Abstract: MRAM technology provides a combination of fast
access time, non-volatility, data retention and endurance. While a
growing interest is given to two-terminal Magnetic Tunnel Junctions
(MTJ) based on Spin-Transfer Torque (STT) switching as the
potential candidate for a universal memory, its reliability is
dramatically decreased because of the common writing/reading path.
Three-terminal MTJ based on Spin-Orbit Torque (SOT) approach
revitalizes the hope of an ideal MRAM. It can overcome the
reliability barrier encountered in current two-terminal MTJs by
separating the reading and the writing path. In this paper, we study
two possible writing schemes for the SOT-MTJ device based on
recently fabricated samples. While the first is based on precessional
switching, the second requires the presence of permanent magnetic
field. Based on an accurate Verilog-A model, we simulate the two
writing techniques and we highlight advantages and drawbacks of
each one. Using the second technique, pioneering logic circuits based
on the three-terminal architecture of the SOT-MTJ described in this
work are under development with preliminary attractive results.
Abstract: Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.
Abstract: This study addresses the effect of impurities on the
crystallization of Na2CO3 produced within a strategy for capturing
CO2 from flue gases by alkaline absorption. A novel technology -
membrane assisted crystallization - is proposed for Na2CO3
crystallization from mother liquors containing impurities. High purity
of Na2CO3•10H2O crystals was obtained without impacting the
performance of the mass transfer of water vapor through membranes
during crystallization.
Abstract: Web usage mining is an interesting application of data
mining which provides insight into customer behaviour on the Internet. An important technique to discover user access and navigation trails is based on sequential patterns mining. One of the
key challenges for web access patterns mining is tackling the problem
of mining richly structured patterns. This paper proposes a novel
model called Web Access Patterns Graph (WAP-Graph) to represent all of the access patterns from web mining graphically. WAP-Graph
also motivates the search for new structural relation patterns, i.e. Concurrent Access Patterns (CAP), to identify and predict more
complex web page requests. Corresponding CAP mining and modelling methods are proposed and shown to be effective in the
search for and representation of concurrency between access patterns
on the web. From experiments conducted on large-scale synthetic
sequence data as well as real web access data, it is demonstrated that
CAP mining provides a powerful method for structural knowledge discovery, which can be visualised through the CAP-Graph model.
Abstract: Opinion extraction about products from customer
reviews is becoming an interesting area of research. Customer
reviews about products are nowadays available from blogs and
review sites. Also tools are being developed for extraction of opinion
from these reviews to help the user as well merchants to track the
most suitable choice of product. Therefore efficient method and
techniques are needed to extract opinions from review and blogs. As
reviews of products mostly contains discussion about the features,
functions and services, therefore, efficient techniques are required to
extract user comments about the desired features, functions and
services. In this paper we have proposed a novel idea to find features
of product from user review in an efficient way. Our focus in this
paper is to get the features and opinion-oriented words about
products from text through auxiliary verbs (AV) {is, was, are, were,
has, have, had}. From the results of our experiments we found that
82% of features and 85% of opinion-oriented sentences include AVs.
Thus these AVs are good indicators of features and opinion
orientation in customer reviews.
Abstract: A new target detection technique is presented in this
paper for the identification of small boats in coastal surveillance. The
proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any
objects present in the scene from the background. The preprocessing
step results in an image having only the foreground objects, such as
boats, trees and other cluttered regions, and hence reduces the search
region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform
correlator (SPFJTC) technique which produces single and delta-like
correlation peak for a potential target present in the input scene. A
post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the
proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.
Abstract: This paper presents a part of research on the
rheological properties of bitumen modified by thermoplastic namely
linear low density polyethylene (LLDPE), high density polyethylene
(HDPE) and polypropylene (PP) and its interaction with 80 pen base
bitumen. As it is known that the modification of bitumen by the use
of polymers enhances its performance characteristics but at the same
time significantly alters its rheological properties. The rheological
study of polymer modified bitumen (PMB) was made through
penetration, ring & ball softening point and viscosity test. The results
were then related to the changes in the rheological properties of
polymer modified bitumen. It was observed that thermoplastic
copolymer shows profound effect on penetration rather than
softening point. The viscoelastic behavior of polymer modified
bitumen depend on the concentration of polymer, mixing
temperature, mixing technique, solvating power of base bitumen and
molecular structure of polymer used. PP offer better blend in
comparison to HDPE and LLDPE. The viscosity of base bitumen was
also enhanced with the addition of polymer. The pseudoplastic
behavior was more prominent for HDPE and LLDPE than PP. Best
results were obtained when polymer concentration was kept below
3%
Abstract: In this article we explore how computer assisted exercises may allow for bridging the traditional gap between theory and practice in professional education. To educate officers able to master the complexity of the battlefield the Norwegian Military Academy needs to develop a learning environment that allows for creating viable connections between the educational environment and the field of practice. In response to this challenge we explore the conditions necessary to make computer assisted training systems (CATS) a useful tool to create structural similarities between an educational context and the field of military practice. Although, CATS may facilitate work procedures close to real life situations, this case do demonstrate how professional competence also must build on viable learning theories and environments. This paper explores the conditions that allow for using simulators to facilitate professional competence from within an educational setting. We develop a generic didactic model that ascribes learning to participation in iterative cycles of action and reflection. The development of this model is motivated by the need to develop an interdisciplinary professional education rooted in the pattern of military practice.
Abstract: During recent years, the traditional learning
approaches have undergone fundamental changes due to the
emergence of new technologies such as multimedia, hypermedia and
telecommunication. E-learning is a modern world phenomenon that
has come into existence in the information age and in a knowledgebased
society. E-learning has developed significantly within a short
period of time. Thus it is of a great significant to secure information,
allow a confident access and prevent unauthorized accesses. Making
use of individuals- physiologic or behavioral (biometric) properties is
a confident method to make the information secure. Among the
biometrics, fingerprint is more acceptable and most countries use it as
an efficient methods of identification. This article provides a new
method to compare the fingerprint comparison by pattern recognition
and image processing techniques. To verify fingerprint, the shortest
distance method is used together with perceptronic multilayer neural
network functioning based on minutiae. This method is highly
accurate in the extraction of minutiae and it accelerates comparisons
due to elimination of false minutiae and is more reliable compared
with methods that merely use directional images.
Abstract: In the present study, the effect of ferrous sulfate concentration and total solids on bioleaching of heavy metals from sewage sludge has been examined using indigenous iron-oxidizing microorganisms. The experiments on effects of ferrous sulfate concentrations on bioleaching were carried out using ferrous sulfate of different concentrations (5-20 g L-1) to optimize the concentration of ferrous sulfate for maximum bioleaching. A rapid change in the pH and ORP took place in first 2 days followed by a slow change till 16th day in all the sludge samples. A 10 g L-1 ferrous sulfate concentration was found to be sufficient in metal bioleaching in the following order: Zn: 69%>Cu: 52%>Cr: 46%>Ni: 45. Further, bioleaching using 10 g/L ferrous sulfate was found to be efficient up to 20 g L-1 sludge solids concentration. The results of the present study strongly indicate that using 10 g L-1 ferrous sulfate indigenous iron-oxidizing microorganisms can bring down pH to a value needed for significant metal solubilization.
Abstract: The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.
Abstract: Fundamental sensor-motor couplings form the backbone
of most mobile robot control tasks, and often need to be implemented
fast, efficiently and nevertheless reliably. Machine learning
techniques are therefore often used to obtain the desired sensor-motor
competences.
In this paper we present an alternative to established machine
learning methods such as artificial neural networks, that is very fast,
easy to implement, and has the distinct advantage that it generates
transparent, analysable sensor-motor couplings: system identification
through nonlinear polynomial mapping.
This work, which is part of the RobotMODIC project at the
universities of Essex and Sheffield, aims to develop a theoretical understanding
of the interaction between the robot and its environment.
One of the purposes of this research is to enable the principled design
of robot control programs.
As a first step towards this aim we model the behaviour of the
robot, as this emerges from its interaction with the environment, with
the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving
Average models with eXogenous inputs). This method produces
explicit polynomial functions that can be subsequently analysed using
established mathematical methods.
In this paper we demonstrate the fidelity of the obtained NARMAX
models in the challenging task of robot route learning; we present a
set of experiments in which a Magellan Pro mobile robot was taught
to follow four different routes, always using the same mechanism to
obtain the required control law.
Abstract: Concerning the measurement of friction properties of
textiles and fabrics using Kawabata Evaluation System (KES), whose
output is constrained to the surface friction factor of fabric, and no
other data would be generated; this research has been conducted to
gain information about surface roughness regarding its surface
friction factor. To assess roughness properties of light nonwovens, a
3-dimensional model of a surface has been simulated with regular
sinuous waves through it as an ideal surface. A new factor was
defined, namely Surface Roughness Factor, through comparing
roughness properties of simulated surface and real specimens. The
relation between the proposed factor and friction factor of specimens
has been analyzed by regression, and results showed a meaningful
correlation between them. It can be inferred that the new presented
factor can be used as an acceptable criterion for evaluating the
roughness properties of light nonwoven fabrics.
Abstract: This paper proposes and analyses the wireless
telecommunication system with multiple antennas to the emission
and reception MIMO (multiple input multiple output) with space
diversity in a OFDM context. In particular it analyses the
performance of a DTT (Digital Terrestrial Television) broadcasting
system that includes MIMO-OFDM techniques. Different
propagation channel models and configurations are considered for
each diversity scheme. This study has been carried out in the context
of development of the next generation DVB-T/H and WRAN.
Abstract: The use of new technologies such internet (e-mail, chat
rooms) and cell phones has steeply increased in recent years.
Especially among children and young people, use of technological
tools and equipments is widespread. Although many teachers and
administrators now recognize the problem of school bullying, few are
aware that students are being harassed through electronic
communication. Referred to as electronic bullying, cyber bullying, or
online social cruelty, this phenomenon includes bullying through email,
instant messaging, in a chat room, on a website, or through
digital messages or images sent to a cell phone. Cyber bullying is
defined as causing deliberate/intentional harm to others using internet
or other digital technologies. It has a quantitative research design nd
uses relational survey as its method. The participants consisted of
300 secondary school students in the city of Konya, Turkey. 195
(64.8%) participants were female and 105 (35.2%) were male. 39
(13%) students were at grade 1, 187 (62.1%) were at grade 2 and 74
(24.6%) were at grade 3. The “Cyber Bullying Question List"
developed by Ar─▒cak (2009) was given to students. Following
questions about demographics, a functional definition of cyber
bullying was provided. In order to specify students- human values,
“Human Values Scale (HVS)" developed by Dilmaç (2007) for
secondary school students was administered. The scale consists of 42
items in six dimensions. Data analysis was conducted by the primary
investigator of the study using SPSS 14.00 statistical analysis
software. Descriptive statistics were calculated for the analysis of
students- cyber bullying behaviour and simple regression analysis was
conducted in order to test whether each value in the scale could
explain cyber bullying behaviour.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: The study investigated the effects of Teaching Games
for Understanding approach on students ‘cognitive learning outcome.
The study was a quasi-experimental non-equivalent pretest-posttest
control group design whereby 10 year old primary school students
(n=72) were randomly assigned to an experimental and a control
group. The experimental group students were exposed with TGfU
approach and the control group with the Traditional Skill approach of
handball game. Game Performance Assessment Instrument (GPAI)
was used to measure students' tactical understanding and decision
making in 3 versus 3 handball game situations. Analysis of
covariance (ANCOVA) was used to analyze the data. The results
reveal that there was a significant difference between the TGfU
approach group and the traditional skill approach group students on
post test score (F (1, 69) = 248.83, p < .05). The findings of this
study suggested the importance of TGfU approach to improve
primary students’ tactical understanding and decision making in
handball game.
Abstract: Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.
Abstract: The aim of this study is to find out and analyze the
role of gender and age on the perceptions of students to the distant
online program offered by Vocational High School in Sakarya
University. The research is based on a questionnaire as a mean of
data collection method to find out the role of age and gender on the
student-s perceptions toward online education, and the study
progressed through finding relationships between the variables used
in the data collection instrument. The findings of the analysis
revealed that although the students registered to the online program
by will, they preferred the traditional face-to-face education due to
the difficulty of the nonverbal communication, their incompetence of
using the technology required, and their belief in traditional face-toface
learning more than online education.
Regarding gender, the results showed that the female students
have a better perception of the online education as opposed to the
male students. Regarding age, the results showed that the older the
students are the more is their preference towards attending face-toface
classes.