Abstract: In this paper, a direct power control (DPC)
strategies have been investigated in order to control a high
power AC/DC converter with time variable load. This converter
is composed of a three level three phase neutral point clamped
(NPC) converter as rectifier and an H-bridge four quadrant
current control converter. In the high power application,
controller not only must adjust the desire outputs but also
decrease the level of distortions which are injected to the network
from the converter. Regarding to this reason and nonlinearity
of the power electronic converter, the conventional controllers
cannot achieve appropriate responses. In this research, the
precise mathematical analysis has been employed to design the
appropriate controller in order to control the time variable
load. A DPC controller has been proposed and simulated using
Matlab/ Simulink. In order to verify the simulation result, a real
time simulator- OPAL-RT- has been employed. In this paper,
the dynamic response and stability of the high power NPC
with variable load has been investigated and compared with
conventional types using a real time simulator. The results proved
that the DPC controller is more stable and has more precise
outputs in comparison with conventional controller.
Abstract: An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.
Abstract: The adaptation of social networking sites within
higher education has garnered significant interest in the recent years
with numerous researches considering it as a possible shift from the
traditional classroom based learning paradigm. Notwithstanding this
increase in research and conducted studies however, the adaption of
SNS based modules have failed to proliferate within Universities.
This paper commences its contribution by analyzing the various
models and theories proposed in literature and amalgamate together
various effective aspects for the inclusion of social technology within
e-Learning. A three phased framework is further proposed which
details the necessary considerations for the successful adaptation of
SNS in enhancing the students learning experience. This proposal
outlines the theoretical foundations which will be analyzed in
practical implementation across international university campuses.
Abstract: Wireless Sensor Networks (WSNs) have wide variety
of applications and provide limitless future potentials. Nodes in
WSNs are prone to failure due to energy depletion, hardware failure,
communication link errors, malicious attacks, and so on. Therefore,
fault tolerance is one of the critical issues in WSNs. We study how
fault tolerance is addressed in different applications of WSNs. Fault
tolerant routing is a critical task for sensor networks operating in
dynamic environments. Many routing, power management, and data
dissemination protocols have been specifically designed for WSNs
where energy awareness is an essential design issue. The focus,
however, has been given to the routing protocols which might differ
depending on the application and network architecture.
Abstract: Cloud computing is a new technology in industry and
academia. The technology has grown and matured in last half decade
and proven their significant role in changing environment of IT
infrastructure where cloud services and resources are offered over the
network. Cloud technology enables users to use services and
resources without being concerned about the technical implications of
technology. There are substantial research work has been performed
for the usage of cloud computing in educational institutes and
majority of them provides cloud services over high-end blade servers
or other high-end CPUs. However, this paper proposes a new stack
called “CiCKAStack” which provide cloud services over unutilized
computing resources, named as commodity computers.
“CiCKAStack” provides IaaS and PaaS using underlying commodity
computers. This will not only increasing the utilization of existing
computing resources but also provide organize file system, on
demand computing resource and design and development
environment.
Abstract: Today’s VLSI networks demands for high speed. And
in this work the compact form mathematical model for current mode
signalling in VLSI interconnects is presented.RLC interconnect line
is modelled using characteristic impedance of transmission line and
inductive effect. The on-chip inductance effect is dominant at lower
technology node is emulated into an equivalent resistance. First order
transfer function is designed using finite difference equation, Laplace
transform and by applying the boundary conditions at the source and
load termination. It has been observed that the dominant pole
determines system response and delay in the proposed model. The
novel proposed current mode model shows superior performance as
compared to voltage mode signalling. Analysis shows that current
mode signalling in VLSI interconnects provides 2.8 times better
delay performance than voltage mode. Secondly the damping factor
of a lumped RLC circuit is shown to be a useful figure of merit.
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: Recently, the competition between websites becomes
intense. How to make users “adopt” their websites is an issue of urgent
importance for online communities companies. Social procedures
(such as social influence) can possibly explain how and why users’
technologies usage behaviors affect other people to use the
technologies. This study proposes two types of social influences on the
initial usage of Facebook Check In-friends and group members.
Besides, this study combines social influences theory and social
network theory to explore the factors influencing initial usage of
Facebook Check In. This study indicates that Facebook friends’
previous usage of Facebook Check In and Facebook group members’
previous usage of Facebook Check In will positively influence focal
actors’ Facebook Check In adoption intention, and network centrality
will moderate the relationships among Facebook friends’ previous
usage of Facebook Check In, Facebook group members’ previous
usage of Facebook Check In and focal actors’ Facebook Check In
adoption intention. The article concludes with contributions to
academic research and practice.
Abstract: Nature is the immense gifted source for solving
complex problems. It always helps to find the optimal solution to
solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide
research area of networks which has set of independent nodes. The
characteristics involved in MANET’s are Dynamic, does not depend
on any fixed infrastructure or centralized networks, High mobility.
The Bio-Inspired algorithms are mimics the nature for solving
optimization problems opening a new era in MANET. The typical
Swarm Intelligence (SI) algorithms are Ant Colony Optimization
(ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization
(PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf
Search Algorithm (WSA) and so on. This work mainly concentrated
on nature of MANET and behavior of nodes. Also it analyses various
performance metrics such as throughput, QoS and End-to-End delay
etc.
Abstract: In a multi-cultural learning context, where ties are
weak and dynamic, combining qualitative with quantitative research
methods may be more effective. Such a combination may also allow
us to answer different types of question, such as about people’s
perception of the network. In this study the use of observation,
interviews and photos were explored as ways of enhancing data from
social network questionnaires. Integrating all of these methods was
found to enhance the quality of data collected and its accuracy, also
providing a richer story of the network dynamics and the factors that
shaped these changes over time.
Abstract: The effects of hypertension are often lethal thus its
early detection and prevention is very important for everybody. In
this paper, a neural network (NN) model was developed and trained
based on a dataset of hypertension causative parameters in order to
forecast the likelihood of occurrence of hypertension in patients. Our
research goal was to analyze the potential of the presented NN to
predict, for a period of time, the risk of hypertension or the risk of
developing this disease for patients that are or not currently
hypertensive. The results of the analysis for a given patient can
support doctors in taking pro-active measures for averting the
occurrence of hypertension such as recommendations regarding the
patient behavior in order to lower his hypertension risk. Moreover,
the paper envisages a set of three example scenarios in order to
determine the age when the patient becomes hypertensive, i.e.
determine the threshold for hypertensive age, to analyze what
happens if the threshold hypertensive age is set to a certain age and
the weight of the patient if being varied, and, to set the ideal weight
for the patient and analyze what happens with the threshold of
hypertensive age.
Abstract: Electronic Word-Of-Mouth (eWOM) communities
represent today an important source of information in which more
and more customers base their purchasing decisions. They include
thousands of reviews concerning very different products and services
posted by many individuals geographically distributed all over the
world. Due to their massive audience, eWOM communities can help
users to find the product they are looking for even if they are less
popular or rare. This is known as the long tail effect, which leads to a
larger number of lower-selling niche products. This paper analyzes
the long tail effect in a well-known eWOM community and defines a
tool for finding niche products unavailable through conventional
channels.
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: Despite the highly touted benefits, emerging
technologies have unleashed pervasive concerns regarding unintended
and unforeseen social impacts. Thus, those wishing to create safe and
socially acceptable products need to identify such side effects and
mitigate them prior to the market proliferation. Various methodologies
in the field of technology assessment (TA), namely Delphi, impact
assessment, and scenario planning, have been widely incorporated in
such a circumstance. However, literatures face a major limitation in
terms of sole reliance on participatory workshop activities. They
unfortunately missed out the availability of a massive untapped data
source of futuristic information flooding through the Internet. This
research thus seeks to gain insights into utilization of futuristic data,
future-oriented documents from the Internet, as a supplementary
method to generate social impact scenarios whilst capturing
perspectives of experts from a wide variety of disciplines. To this end,
network analysis is conducted based on the social keywords extracted
from the futuristic documents by text mining, which is then used as a
guide to produce a comprehensive set of detailed scenarios. Our
proposed approach facilitates harmonized depictions of possible
hazardous consequences of emerging technologies and thereby makes
decision makers more aware of, and responsive to, broad qualitative
uncertainties.
Abstract: In the framework of the modernization of the city of
Constantine and in order to restore its status as a regional metropolis
introducing it into the network of cities international metropolises,
has major urban project was launched: project of modernization and
of metropolitanization of the city of Constantine.
Our research project focuses on the management of the project for
the modernization of the city of Constantine (PMMC) focusing on
the management of some aspects of the urban project whose
participation, with the objective assessment of the managerial
approach business.
In this contribution, we focus on two cases revealing taken into
account in our research work on the question of participation of
actors and their organizations. It is "the urban project of
modernization of Constantine" and the operation relating to "the
urban improvement in the city of the Brothers FERRAD in the
district of Zouaghi". This project and this operation with the objective
of improving the living conditions of citizens have faced several
challenges and obstacles that have been in major part the factors of its
failures.
Through this study, we examined the management process and the
mode of organization of the actors of the project as well as the level
of participation of the citizen to finally proposed managerial solutions
toconflict situations observed.
Abstract: This paper analyzes the political and economic issues
that people with disabilities face related to globalization; how people
with disabilities have been adapting globalization and surviving under
worldwide competition system. It explains that economic
globalization exacerbates inequality and deprivation of people with
disabilities. The rising tide of neo-liberal welfare policies emphasized
efficiency, downsized social expenditure for people with disabilities,
excluded people with disabilities against labor market, and shifted
them from welfare system to nothing. However, there have been
people with disabilities' political responses to globalization, which are
characterized by a global network of people with disabilities as well as
participation to global governance. Their resistance can be seen as an
attempt to tackle the problems that economic globalization has
produced. It is necessary paradigm shift of disability policy from
dependency represented by disability benefits to independency
represented by labor market policies for people with disabilities.
Abstract: Future mobile networks following 5th generation will
be characterized by one thousand times higher gains in capacity;
connections for at least one hundred billion devices; user experience
capable of extremely low latency and response times. To be close to
the capacity requirements and higher reliability, advanced
technologies have been studied, such as multiple connectivity, small
cell enhancement, heterogeneous networking, and advanced
interference and mobility management. This paper is focused on the
multiple connectivity in heterogeneous cellular networks. We
investigate the performance of coverage and user throughput in several
deployment scenarios. Using the stochastic geometry approach, the
SINR distributions and the coverage probabilities are derived in case
of dual connection. Also, to compare the user throughput enhancement
among the deployment scenarios, we calculate the spectral efficiency
and discuss our results.
Abstract: IEEE 802.11a/b/g standards provide multiple
transmission rates, which can be changed dynamically according to the
channel condition. Cooperative communications were introduced to
improve the overall performance of wireless LANs with the help of
relay nodes with higher transmission rates. The cooperative
communications are based on the fact that the transmission is much
faster when sending data packets to a destination node through a relay
node with higher transmission rate, rather than sending data directly to
the destination node at low transmission rate. To apply the cooperative
communications in wireless LAN, several MAC protocols have been
proposed. Some of them can result in collisions among relay nodes in a
dense network. In order to solve this problem, we propose a new
protocol. Relay nodes are grouped based on their transmission rates.
And then, relay nodes only in the highest group try to get channel
access. Performance evaluation is conducted using simulation, and
shows that the proposed protocol significantly outperforms the
previous protocol in terms of throughput and collision probability.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.