Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.
Abstract: By textile science incorporating with electronic
industry, developed textile products start to take part in different
areas such as industry, military, space, medical etc. for health,
protection, defense, communication and automation. Electronic
textiles (e-textiles) are fabrics that contain electronics and
interconnections with them. In this study, two types of base yarns
(cotton and acrylic) and three types of conductive steel yarns with
different linear resistance values (14Ω/m, 30Ω/m, 70Ω/m) were used
to investigate the effect of base yarn type and linear resistance of
conductive yarns on thermal behavior of e-textile structures. Thermal
behavior of samples was examined by thermal camera.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: We investigate relaxation dynamics of a quantum
dipole emitter (QDE), e.g., a molecule or quantum dot, located near a
metal nanoparticle (MNP) exhibiting a dipolar localized surface
plasmon (LSP) resonance at the frequency of the QDE radiative
transition. It is shown that under the condition of the QDE-MNP
characteristic relaxation time being much shorter than that of the
QDE in free-space but much longer than the LSP lifetime. It is also
shown that energy dissipation in the QDE-MNP system is relatively
weak with the probability of the photon emission being about 0.75, a
number which, rather surprisingly, does not explicitly depend on the
metal absorption characteristics. The degree of entanglement
measured by the concurrency takes the maximum value, while the
distances between the QDEs and metal ball approximately are equal.
Abstract: Subspace channel estimation methods have been
studied widely, where the subspace of the covariance matrix is
decomposed to separate the signal subspace from noise subspace. The
decomposition is normally done by using either the eigenvalue
decomposition (EVD) or the singular value decomposition (SVD) of
the auto-correlation matrix (ACM). However, the subspace
decomposition process is computationally expensive. This paper
considers the estimation of the multipath slow frequency hopping
(FH) channel using noise space based method. In particular, an
efficient method is proposed to estimate the multipath time delays by
applying multiple signal classification (MUSIC) algorithm which is
based on the null space extracted by the rank revealing LU (RRLU)
factorization. As a result, precise information is provided by the
RRLU about the numerical null space and the rank, (i.e., important
tool in linear algebra). The simulation results demonstrate the
effectiveness of the proposed novel method by approximately
decreasing the computational complexity to the half as compared
with RRQR methods keeping the same performance.
Abstract: The number of persons with implanted cardiac
pacemakers (PM) has increased in Western countries. The aim of this
paper is to investigate the possible situations where persons with a
PM may be exposed to extremely low frequency (ELF) electric (EF)
and magnetic fields (MF) that may disturb their PM. Based on our
earlier studies, it is possible to find such high public exposure to EFs
only in some places near 400 kV power lines, where an EF may
disturb a PM in unipolar mode. Such EFs cannot be found near 110
kV power lines. Disturbing MFs can be found near welding
machines. However, we do not have measurement data from welding.
Based on literature and earlier studies at Tampere University of
Technology, it is difficult to find public EF or MF exposure that is
high enough to interfere with PMs.
Abstract: The textile industry plays a major role in the economy
of India and on the other side of the coin it is the major source for
water pollution. As azo dyes is the largest dye class they are
extensively used in many fields such as textile industry, leather
tanning industry, paper production, food, color photography,
pharmaceuticals and medicine, cosmetic, hair colorings, wood
staining, agricultural, biological and chemical research etc. In
addition to these, they can have acute and/or chronic effects on
organisms depending on their concentration and length of exposure
when they discharged as effluent in the environment. The aim of this
study was to assess the genotoxic and histotoxic potentials of
environmentally relevant concentrations of C. I. Reactive Red 120
(RR 120) on Catla catla, important edible freshwater fingerlings. For
this, healthy Catla catla fingerlings were procured from the
Government Fish Farm and acclimatized in 100 L capacity and
continuously aerated glass aquarium in laboratory for 15 days.
According to APHA some physic-chemical parameters were
measured and maintained such as temperature, pH, dissolve oxygen,
alkalinity, total hardness. Water along with excreta had been changed
every 24 hrs. All fingerlings were fed artificial food palates once a
day @ body weight. After 15 days fingerlings were grouped in 5 (10
in each) and exposed to various concentrations of RR 120 (Control,
10, 20, 30 and 40 mg.l-1) and samples (peripheral blood and gills,
kidney) were collected and analyzed at 96 hrs. All results were
compared with the control. Micronuclei (MN), nuclear buds (NB),
fragmented-apoptotic (FA) and bi-nucleated (BN) cells in blood
smears and in tissues (gills and kidney cells) were observed.
Prominent histopathological alterations were noticed in gills such as
aneurism, hyperplasia, degenerated central axis, lifting of gill
epithelium, curved secondary gill lamellae etc. Similarly kidney
showed some detrimental changes like shrunken glomeruli with
increased periglomerular space, degenerated renal tubules etc. Both
haematological and histopathological changes clearly reveal the toxic
potential of RR 120. This work concludes that water pollution
assessment can be done by these two biomarkers which provide
baseline to the further chromosomal or molecular work.
Abstract: Taking into account the significance of measuring the
daily use of the study space in the libraries in order to develop and
reorganize the space for enhancing the efficiency of the study space,
the current study aimed to apply GIS in analyzing the study halls of
the Central Library and Document Center of Tehran University in
order to determine how study desks and chairs were used by the
students. The study used a combination of survey-descriptive and
system design method. In order to gather the required data, surveydescriptive
method was used. For implementing and entering data
into ArcGIS and analyzing the data and displaying the results on the
maps of the study halls of the library, system design method was
utilized. The design of the spatial database of the use of the study
halls was measured through the extent of occupancy of the space by
the library users and the maps of the study halls of the central library
of Tehran University as the case study. The results showed that
Abooreyhan hall had the highest rate of occupancy of the desks and
chairs compared to the other halls. The Hall of Science and
Technology, with an average occupancy rate of 0.39 for the tables
represented the lowest number of users and Rashid al-Dins hall, and
Science and Technology hall with an average occupancy rate (0.40)
had the lowest number of users for seats. In this study, the
comparison of the space occupied at different periods in the morning,
evenings, afternoons, and several months was performed through
GIS. This system analyzed the space relationships effectively and
efficiently. The output of this study would be used by administrators
and librarians to determine the exact extent of use of the equipment
of the study halls and librarians can use the output map to design the
space more efficiently at the library.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Abstract: Applications of the Hausdorff space and its mappings
into tangent spaces are outlined, including their fractal dimensions
and self-similarities. The paper details this theory set up and further
describes virtualizations and atomization of manufacturing processes.
It demonstrates novel concurrency principles that will guide
manufacturing processes and resources configurations. Moreover,
varying levels of details may be produced by up folding and breaking
down of newly introduced generic models. This choice of layered
generic models for units and systems aspects along specific aspects
allows research work in parallel to other disciplines with the same
focus on all levels of detail. More credit and easier access are granted
to outside disciplines for enriching manufacturing grounds. Specific
mappings and the layers give hints for chances for interdisciplinary
outcomes and may highlight more details for interoperability
standards, as already worked on the international level. The new rules
are described, which require additional properties concerning all
involved entities for defining distributed decision cycles, again on the
base of self-similarity. All properties are further detailed and assigned
to a maturity scale, eventually displaying the smartness maturity of a
total shopfloor or a factory. The paper contributes to the intensive
ongoing discussion in the field of intelligent distributed
manufacturing and promotes solid concepts for implementations of
Cyber Physical Systems and the Internet of Things into
manufacturing industry, like industry 4.0, as discussed in German-speaking
countries.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: Modeling and forecasting dynamics of rainfall
occurrences constitute one of the major topics, which have been
largely treated by statisticians, hydrologists, climatologists and many
other groups of scientists. In the same issue, we propose, in the
present paper, a new hybrid method, which combines Extreme
Values and fractal theories. We illustrate the use of our methodology
for transformed Emberger Index series, constructed basing on data
recorded in Oujda (Morocco).
The index is treated at first by Peaks Over Threshold (POT)
approach, to identify excess observations over an optimal threshold u.
In the second step, we consider the resulting excess as a fractal object
included in one dimensional space of time. We identify fractal
dimension by the box counting. We discuss the prospect descriptions
of rainfall data sets under Generalized Pareto Distribution, assured by
Extreme Values Theory (EVT). We show that, despite of the
appropriateness of return periods given by POT approach, the
introduction of fractal dimension provides accurate interpretation
results, which can ameliorate apprehension of rainfall occurrences.
Abstract: Machining of hard materials is a recent technology for
direct production of work-pieces. The primary challenge in
machining these materials is selection of cutting tool inserts which
facilitates an extended tool life and high-precision machining of the
component. These materials are widely for making precision parts for
the aerospace industry. Nickel-based alloys are typically used in
extreme environment applications where a combination of strength,
corrosion resistance and oxidation resistance material characteristics
are required. The present paper reports the theoretical and
experimental investigations carried out to understand the influence of
machining parameters on the response parameters. Considering the
basic machining parameters (speed, feed and depth of cut) a study has
been conducted to observe their influence on material removal rate,
surface roughness, cutting forces and corresponding tool wear.
Experiments are designed and conducted with the help of Central
Composite Rotatable Design technique. The results reveals that for a
given range of process parameters, material removal rate is favorable
for higher depths of cut and low feed rate for cutting forces. Low feed
rates and high values of rotational speeds are suitable for better finish
and higher tool life.
Abstract: The Al-MoO3-P-CdTe-Al MOS sandwich structures
were fabricated by vacuum deposition method on cleaned glass
substrates. Capacitance versus voltage measurements were performed
at different frequencies and sweep rates of applied voltages for oxide
and semiconductor films of different thicknesses. In the negative
voltage region of the C-V curve a high differential capacitance of the
semiconductor was observed and at high frequencies (
Abstract: In this paper we present the efficient parallel
implementation of elastoplastic problems based on the TFETI (Total
Finite Element Tearing and Interconnecting) domain decomposition
method. This approach allow us to use parallel solution and compute
this nonlinear problem on the supercomputers and decrease the
solution time and compute problems with millions of DOFs. In
our approach we consider an associated elastoplastic model with
the von Mises plastic criterion and the combination of linear
isotropic-kinematic hardening law. This model is discretized by
the implicit Euler method in time and by the finite element
method in space. We consider the system of nonlinear equations
with a strongly semismooth and strongly monotone operator. The
semismooth Newton method is applied to solve this nonlinear
system. Corresponding linearized problems arising in the Newton
iterations are solved in parallel by the above mentioned TFETI. The
implementation of this problem is realized in our in-house MatSol
packages developed in MatLab.
Abstract: In this paper we are presenting some spamming
techniques their behaviour and possible solutions. We have analyzed
how Spammers enters into online social networking sites (OSNSs) to
target them and diverse techniques used by them for this purpose.
Spamming is very common issue in present era of Internet
especially through Online Social Networking Sites (like Facebook,
Twitter, and Google+ etc.). Spam messages keep wasting Internet
bandwidth and the storage space of servers. On social networking
sites; spammers often disguise themselves by creating fake accounts
and hijacking user’s accounts for personal gains. They behave like
normal user and they continue to change their spamming strategy.
Following spamming techniques are discussed in this paper like
clickjacking, social engineered attacks, cross site scripting, URL
shortening, and drive by download. We have used elgg framework
for demonstration of some of spamming threats and respective
implementation of solutions.
Abstract: This work deals with parameter identification of
permanent magnet motors, a class of ac motor which is particularly
important in industrial automation due to characteristics like
applications high performance, are very attractive for applications
with limited space and reducing the need to eliminate because they
have reduced size and volume and can operate in a wide speed range,
without independent ventilation. By using experimental data and
genetic algorithm we have been able to extract values for both the
motor inductance and the electromechanical coupling constant, which
are then compared to measured and/or expected values.
Abstract: In this paper, the problem of fault detection and
isolation in the attitude control subsystem of spacecraft formation
flying is considered. In order to design the fault detection method, an
extended Kalman filter is utilized which is a nonlinear stochastic state
estimation method. Three fault detection architectures, namely,
centralized, decentralized, and semi-decentralized are designed based
on the extended Kalman filters. Moreover, the residual generation
and threshold selection techniques are proposed for these
architectures.