Abstract: Producing IT products/services required carefully
designed. IT development process is intangible and labour intensive.
Making optimal use of available resources, both soft (knowledge,
skill-set etc.) and hard (computer system, ancillary equipment etc.),
is vital if IT development is to achieve sensible economical
advantages. Apart from the norm of Project Life Cycle and System
Development Life Cycle (SDLC), there is an urgent need to establish
a general yet widely acceptable guideline on the most effective and
efficient way to precede an IT project in the broader view of Product
Life Cycle. The current paper proposes such a framework with two
major areas of concern: (1) an integration of IT Products and IT
Services within an existing IT Process architecture and; (2) how IT
Product and IT Services are built into the framework of Product Life
Cycle, Project Life Cycle and SDLC.
Abstract: The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of 'n' input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.
Abstract: Numerical investigation of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann methods at different Reynolds numbers. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations, streamlines and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The Reynolds numbers affected the physical quantities.
Abstract: In recent years, the development of e-learning is very
rapid. E-learning is an attractive and efficient way for computer
education. Student interaction and collaboration also plays an
important role in e-learning. In this paper, a collaborative web-based
e-learning environment is presented. A wide range of interactive and
collaborative methods are integrated into a web-based environment.
This e-learning environment is designed for information security
curriculum.
Abstract: This paper presents an new vision technique for
robotic manipulation of randomly oriented objects in industrial
applications. The proposed approach uses 2D and 3D vision for
efficiently extracting the 3D pose of an object in the presence of
multiple randomly positioned objects. 2D vision permits to quickly
select the objects of interest for 3D processing with a new modified
ICP algorithm (FaR-ICP), thus reducing significantly the processing
time. The extracted 3D pose is then sent to the robot manipulator for
picking. The tests show that the proposed system achieves high
performances
Abstract: Deciding the numerous parameters involved in
designing a competent artificial neural network is a complicated task.
The existence of several options for selecting an appropriate
architecture for neural network adds to this complexity, especially
when different applications of heterogeneous natures are concerned.
Two completely different applications in engineering and medical
science were selected in the present study including prediction of
workpiece's surface roughness in ultrasonic-vibration assisted turning
and papilloma viruses oncogenicity. Several neural network
architectures with different parameters were developed for each
application and the results were compared. It was illustrated in this
paper that some applications such as the first one mentioned above
are apt to be modeled by a single network with sufficient accuracy,
whereas others such as the second application can be best modeled
by different expert networks for different ranges of output.
Development of knowledge about the essentials of neural networks
for different applications is regarded as the cornerstone of
multidisciplinary network design programs to be developed as a
means of reducing inconsistencies and the burden of the user
intervention.
Abstract: Microstructure, wetting behavior and interfacial
reactions between Sn–0.7Cu and Sn–0.3Ag–0.7Cu (SAC0307)
solders solidified on Ni coated Al substrates were compared and
investigated. Microstructure of Sn–0.7Cu alloy exhibited a eutectic
matrix composed of primary β-Sn dendrites with a fine dispersion of
Cu6Sn5 intermetallics whereas microstructure of SAC0307 alloy
exhibited coarser Cu6Sn5 and finer Ag3Sn precipitates of IMCs with
decreased tin dendrites. Contact angles ranging from 22° to 26° were
obtained for Sn–0.7Cu solder solidified on substrate surface whereas
for SAC0307 solder alloy contact angles were found to be in the
range of 20° to 22°. Sn–0.7Cu solder/substrate interfacial region
exhibited faceted (Cu, Ni)6Sn5 IMCs protruding into the solder matrix
and a small amount of (Cu, Ni)3Sn4 intermetallics at the interface.
SAC0307 solder/substrate interfacial region showed mainly (Cu,
Ni)3Sn4 intermetallics adjacent to the coating layer and (Cu,
Ni)6Sn5 IMCs in the solder matrix. The improvement in the
wettability of SAC0307 solder alloy on substrate surface is attributed
to the formation of cylindrical shape (Cu,Ni)6Sn5 and a layer of
(Cu, Ni)3Sn4 IMCs at the interface.
Abstract: Portuguese diet has been gradually diverging from the basic principles of healthy eating, leading to an unbalanced dietary pattern which, associated with increasing sedentary lifestyle, has a negative impact on public health. The main objective of this work was to characterize the dietary habits of university students in Viseu, Portugal. The study consisted of a sample of 80 university students, aged between 18 and 28 years. Anthropometric data (weight (kg) and height (m)) were collected and Body Mass Index (BMI) was calculated. The dietary habits were assessed through a three-day food record and the software Medpoint was used to convert food into energy and nutrients. The results showed that students present a normal body mass index. Female university students made a higher number of daily meals than male students, and these last skipped breakfast more frequently. The values of average daily intake of energy, macronutrients and calcium were higher in males. The food pattern was characterized by a predominant consumption of meat, cereal, fats and sugar. Dietary intake of dairy products, fruits, vegetables and legumes does not meet the recommendations, revealing inadequate food habits such as hypoglycemic, hyperprotein and hyperlipidemic diet. Our findings suggest that preventive interventions should be focus in promoting healthy eating habits and physical activity in adulthood.
Abstract: Processing the data by computers and performing
reasoning tasks is an important aim in Computer Science. Semantic
Web is one step towards it. The use of ontologies to enhance the
information by semantically is the current trend. Huge amount of
domain specific, unstructured on-line data needs to be expressed in
machine understandable and semantically searchable format.
Currently users are often forced to search manually in the results
returned by the keyword-based search services. They also want to use
their native languages to express what they search. In this paper, an
ontology-based automated question answering system on software
test documents domain is presented. The system allows users to enter
a question about the domain by means of natural language and
returns exact answer of the questions. Conversion of the natural
language question into the ontology based query is the challenging
part of the system. To be able to achieve this, a new algorithm
regarding free text to ontology based search engine query conversion
is proposed. The algorithm is based on investigation of suitable
question type and parsing the words of the question sentence.
Abstract: Low frequency power oscillations may be triggered
by many events in the system. Most oscillations are damped by the
system, but undamped oscillations can lead to system collapse.
Oscillations develop as a result of rotor acceleration/deceleration
following a change in active power transfer from a generator. Like
the operations limits, the monitoring of power system oscillating
modes is a relevant aspect of power system operation and control.
Unprevented low-frequency power swings can be cause of cascading
outages that can rapidly extend effect on wide region. On this regard,
a Wide Area Monitoring, Protection and Control Systems
(WAMPCS) help in detecting such phenomena and assess power
system dynamics security. The monitoring of power system
electromechanical oscillations is very important in the frame of
modern power system management and control. In first part, this
paper compares the different technique for identification of power
system oscillations. Second part analyzes possible identification
some power system dynamics behaviors Using Wide Area
Monitoring Systems (WAMS) based on Phasor Measurement Units
(PMUs) and wavelet technique.
Abstract: The use of solar control film on windows as one of
solar passive strategies for building have becoming important and is
gaining recognition. Malaysia located close to equator is having
warm humid climate with long sunshine hours and abundant solar
radiation throughout the year. Hence, befitting solar control on
windows is absolutely necessary to capture the daylight whilst
moderating thermal impact and eliminating glare problems. This is
one of the energy efficient strategies to achieve thermal and visual
comfort in buildings. Therefore, this study was carried out to
investigate the effect of window solar controls on thermal and visual
performance of naturally ventilated buildings. This was conducted via
field data monitoring using a test building facility. Four types of
window glazing systems were used with three types of solar control
films. Data were analysed for thermal and visual impact with
reference to thermal and optical characteristics of the films. Results
show that for each glazing system, the surface temperature of
windows are influenced by the Solar Energy Absorption property, the
indoor air temperature are influenced by the Solar Energy
Transmittance and Solar Energy Reflectance, and the daylighting by
Visible Light Transmission and Shading Coefficient. Further
investigations are underway to determine the mathematical relation
between thermal energy and visual performance with the thermal and
optical characteristics of solar control films.
Abstract: Measurements of radioactivity in the environment is of great importance to monitor and control the levels of radiation to which man is exposed directly or indirectly. It is necessary to show that regardless of working or being close to nuclear power plants, people are daily in contact with some amount of radiation from the actual environment and food that are ingested, contradicting the view of most of them. The aim of this study was to analyze the rate of natural and artificial radiation from radionuclides present in cement, soil and fertilizers used in Sergipe State – Brazil. The radionuclide activitiesmeasured all samples arebelow the Brazilian limit of the exclusion and exemption criteria from the requirement of radiation protection.It was detected Be-7 in organic fertilizers that means a short interval between the brewing processes for use in agriculture. It was also detected an unexpected Cs-137 in some samples; however its activities does not represent risk for the population. Th-231 was also found in samples of soil and cement in the state of Sergipe that is an unprecedented result.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: In this study, a classification-based video
super-resolution method using artificial neural network (ANN) is
proposed to enhance low-resolution (LR) to high-resolution (HR)
frames. The proposed method consists of four main steps:
classification, motion-trace volume collection, temporal adjustment,
and ANN prediction. A classifier is designed based on the edge
properties of a pixel in the LR frame to identify the spatial information.
To exploit the spatio-temporal information, a motion-trace volume is
collected using motion estimation, which can eliminate unfathomable
object motion in the LR frames. In addition, temporal lateral process is
employed for volume adjustment to reduce unnecessary temporal
features. Finally, ANN is applied to each class to learn the complicated
spatio-temporal relationship between LR and HR frames. Simulation
results show that the proposed method successfully improves both
peak signal-to-noise ratio and perceptual quality.
Abstract: The combustion chamber dimensions have important
effects on pollutant emission in furnaces as a direct result of
temperature distribution and maximum temperature value. In this
paper the pollutant emission and the temperature distribution in two
cylindrical furnaces with different dimensions (with similar length to
diameter ratio) in similar condition have been investigated
experimentally. The furnace fuel is gas oil that is used with three
different flow rates. The results show that in these two cases the
temperature increases to its maximum value quickly, and then
decreases slowly. The results also show that increase in fuel flow rate
cause to increase in NOx emission in each case, but this increase is
greater in small furnace. With increase in fuel flow rate, CO emission
decreases firstly, and then it increases. Combustion efficiency
reduces with increase in fuel flow rate but the rate of reduction in
small furnace is greater than large furnace. The results of axial
temperature distribution have been compared with those have been
obtained numerically and experimentally by Moghiman.
Abstract: A fault detection and identification (FDI) technique is
presented to create a fault tolerant control system (FTC). The fault
detection is achieved by monitoring the position of the light source
using an array of light sensors. When a decision is made about the
presence of a fault an identification process is initiated to locate the
faulty component and reconfigure the controller signals. The signals
provided by the sensors are predictable; therefore the existence of a
fault is easily identified. Identification of the faulty sensor is based on
the dynamics of the frame. The technique is not restricted to a
particular type of controllers and the results show consistency.
Abstract: Reverse Engineering is a very important process in
Software Engineering. It can be performed backwards from system
development life cycle (SDLC) in order to get back the source data
or representations of a system through analysis of its structure,
function and operation. We use reverse engineering to introduce an
automatic tool to generate system requirements from its program
source codes. The tool is able to accept the Cµ programming source
codes, scan the source codes line by line and parse the codes to
parser. Then, the engine of the tool will be able to generate system
requirements for that specific program to facilitate reuse and
enhancement of the program. The purpose of producing the tool is to
help recovering the system requirements of any system when the
system requirements document (SRD) does not exist due to
undocumented support of the system.
Abstract: In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.
Abstract: In this paper, an artificial neural network simulator is
employed to carry out diagnosis and prognosis on electric motor as
rotating machinery based on predictive maintenance. Vibration data
of the primary failed motor including unbalance, misalignment and
bearing fault were collected for training the neural network. Neural
network training was performed for a variety of inputs and the motor
condition was used as the expert training information. The main
purpose of applying the neural network as an expert system was to
detect the type of failure and applying preventive maintenance. The
advantage of this study is for machinery Industries by providing
appropriate maintenance that has an essential activity to keep the
production process going at all processes in the machinery industry.
Proper maintenance is pivotal in order to prevent the possible failures
in operating system and increase the availability and effectiveness of
a system by analyzing vibration monitoring and developing expert
system.
Abstract: This study uses natural water and the surface properties of powdered activated carbon to acclimatize organics, forming biofilms on the surface of powdered activated carbon. To investigate the influence of different hydraulic retention times on the removal efficacy of trace organics in raw water, and to determine the optimal hydraulic retention time of a biological powdered activated carbon system, this study selects ozone-treated water processed by Feng-shan Advanced Water Purification Plant in southern Taiwan for the experiment. The evaluation indicators include assimilable organic carbon, dissolved organic carbon, and total organic carbon. The results of this study can improve the quality of drinking water treated using advanced water purification procedures.