Abstract: Stainless steel has been employed in many
engineering applications ranging from pharmaceutical equipment to
piping in the nuclear reactors and storage to chemical products. In
this attempt, simulation of fatigue crack growth based on
experimental results of austenitic stainless steel 304L was presented
using AFGROW code when NASGRO mode laws adopted. Double
through crack at hole specimen is used in this investigation under
constant amplitude loading. Effect of mean stress is highlighted.
Results show that fatigue crack growth rate (FCGR) and fatigue life
were affected by maximum applied load and dimension of hole. An
equivalent of Paris law for this material was estimated.
Abstract: This paper presents a low cost design of heart beat monitoring device using reflectance mode PhotoPlethysmography (PPG). PPG is known for its simple construction, ease of use and cost effectiveness and can provide information about the changes in cardiac activity as well as aid in earlier non-invasive diagnostics. The proposed device is divided into three phases. First is the detection of pulses through the fingertip. The signal is then passed to the signal processing unit for the purpose of amplification, filtering and digitizing. Finally the heart rate is calculated and displayed on the computer using parallel port interface. The paper is concluded with prototyping of the device followed by verification procedure of the heartbeat signal obtained in laboratory setting.
Abstract: The scope of this research was to study the relation between the facial expressions of three lecturers in a real academic lecture theatre and the reactions of the students to those expressions. The first experiment aimed to investigate the effectiveness of a virtual lecturer-s expressions on the students- learning outcome in a virtual pedagogical environment. The second experiment studied the effectiveness of a single facial expression, i.e. the smile, on the students- performance. Both experiments involved virtual lectures, with virtual lecturers teaching real students. The results suggest that the students performed better by 86%, in the lectures where the lecturer performed facial expressions compared to the results of the lectures that did not use facial expressions. However, when simple or basic information was used, the facial expressions of the virtual lecturer had no substantial effect on the students- learning outcome. Finally, the appropriate use of smiles increased the interest of the students and consequently their performance.
Abstract: Due to the recovering global economy, enterprises are
increasingly focusing on logistics. Investing in logistic measures for
a production generates a large potential for achieving a good starting
point within a competitive field. Unlike during the global economic
crisis, enterprises are now challenged with investing available capital
to maximize profits. In order to be able to create an informed and
quantifiably comprehensible basis for a decision, enterprises need an
adequate model for logistically and monetarily evaluating measures
in production. The Collaborate Research Centre 489 (SFB 489) at the
Institute for Production Systems (IFA) developed a Logistic
Information System which provides support in making decisions and
is designed specifically for the forging industry. The aim of a project
that has been applied for is to now transfer this process in order to
develop a universal approach to logistically and monetarily evaluate
measures in production.
Abstract: This paper describes a new supervised fusion (hybrid)
electrocardiogram (ECG) classification solution consisting of a new
QRS complex geometrical feature extraction as well as a new version
of the learning vector quantization (LVQ) classification algorithm
aimed for overcoming the stability-plasticity dilemma. Toward this
objective, after detection and delineation of the major events of ECG
signal via an appropriate algorithm, each QRS region and also its
corresponding discrete wavelet transform (DWT) are supposed as
virtual images and each of them is divided into eight polar sectors.
Then, the curve length of each excerpted segment is calculated
and is used as the element of the feature space. To increase the
robustness of the proposed classification algorithm versus noise,
artifacts and arrhythmic outliers, a fusion structure consisting of
five different classifiers namely as Support Vector Machine (SVM),
Modified Learning Vector Quantization (MLVQ) and three Multi
Layer Perceptron-Back Propagation (MLP–BP) neural networks with
different topologies were designed and implemented. The new proposed
algorithm was applied to all 48 MIT–BIH Arrhythmia Database
records (within–record analysis) and the discrimination power of the
classifier in isolation of different beat types of each record was
assessed and as the result, the average accuracy value Acc=98.51%
was obtained. Also, the proposed method was applied to 6 number
of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging
to 20 different records of the aforementioned database (between–
record analysis) and the average value of Acc=95.6% was achieved.
To evaluate performance quality of the new proposed hybrid learning
machine, the obtained results were compared with similar peer–
reviewed studies in this area.
Abstract: Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.
Abstract: Information is power. Geographical information is an
emerging science that is advancing the development of knowledge to
further help in the understanding of the relationship of “place" with
other disciplines such as crime. The researchers used crime data for
the years 2004 to 2007 from the Baguio City Police Office to
determine the incidence and actual locations of crime hotspots.
Combined qualitative and quantitative research methodology was
employed through extensive fieldwork and observation, geographic
visualization with Geographic Information Systems (GIS) and Global
Positioning Systems (GPS), and data mining. The paper discusses
emerging geographic visualization and data mining tools and
methodologies that can be used to generate baseline data for
environmental initiatives such as urban renewal and rejuvenation.
The study was able to demonstrate that crime hotspots can be
computed and were seen to be occurring to some select places in the
Central Business District (CBD) of Baguio City. It was observed that
some characteristics of the hotspot places- physical design and milieu
may play an important role in creating opportunities for crime. A list
of these environmental attributes was generated. This derived
information may be used to guide the design or redesign of the urban
environment of the City to be able to reduce crime and at the same
time improve it physically.
Abstract: As networking has become popular, Web-learning
tends to be a trend while designing a tool. Moreover, five-axis
machining has been widely used in industry recently; however, it has
potential axial table colliding problems. Thus this paper aims at
proposing an efficient web-learning collision detection tool on
five-axis machining. However, collision detection consumes heavy
resource that few devices can support, thus this research uses a
systematic approach based on web knowledge to detect collision. The
methodologies include the kinematics analyses for five-axis motions,
separating axis method for collision detection, and computer
simulation for verification. The machine structure is modeled as STL
format in CAD software. The input to the detection system is the
g-code part program, which describes the tool motions to produce the
part surface. This research produced a simulation program with C
programming language and demonstrated a five-axis machining
example with collision detection on web site. The system simulates the
five-axis CNC motion for tool trajectory and detects for any collisions
according to the input g-codes and also supports high-performance
web service benefiting from C. The result shows that our method
improves 4.5 time of computational efficiency, comparing to the
conventional detection method.
Abstract: This research contribution is drafted to present the
orbit design, orbit propagator and geomagnetic field estimator for the
nanosatellites specifically for the upcoming CUBESAT, ICUBE-1 of
the Institute of Space Technology (IST), Islamabad, Pakistan. The
ICUBE mission is designed for the low earth orbit at the approximate
height of 700KM. The presented research endeavor designs the
Keplarian elements for ICUBE-1 orbit while incorporating the
mission requirements and propagates the orbit using J2 perturbations,
The attitude determination system of the ICUBE-1 consists of
attitude determination sensors like magnetometer and sun sensor. The
Geomagnetic field estimator is developed according to the model of
International Geomagnetic Reference Field (IGRF) for comparing the
magnetic field measurements by the magnetometer for attitude
determination. The output of the propagator namely the Keplarians
position and velocity vectors and the magnetic field vectors are
compared and verified with the same scenario generated in the
Satellite Tool Kit (STK).
Abstract: The paper presents an overview of environmental
issues that may be expected with nuclear desalination. The analysis
of coupling nuclear power with desalination plants indicates that
adverse marine impacts can be mitigated with alternative intake
designs or cooling systems. The atmospheric impact of desalination
may be greatly reduced through the coupling with nuclear power,
while maximizing the socio-economic benefit for both processes. The
potential for tritium contamination of the desalinated water was
reviewed. Experience with the systems and practices related to the
radiological quality of the product water, shows no examples of
cross-contamination. Furthermore, the indicators for the public
acceptance of nuclear desalination, as one of the most important
sustainability aspects of any such large project, show a positive trend.
From the data collected, a conclusion is made that nuclear
desalination should be supported by decision-makers.
Abstract: Fixed-point simulation results are used for the
performance measure of inverting matrices by Cholesky
decomposition. The fixed-point Cholesky decomposition algorithm
is implemented using a fixed-point reconfigurable processing
element. The reconfigurable processing element provides all
mathematical operations required by Cholesky decomposition. The
fixed-point word length analysis is based on simulations using
different condition numbers and different matrix sizes. Simulation
results show that 16 bits word length gives sufficient performance
for small matrices with low condition number. Larger matrices and
higher condition numbers require more dynamic range for a fixedpoint
implementation.
Abstract: Atrial Fibrillation is the most common sustained
arrhythmia encountered by clinicians. Because of the invisible
waveform of atrial fibrillation in atrial activation for human, it is
necessary to develop an automatic diagnosis system. 12-Lead ECG
now is available in hospital and is appropriate for using Independent
Component Analysis to estimate the AA period. In this research, we
also adopt a second-order blind identification approach to transform
the sources extracted by ICA to more precise signal and then we use
frequency domain algorithm to do the classification. In experiment,
we gather a significant result of clinical data.
Abstract: Since straightness error of linear motor stage is hardly
dependent upon machining accuracy and assembling accuracy, there is
limit on maximum realizable accuracy. To cope with this limitation,
this paper proposed a servo system to compensate straightness error of
a linear motor stage. The servo system is mounted on the slider of the
linear motor stage and moves in the direction of the straightness error
so as to compensate the error. From position dependency and
repeatability of the straightness error of the slider, a feedforward
compensation control is applied to the platform servo control. In the
consideration of required fine positioning accuracy, a platform driven
by an electro-magnetic actuator is suggested and a sliding mode
control was applied. The effectiveness of the sliding mode control was
verified along with some experimental results.
Abstract: Segmentation techniques based on Active Contour
Models have been strongly benefited from the use of prior information
during their evolution. Shape prior information is captured from
a training set and is introduced in the optimization procedure to
restrict the evolution into allowable shapes. In this way, the evolution
converges onto regions even with weak boundaries. Although
significant effort has been devoted on different ways of capturing
and analyzing prior information, very little thought has been devoted
on the way of combining image information with prior information.
This paper focuses on a more natural way of incorporating the
prior information in the level set framework. For proof of concept
the method is applied on hippocampus segmentation in T1-MR
images. Hippocampus segmentation is a very challenging task, due
to the multivariate surrounding region and the missing boundary
with the neighboring amygdala, whose intensities are identical. The
proposed method, mimics the human segmentation way and thus
shows enhancements in the segmentation accuracy.
Abstract: In this paper is investigated a possible
optimization of some linear algebra problems which can be
solved by parallel processing using the special arrays called
systolic arrays. In this paper are used some special types of
transformations for the designing of these arrays. We show
the characteristics of these arrays. The main focus is on
discussing the advantages of these arrays in parallel
computation of matrix product, with special approach to the
designing of systolic array for matrix multiplication.
Multiplication of large matrices requires a lot of
computational time and its complexity is O(n3 ). There are
developed many algorithms (both sequential and parallel) with
the purpose of minimizing the time of calculations. Systolic
arrays are good suited for this purpose. In this paper we show
that using an appropriate transformation implicates in finding
more optimal arrays for doing the calculations of this type.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.
A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.
Abstract: Recently there has been a growing interest in the field
of bio-mimetic robots that resemble the behaviors of an insect or an
aquatic animal, among many others. One of various bio-mimetic robot
applications is to explore pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. Special
types of mobile robots are necessary for the pipeline monitoring tasks.
In order to move effectively along a pipeline, the robot-s movement
will resemble that of insects or crawling animals. When situated in
massive pipelines with complex routes, the robot places fixed sensors
in several important spots in order to complete its monitoring. This
monitoring task is to prevent a major system failure by preemptively
recognizing any minor or partial malfunctions. Areas uncovered by
fixed sensors are usually impossible to provide real-time observation
and examination, and thus are dependent on periodical offline
monitoring. This paper proposes a monitoring system that is able to
monitor the entire area of pipelines–with and without fixed
sensors–by using the bio-mimetic robot.
Abstract: The phenomenon of global warming or climate
change has led to many environmental issues including higher
atmospheric temperatures, intense precipitation, increased
greenhouse gaseous emissions and increased indoor discomfort.
Studies have shown that bringing nature to the roof such as
constructing green roof and implementing high-reflective roof may
give positive impact in mitigating the effects of global warming and
in increasing thermal comfort sensation inside buildings. However,
no study has been conducted to compare both types of passive roof
treatments in Malaysia in order to increase thermal comfort in
buildings. Therefore, this study is conducted to investigate the effect
of green roof and white painted roof as passive roof treatment in
improving indoor comfort of Malaysian homes. This study uses an
experimental approach in which the measurements of temperatures
are conducted on the case study building. The measurements of
outdoor and indoor environments were conducted on the flat roof
with two different types of roof treatment that are green roof and
white roof. The measurement of existing black bare roof was also
conducted to act as a control for this study.
Abstract: In cellular networks, limited availability of resources
has to be tapped to its fullest potential. In view of this aspect, a
sophisticated averaging and voting technique has been discussed in
this paper, wherein the radio resources available are utilized to the
fullest value by taking into consideration, several network and radio
parameters which decide on when the handover has to be made and
thereby reducing the load on Base station .The increase in the load
on the Base station might be due to several unnecessary handover
taking place which can be eliminated by making judicious use of the
radio and network parameters.