivation interfering with gender
socialization effects is held. The survey, aiming to seize gender
differences in academic motivation and self-recorded improvementoriented
efforts as a result of socialization processes operating in the
families of low and high socioeconomic status, was designed. The
results of Lithuanian higher education students’ survey are presented
and discussed.
Abstract: Nowadays, Photovoltaic-PV Farms/ Parks and large
PV-Smart Grid Interface Schemes are emerging and commonly
utilized in Renewable Energy distributed generation. However, PVhybrid-
Dc-Ac Schemes using interface power electronic converters
usually has negative impact on power quality and stabilization of
modern electrical network under load excursions and network fault
conditions in smart grid. Consequently, robust FACTS based
interface schemes are required to ensure efficient energy utilization
and stabilization of bus voltages as well as limiting switching/fault
onrush current condition. FACTS devices are also used in smart grid-
Battery Interface and Storage Schemes with PV-Battery Storage
hybrid systems as an elegant alternative to renewable energy
utilization with backup battery storage for electric utility energy and
demand side management to provide needed energy and power
capacity under heavy load conditions. The paper presents a robust
interface PV-Li-Ion Battery Storage Interface Scheme for
Distribution/Utilization Low Voltage Interface using FACTS
stabilization enhancement and dynamic maximum PV power tracking
controllers.
Digital simulation and validation of the proposed scheme is done
using MATLAB/Simulink software environment for Low Voltage-
Distribution/Utilization system feeding a hybrid Linear-Motorized
inrush and nonlinear type loads from a DC-AC Interface VSC-6-
pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion
Storage Battery.
Abstract: In this work, neural networks methods MLP type were
applied to a database from an array of six sensors for the detection of
three toxic gases. The choice of the number of hidden layers and the
weight values are influential on the convergence of the learning
algorithm. We proposed, in this article, a mathematical formula to
determine the optimal number of hidden layers and good weight
values based on the method of back propagation of errors. The results
of this modeling have improved discrimination of these gases and
optimized the computation time. The model presented here has
proven to be an effective application for the fast identification of
toxic gases.
Abstract: The continuous decline of petroleum and natural gas
reserves and non linear rise of oil price has brought about a
realisation of the need for a change in our perpetual dependence on
the fossil fuel. A day to day increased consumption of crude and
petroleum products has made a considerable impact on our foreign
exchange reserves. Hence, an alternate resource for the conversion of
energy (both liquid and gas) is essential for the substitution of
conventional fuels. Biomass is the alternate solution for the present
scenario. Biomass can be converted into both liquid as well as
gaseous fuels and other feedstocks for the industries.
Abstract: Container handling problems at container terminals
are NP-hard problems. This paper presents an approach using
discrete-event simulation modeling to optimize solution for storage
space allocation problem, taking into account all various interrelated
container terminal handling activities. The proposed approach is
applied on a real case study data of container terminal at Alexandria
port. The computational results show the effectiveness of the
proposed model for optimization of storage space allocation in
container terminal where 54% reduction in containers handling time
in port is achieved.
Abstract: In this study, we are interested in a species of the
family of Asteraceae (Tagetes erecta). This family is considered as a
source of antimicrobial extracts with strong capacity. The extraction
of the flavonoids is carried out by the method of liquid/liquid with the
use of successive solvents. Afterwards, we evaluated the biological
activity of the flavonoids on five pathogenic bacterial stocks such as
Escherichia coli, Bacillus subtilis, Klebsiella pneumoniae,
Pseudomonas aeruginosa and Staphylococcus aureus and two stocks
of yeasts to knowing Candida albicans) and Saccharomyces
cerevisiae, by employing the method of the aromatogramme starting
from a solid disc. The result of the antimicrobial activity shows an
action and a variable degree of sensitivity according to bacterial
stocks tested. It will be noted that the flavonoids have an inhibiting
effect on E. coli, B. subtilis, K. pneumoniae and S. aureus. But a
resistance with respect to the extract by P. aeruginosa, C. albicans
and S. cerevisiae is to be mentioned.
Abstract: At present, the evaluation of voltage stability
assessment experiences sizeable anxiety in the safe operation of
power systems. This is due to the complications of a strain power
system. With the snowballing of power demand by the consumers
and also the restricted amount of power sources, therefore, the system
has to perform at its maximum proficiency. Consequently, the
noteworthy to discover the maximum ability boundary prior to
voltage collapse should be undertaken. A preliminary warning can be
perceived to evade the interruption of power system’s capacity. The
effectiveness of line voltage stability indices (LVSI) is differentiated
in this paper. The main purpose of the indices used is to predict the
proximity of voltage instability of the electric power system. On the
other hand, the indices are also able to decide the weakest load buses
which are close to voltage collapse in the power system. The line
stability indices are assessed using the IEEE 14 bus test system to
validate its practicability. Results demonstrated that the implemented
indices are practically relevant in predicting the manifestation of
voltage collapse in the system. Therefore, essential actions can be
taken to dodge the incident from arising.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: The paper describes a Chinese shadow play animation
system based on Kinect. Users, without any professional training, can
personally manipulate the shadow characters to finish a shadow play
performance by their body actions and get a shadow play video
through giving the record command to our system if they want. In our
system, Kinect is responsible for capturing human movement and
voice commands data. Gesture recognition module is used to control
the change of the shadow play scenes. After packaging the data from
Kinect and the recognition result from gesture recognition module,
VRPN transmits them to the server-side. At last, the server-side uses
the information to control the motion of shadow characters and video
recording. This system not only achieves human-computer interaction,
but also realizes the interaction between people. It brings an
entertaining experience to users and easy to operate for all ages. Even
more important is that the application background of Chinese shadow
play embodies the protection of the art of shadow play animation.
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: Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
Abstract: Machining parameters are very important in
determining the surface quality of any material. In the past decade,
some new engineering materials were developed for the
manufacturing industry which created a need to conduct an
investigation on the impact of the said parameters on their surface
roughness. Polyurethane (PU) block is widely used in the automotive
industry to manufacture parts such as checking fixtures that are used
to verify the dimensional accuracy of automotive parts. In this paper,
the design of experiment (DOE) was used to investigate on the effect
of the milling parameters on the PU block. Furthermore, an analysis
of the machined surface chemical composition was done using
scanning electron microscope (SEM). It was found that the surface
roughness of the PU block is severely affected when PU undergoes a
flood machining process instead of a dry condition. In addition the
stepover and the silicon content were found to be the most significant
parameters that influence the surface quality of the PU block.
Abstract: Safety is one of the most important considerations
when buying a new car. While active safety aims at avoiding
accidents, passive safety systems such as airbags and seat belts
protect the occupant in case of an accident. In addition to legal
regulations, organizations like Euro NCAP provide consumers with
an independent assessment of the safety performance of cars and
drive the development of safety systems in automobile industry.
Those ratings are mainly based on injury assessment reference values
derived from physical parameters measured in dummies during a car
crash test.
The components and sub-systems of a safety system are designed
to achieve the required restraint performance. Sled tests and other
types of tests are then carried out by car makers and their suppliers
to confirm the protection level of the safety system. A Knowledge
Discovery in Databases (KDD) process is proposed in order to
minimize the number of tests. The KDD process is based on the
data emerging from sled tests according to Euro NCAP specifications.
About 30 parameters of the passive safety systems from different data
sources (crash data, dummy protocol) are first analysed together with
experts opinions. A procedure is proposed to manage missing data
and validated on real data sets. Finally, a procedure is developed to
estimate a set of rough initial parameters of the passive system before
testing aiming at reducing the number of tests.
Abstract: Electricity spot prices are highly volatile under
optimal generation capacity scenarios due to factors such as nonstorability
of electricity, peak demand at certain periods, generator
outages, fuel uncertainty for renewable energy generators, huge
investments and time needed for generation capacity expansion etc.
As a result market participants are exposed to price and volume risk,
which has led to the development of risk management practices. This
paper provides an overview of risk management practices by market
participants in electricity markets using financial derivatives.
Abstract: Fuzzy inference method based approach to the
forming of modular intellectual system of assessment the quality of
communication services is proposed. Developed under this approach
the basic fuzzy estimation model takes into account the
recommendations of the International Telecommunication Union in
respect of the operation of packet switching networks based on IPprotocol.
To implement the main features and functions of the fuzzy
control system of quality telecommunication services it is used
multilayer feedforward neural network.
Abstract: Metal matrix composites (MMCs) attract considerable
attention as a result from its ability in providing a high strength, high
modulus, high toughness, high impact properties, improving wear
resistance and providing good corrosion resistance compared to
unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been
widely used in various industrial sectors such as in transportation,
domestic equipment, aerospace, military, construction, etc.
Aluminium silicon alloy is an MMC that had been reinforced with
aluminium nitrate (AlN) particle and become a new generation
material use in automotive and aerospace sector. The AlN is one of
the advance material that have a bright prospect in future since it has
features such as lightweight, high strength, high hardness and
stiffness quality. However, the high degree of ceramic particle
reinforcement and the irregular nature of the particles along the
matrix material that contribute to its low density is the main problem
which leads to difficulties in machining process. This paper examined
the tool wear when milling AlSi/AlN Metal Matrix Composite using
a TiB2 (Titanium diboride) coated carbide cutting tool. The volume
of the AlN reinforced particle was 10% and milling process was
carried out under dry cutting condition. The TiB2 coated carbide
insert parameters used were at the cutting speed of (230, 300 and
370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The
Sometech SV-35 video microscope system used to quantify of the
tool wear. The result shown that tool life span increasing with the
cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at
0.4mm) which constituted an optimum condition for longer tool life
lasted until 123.2 mins. Meanwhile, at medium cutting speed which
at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we
found that tool life span lasted until 119.86 mins while at low cutting
speed it lasted in 119.66 mins. High cutting speed will give the best
parameter in cutting AlSi/AlN MMCs material. The result will help
manufacturers in machining process of AlSi/AlN MMCs materials.
Abstract: Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.