Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.
Abstract: In recent years parasitic antenna play major role in
MIMO systems because of their gain and spectral efficiency. In this
paper, single RF chain MIMO transmitter is designed using
reconfigurable parasitic antenna. The Spatial Modulation (SM) is a
recently proposed scheme in MIMO scenario which activates only
one antenna at a time. The SM entirely avoids ICI and IAS, and only
requires a single RF chain at the transmitter. This would switch ON a
single transmit-antenna for data transmission while all the other
antennas are kept silent. The purpose of the parasitic elements is to
change the radiation pattern of the radio waves which is emitted from
the driven element and directing them in one direction and hence
introduces transmit diversity. Diode is connect between the patch and
ground by changing its state (ON and OFF) the parasitic element act
as reflector and director and also capable of steering azimuth and
elevation angle. This can be achieved by changing the input
impedance of each parasitic element through single RF chain. The
switching of diode would select the single parasitic antenna for
spatial modulation. This antenna is expected to achieve maximum
gain with desired efficiency.
Abstract: Customer churn prediction is one of the most useful
areas of study in customer analytics. Due to the enormous amount
of data available for such predictions, machine learning and data
mining have been heavily used in this domain. There exist many
machine learning algorithms directly applicable for the problem of
customer churn prediction, and here, we attempt to experiment on
a novel approach by using a cognitive learning based technique in
an attempt to improve the results obtained by using a combination
of supervised learning methods, with cognitive unsupervised learning
methods.
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: Offering a Product-Service System (PSS) is a
well-accepted strategy that companies may adopt to provide a set of
systemic solutions to customers. PSSs were initially provided in a
simple form but now take diversified and complex forms involving
multiple services, products and technologies. With the growing
interest in the PSS, frameworks for the PSS development have been
introduced by many researchers. However, most of the existing
frameworks fail to examine various relations existing in a complex
PSS. Since designing a complex PSS involves full integration of
multiple products and services, it is essential to identify not only
product-service relations but also product-product/ service-service
relations. It is also equally important to specify how they are related
for better understanding of the system. Moreover, as customers tend to
view their purchase from a more holistic perspective, a PSS should be
developed based on the whole system’s requirements, rather than
focusing only on the product requirements or service requirements.
Thus, we propose a framework to develop a complex PSS that is
coordinated fully with the requirements of both worlds. Specifically,
our approach adopts a multi-domain matrix (MDM). A MDM
identifies not only inter-domain relations but also intra-domain
relations so that it helps to design a PSS that includes highly desired
and closely related core functions/ features. Also, various dependency
types and rating schemes proposed in our approach would help the
integration process.
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: This paper describes the problem of building secure
computational services for encrypted information in the Cloud
Computing without decrypting the encrypted data; therefore, it meets
the yearning of computational encryption algorithmic aspiration
model that could enhance the security of big data for privacy,
confidentiality, availability of the users. The cryptographic model
applied for the computational process of the encrypted data is the
Fully Homomorphic Encryption Scheme. We contribute a theoretical
presentations in a high-level computational processes that are based
on number theory and algebra that can easily be integrated and
leveraged in the Cloud computing with detail theoretic mathematical
concepts to the fully homomorphic encryption models. This
contribution enhances the full implementation of big data analytics
based cryptographic security algorithm.
Abstract: Game theory is the study of how people interact and
make decisions to handle competitive situations. It has mainly been
developed to study decision making in complex situations. Humans
routinely alter their behaviour in response to changes in their social
and physical environment. As a consequence, the outcomes of
decisions that depend on the behaviour of multiple decision makers
are difficult to predict and require highly adaptive decision-making
strategies. In addition to the decision makers may have preferences
regarding consequences to other individuals and choose their actions
to improve or reduce the well-being of others. Nash equilibrium is a
fundamental concept in the theory of games and the most widely used
method of predicting the outcome of a strategic interaction in the
social sciences. A Nash Equilibrium exists when there is no unilateral
profitable deviation from any of the players involved. On the other
hand, no player in the game would take a different action as long as
every other player remains the same.
Abstract: Due to the rapid increase of Internet, web opinion
sources dynamically emerge which is useful for both potential
customers and product manufacturers for prediction and decision
purposes. These are the user generated contents written in natural
languages and are unstructured-free-texts scheme. Therefore, opinion
mining techniques become popular to automatically process customer
reviews for extracting product features and user opinions expressed
over them. Since customer reviews may contain both opinionated and
factual sentences, a supervised machine learning technique applies
for subjectivity classification to improve the mining performance. In
this paper, we dedicate our work is the task of opinion
summarization. Therefore, product feature and opinion extraction is
critical to opinion summarization, because its effectiveness
significantly affects the identification of semantic relationships. The
polarity and numeric score of all the features are determined by
Senti-WordNet Lexicon. The problem of opinion summarization
refers how to relate the opinion words with respect to a certain
feature. Probabilistic based model of supervised learning will
improve the result that is more flexible and effective.
Abstract: A new concept of response system is proposed for
filling the gap that exists in reducing vulnerability during immediate
response to natural disasters. Real Time Early Response Systems
(RTERSs) incorporate real time information as feedback data for
closing control loop and for generating real time situation assessment.
A review of the state of the art on works that fit the concept of
RTERS is presented, and it is found that they are mainly focused on
manmade disasters. At the same time, in response phase of natural
disaster management many works are involved in creating early
warning systems, but just few efforts have been put on deciding what
to do once an alarm is activated. In this context a RTERS arises as a
useful tool for supporting people in their decision making process
during natural disasters after an event is detected, and also as an
innovative context for applying well-known automation technologies
and automatic control concepts and tools.
Abstract: Formal verification is proposed to ensure the
correctness of the design and make functional verification more
efficient. As cache plays a vital role in the design of System on Chip
(SoC), and cache with Memory Management Unit (MMU) and cache
memory unit makes the state space too large for simulation to verify,
then a formal verification is presented for such system design. In the
paper, a formal model checking verification flow is suggested and a
new cache memory model which is called “exhaustive search model”
is proposed. Instead of using large size ram to denote the whole cache
memory, exhaustive search model employs just two cache blocks. For
cache system contains data cache (Dcache) and instruction cache
(Icache), Dcache memory model and Icache memory model are
established separately using the same mechanism. At last, the novel
model is employed to the verification of a cache which is module of a
custom-built SoC system that has been applied in practical, and the
result shows that the cache system is verified correctly using the
exhaustive search model, and it makes the verification much more
manageable and flexible.
Abstract: IEEE 802.16 (WiMAX) aims to present high speed
wireless access to cover wide range coverage. The base station (BS)
and the subscriber station (SS) are the main parts of WiMAX.
WiMAX uses either Point-to-Multipoint (PMP) or mesh topologies.
In the PMP mode, the SSs connect to the BS to gain access to the
network. However, in the mesh mode, the SSs connect to each other
to gain access to the BS.
The main components of QoS management in the 802.16 standard
are the admission control, buffer management and packet scheduling.
In this paper, we use QualNet 5.0.2 to study the performance of
different scheduling schemes, such as WFQ, SCFQ, RR and SP when
the numbers of SSs increase. We find that when the number of SSs
increases, the average jitter and average end-to-end delay is increased
and the throughput is reduced.
Abstract: The planning of geological survey works is an
iterative process which involves planner, geologist, civil engineer and
other stakeholders, who perform different roles and have different
points of view. Traditionally, the team used paper maps or CAD
drawings to present the proposal which is not an efficient way to
present and share idea on the site investigation proposal such as
sitting of borehole location or seismic survey lines. This paper
focuses on how a GIS approach can be utilised to develop a webbased
system to support decision making process in the planning of
geological survey works and also to plan site activities carried out by
Singapore Geological Office (SGO). The authors design a framework
of building an interactive web-based GIS system, and develop a
prototype, which enables the users to obtain rapidly existing
geological information and also to plan interactively borehole
locations and seismic survey lines via a web browser. This prototype
system is used daily by SGO and has shown to be effective in
increasing efficiency and productivity as the time taken in the
planning of geological survey works is shortened. The prototype
system has been developed using the ESRI ArcGIS API 3.7 for Flex
which is based on the ArcGIS 10.2.1 platform.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: With increasingly more mobile health applications
appearing due to the popularity of smartphones, the possibility arises
that these data can be used to improve the medical diagnostic process,
as well as the overall quality of healthcare, while at the same time
lowering costs. However, as of yet there have been no reports of a
successful combination of patient-generated data from smartphones
with data from clinical routine. In this paper we describe how these
two types of data can be combined in a secure way without
modification to hospital information systems, and how they can
together be used in a medical expert system for automatic nutritional
classification and triage.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
Abstract: It is important to take security measures to protect
your computer information, reduce identify theft, and prevent from
malicious cyber-attacks. With cyber-attacks on the continuous rise,
people need to understand and learn ways to prevent from these
attacks. Cyber-attack is an important factor to be considered if one is
to be able to protect oneself from malicious attacks. Without proper
security measures, most computer technology would hinder home
users more than such technologies would help. Knowledge of how
cyber-attacks operate and protective steps that can be taken to reduce
chances of its occurrence are key to increasing these security
measures. The purpose of this paper is to inform home users on the
importance of identifying and taking preventive steps to avoid cyberattacks.
Throughout this paper, many aspects of cyber-attacks will be
discuss: what a cyber-attack is, the affects of cyber-attack for home
users, different types of cyber-attacks, methodology to prevent such
attacks; home users can take to fortify security of their computer.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.