Abstract: Structural Integrity Management (SIM) is
important for the protection of offshore crew, environment, business assets and company and industry reputation. API RP 2A contained guidelines for assessment of existing platforms mostly for the Gulf
of Mexico (GOM). ISO 19902 SIM framework also does not
specifically cater for Malaysia. There are about 200 platforms in
Malaysia with 90 exceeding their design life. The Petronas Carigali
Sdn Bhd (PCSB) uses the Asset Integrity Management System and
the very subjective Risk based Inspection Program for these
platforms. Petronas currently doesn-t have a standalone Petronas
Technical Standard PTS-SIM. This study proposes a recommended
practice for the SIM process for offshore structures in Malaysia,
including studies by API and ISO and local elements such as the
number of platforms, types of facilities, age and risk ranking. Case
study on SMG-A platform in Sabah shows missing or scattered
platform data and a gap in inspection history. It is to undergo a level
3 underwater inspection in year 2015.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
Abstract: The purpose of this article is to briefly review the opportunities that social media present to counselors and psychologists. Particular attention was given to understanding some of the more important common risks inherent in social media and the potential ethical dilemmas which may arise for counselors and psychologists who embrace them in their practice. Key considerations of issues pertinent to an online presence such as multiple relationships, visibility and privacy, maintaining ethical principles and professional boundaries are being discussed.
Abstract: Total liquid ventilation can support gas exchange in animal models of lung injury. Clinical application awaits further technical improvements and performance verification. Our aim was to develop a liquid ventilator, able to deliver accurate tidal volumes, and a computerized system for measuring lung mechanics. The computer-assisted, piston-driven respirator controlled ventilatory parameters that were displayed and modified on a real-time basis. Pressure and temperature transducers along with a lineal displacement controller provided the necessary signals to calculate lung mechanics. Ten newborn lambs (
Abstract: The Artificial immune systems algorithms are Meta
heuristic optimization method, which are used for clustering and
pattern recognition applications are abundantly. These algorithms in
multimodal optimization problems are more efficient than genetic
algorithms. A major drawback in these algorithms is their slow
convergence to global optimum and their weak stability can be
considered in various running of these algorithms. In this paper,
improved Artificial Immune System Algorithm is introduced for the
first time to overcome its problems of artificial immune system. That
use of the small size of a local search around the memory antibodies
is used for improving the algorithm efficiently. The credibility of the
proposed approach is evaluated by simulations, and it is shown that
the proposed approach achieves better results can be achieved
compared to the standard artificial immune system algorithms
Abstract: Observations show that power plant efficiency
decreases in hot summer days. Water droplet injection in air
condensers is suggested in order to decrease the inlet air temperature.
Nozzle arrangement, injected water flow rate and droplets diameter
effects on evaporation rate and the resulting air temperature are
investigated using numerical simulation. Decreasing the diameter of
injected droplets and increasing the number of injecting nozzles,
decreases the outlet air temperature. Also a more uniform air
temperature can be obtained using more injecting nozzles. Numerical
results are in good agreement with analytical results.
Abstract: Energy consumption is an important design issue for
Mobile Subscriber Station (MSS) in the standard IEEE 802.16e.
Because mobility of MSS implies that energy saving becomes an
issue so that lifetime of MSS can be extended before re-charging.
Also, the mechanism in efficiently managing the limited energy is
becoming very significant since a MSS is generally energized by
battery. For these, sleep mode operation is recently specified in the
MAC (Medium Access Control) protocol. In order to reduce the
energy consumption, we focus on the sleep-mode and wake-mode of
the MAC layer, which are included in the IEEE 802.16 standards [1-
2].
Abstract: Many applications require surface modification and
micro-structuring of polymers. For these purposes is mainly used
ultraviolet (UV) radiation from excimer lamps or excimer lasers.
However, these sources have a decided disadvantage - degrading the
polymer deep inside due to relatively big radiation penetration depth
which may exceed 100 μm. In contrast, extreme ultraviolet (EUV)
radiation is absorbed in a layer approximately 100 nm thick only. In
this work, the radiation from a discharge-plasma EUV source (with
wavelength 46.9 nm) based on a capillary discharge driver is focused
with a spherical Si/Sc multilayer mirror for surface modification of
PMMA sample or thin gold layer (thickness about 40 nm). It was
found that the focused EUV laser beam is capable by one shot to
ablate PMMA or layer of gold, even if the focus is significantly
influenced by astigmatism.
Abstract: Many single or multispan arch bridges are
strengthened with the addition of some kind of structural support
between adjacent arches of multispan or beside the arch barrel of a
single span to increase the strength of the overall structure. It was
traditionally formed by either placing loose rubble masonry blocks
between the arches and beside the arches or using mortar or concrete
to construct a more substantial structural bond between the spans. On
the other hand backing materials are present in some existing bridges.
Existing arch assessment procedures generally ignore the effects of
backing materials. In this paper an investigation of the effects of
backing on ratings for masonry arch bridges is carried out. It is
observed that increasing the overall lateral stability of the arch
system through the inclusion of structural backing results in an
enhanced failure load by reducing the likelihood of any tension
occurring at the top of the arch.
Abstract: In a complex project environment, project teams face
multi-dimensional communication problems that can ultimately lead
to project breakdown. Team Performance varies in Face-to-Face
(FTF) environment versus groups working remotely in a computermediated
communication (CMC) environment. A brief review of the
Input_Process_Output model suggested by James E. Driskell, Paul H.
Radtke and Eduardo Salas in “Virtual Teams: Effects of
Technological Mediation on Team Performance (2003)", has been
done to develop the basis of this research. This model theoretically
analyzes the effects of technological mediation on team processes,
such as, cohesiveness, status and authority relations, counternormative
behavior and communication. An empirical study
described in this paper has been undertaken to test the
“cohesiveness" of diverse project teams in a multi-national
organization. This study uses both quantitative and qualitative
techniques for data gathering and analysis. These techniques include
interviews, questionnaires for data collection and graphical data
representation for analyzing the collected data. Computer-mediated
technology may impact team performance because of difference in
cohesiveness among teams and this difference may be moderated by
factors, such as, the type of communication environment, the type of
task and the temporal context of the team. Based on the reviewed
model, sets of hypotheses are devised and tested. This research,
reports on a study that compared team cohesiveness among virtual
teams using CMC and non-CMC communication mediums. The
findings suggest that CMC can help virtual teams increase team
cohesiveness among their members, making CMC an effective
medium for increasing productivity and team performance.
Abstract: Removal of Methylene Blue (MB) from aqueous
solution by adsorbing it on Gypsum was investigated by batch
method. The studies were conducted at 25°C and included the effects
of pH and initial concentration of Methylene Blue. The adsorption
data was analyzed by using the Langmuir, Freundlich and Tempkin
isotherm models. The maximum monolayer adsorption capacity was
found to be 36 mg of the dye per gram of gypsum. The data were
also analyzed in terms of their kinetic behavior and was found to
obey the pseudo second order equation.
Abstract: Petrol Fuel Station (PFS) has potential hazards to the
people, asset, environment and reputation of an operating company.
Fire hazards, static electricity air pollution evoked by aliphatic and
aromatic organic compounds are major causes of accident/incident
occurrence at fuel station. Activities such as carelessness,
maintenance, housekeeping, slips trips and falls, transportation
hazard, major and minor injuries, robbery and snake bites has a
potential to create unsafe conditions. The level of risk of these
hazards varies according to location and country. The emphasis on
safety considerations by the government is variable all around the
world. Developed countries safety records are much better as
compared to developing countries safety statistics. There is no
significant approach available to highlight the unsafe acts and unsafe
conditions during operation and maintenance of fuel station. Fuel
station is the most commonly available facilities that contain
flammable and hazardous materials. Due to continuous operation of
fuel station they pose various hazards to people, environment and
assets of an organization. To control these hazards, there is a need for
specific approach. PFS operation is unique as compared to other
businesses. For smooth operations it demands an involvement of
operating company, contractor and operator group. This study will
focus to address hazard contributing factors that have a potential to
make PFS operation risky. One year data collected, 902 activities
analyzed, comparisons were made to highlight significant
contributing factors. The study will provide help and assistance to
PFS outlet marketing companies to make their fuel station operation
safer. It will help health safety and environment (HSE) professionals
to arrest the gap available related to safety matters at PFS.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: One of the popular methods for recognition of facial
expressions such as happiness, sadness and surprise is based on
deformation of facial features. Motion vectors which show these
deformations can be specified by the optical flow. In this method, for
detecting emotions, the resulted set of motion vectors are compared
with standard deformation template that caused by facial expressions.
In this paper, a new method is introduced to compute the quantity of
likeness in order to make decision based on the importance of
obtained vectors from an optical flow approach. For finding the
vectors, one of the efficient optical flow method developed by
Gautama and VanHulle[17] is used. The suggested method has been
examined over Cohn-Kanade AU-Coded Facial Expression Database,
one of the most comprehensive collections of test images available.
The experimental results show that our method could correctly
recognize the facial expressions in 94% of case studies. The results
also show that only a few number of image frames (three frames) are
sufficient to detect facial expressions with rate of success of about
83.3%. This is a significant improvement over the available methods.
Abstract: Nowadays the control of stator voltage at a constant frequency is one of the traditional and low expense methods in order to control the speed of induction motors near its nominal speed. The torque of induction motor is a nonlinear function of the firing angle, phase angle and speed. In this paper the speed control of induction motor regarding various load torque and under different conditions will be investigated based on a fuzzy controller with inverse training.
Abstract: This paper presents a hybrid approach for solving nqueen problem by combination of PSO and SA. PSO is a population based heuristic method that sometimes traps in local maximum. To solve this problem we can use SA. Although SA suffer from many iterations and long time convergence for solving some problems, By good adjusting initial parameters such as temperature and the length of temperature stages SA guarantees convergence. In this article we use discrete PSO (due to nature of n-queen problem) to achieve a good local maximum. Then we use SA to escape from local maximum. The experimental results show that our hybrid method in comparison of SA method converges to result faster, especially for high dimensions n-queen problems.
Abstract: Innovations in technology have created new ethical
challenges. Essential use of electronic communication in the
workplace has escalated at an astronomical rate over the past decade.
As such, legal and ethical dilemmas confronted by both the employer
and the employee concerning managerial control and ownership of einformation
have increased dramatically in the USA. From the
employer-s perspective, ownership and control of all information
created for the workplace is an undeniable source of economic
advantage and must be monitored zealously. From the perspective of
the employee, individual rights, such as privacy, freedom of speech,
and freedom from unreasonable search and seizure, continue to be
stalwart legal guarantees that employers are not legally or ethically
entitled to abridge in the workplace. These issues have been the
source of great debate and the catalyst for legal reform. The fine line
between ethical and legal has been complicated by emerging
technologies. This manuscript will identify and discuss a number of
specific legal and ethical issues raised by the dynamic electronic
workplace and conclude with suggestions that employers should
follow to respect the delicate balance between employees- legal
rights to privacy and the employer's right to protect its knowledge
systems and infrastructure.
Abstract: This study has investigated the antidiabetic and
antioxidant potential of Pseudovaria macrophylla bark extract on
streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF
and NMR experiments were done to determine the chemical
composition in the methanolic bark extract. For in vivo experiments,
the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.)
induced diabetic rats were treated with methanolic extract of
Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and
glibenclamide (2.5 mg/kg) as positive control respectively.
Biochemical parameters were assayed in the blood samples of all
groups of rats. The pro-inflammatory cytokines, antioxidant status
and plasma transforming growth factor βeta-1 (TGF-β1) were
evaluated. The histological study of the pancreas was examined and
its expression level of insulin was observed by
immunohistochemistry. In addition, the expression of glucose
transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by
western blot analysis. The outcomes of the study displayed that the
bark methanol extract of Pseuduvaria macrophylla has potentially
normalized the elevated blood glucose levels and improved serum
insulin and C-peptide levels with significant increase in the
antioxidant enzyme, reduced glutathione (GSH) and decrease in the
level of lipid peroxidation (LPO). Additionally, the extract has
markedly decreased the levels of serum pro-inflammatory cytokines
and transforming growth factor beta-1 (TGF-β1). Histopathology
analysis demonstrated that Pseuduvaria macrophylla has the
potential to protect the pancreas of diabetic rats against peroxidation
damage by downregulating oxidative stress and elevated
hyperglycaemia. Furthermore, the expression of insulin protein,
GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced.
The findings of this study support the anti-diabetic claims of
Pseudovaria macrophylla bark.
Abstract: An adaptive neural network controller for
autonomous underwater vehicles (AUVs) is presented in this paper.
The AUV model is highly nonlinear because of many factors, such as
hydrodynamic drag, damping, and lift forces, Coriolis and centripetal
forces, gravity and buoyancy forces, as well as forces from thruster.
In this regards, a nonlinear neural network is used to approximate the
nonlinear uncertainties of AUV dynamics, thus overcoming some
limitations of conventional controllers and ensure good performance.
The uniform ultimate boundedness of AUV tracking errors and the
stability of the proposed control system are guaranteed based on
Lyapunov theory. Numerical simulation studies for motion control of
an AUV are performed to demonstrate the effectiveness of the
proposed controller.
Abstract: Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.