Abstract: In this paper cognitive radio is presented and the
spectrum overlay cognitive radio antenna system is detailed. A UWB
antenna with frequency reconfigurable characteristics is proposed.
The reconfigurability is achieved when the filter is integrated to the
feeding line of the single port overlay cognitive radio. When
activated, the filter can transform the UWB frequency response into a
reconfigurable narrowband one, which is suitable for the
communication operation of the CR system. Here single port overlay
cognitive radio antenna is designed and simulated using Ansoft High
Frequency Structure Simulator (HFSS).
Abstract: Spam is any unwanted electronic message or material
in any form posted too many people. As the world is growing as
global world, social networking sites play an important role in
making world global providing people from different parts of the
world a platform to meet and express their views. Among different
social networking sites Facebook become the leading one. With
increase in usage different users start abusive use of Facebook by
posting or creating ways to post spam. This paper highlights the
potential spam types nowadays Facebook users’ faces. This paper
also provide the reason how user become victim to spam attack. A
methodology is proposed in the end discusses how to handle different
types of spam.
Abstract: This paper presents a new structure of microstrip band
pass filter (BPF) based on coupled stepped impedance resonators.
Each filter consists of two coupled stepped impedance resonators
connected to microstrip feed lines. The coupled junction is utilized to
connect the two BPFs to the antenna. This two band pass filters are
designed and simulated to operate for the digital communication
system (DCS) and Industrial Scientific and Medical (ISM) bands at
1.8 GHz and 2.45 GHz respectively. The proposed circuit presents
good performances with an insertion loss lower than 2.3 dB and
isolation between the two channels greater than 21 dB. The prototype
of the optimized diplexer have been investigated numerically by
using ADS Agilent and verified with CST microwave software.
Abstract: Nowadays, Photovoltaic-PV Farms/ Parks and large
PV-Smart Grid Interface Schemes are emerging and commonly
utilized in Renewable Energy distributed generation. However, PVhybrid-
Dc-Ac Schemes using interface power electronic converters
usually has negative impact on power quality and stabilization of
modern electrical network under load excursions and network fault
conditions in smart grid. Consequently, robust FACTS based
interface schemes are required to ensure efficient energy utilization
and stabilization of bus voltages as well as limiting switching/fault
onrush current condition. FACTS devices are also used in smart grid-
Battery Interface and Storage Schemes with PV-Battery Storage
hybrid systems as an elegant alternative to renewable energy
utilization with backup battery storage for electric utility energy and
demand side management to provide needed energy and power
capacity under heavy load conditions. The paper presents a robust
interface PV-Li-Ion Battery Storage Interface Scheme for
Distribution/Utilization Low Voltage Interface using FACTS
stabilization enhancement and dynamic maximum PV power tracking
controllers.
Digital simulation and validation of the proposed scheme is done
using MATLAB/Simulink software environment for Low Voltage-
Distribution/Utilization system feeding a hybrid Linear-Motorized
inrush and nonlinear type loads from a DC-AC Interface VSC-6-
pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion
Storage Battery.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: Recommendation systems are widely used in
e-commerce applications. The engine of a current recommendation
system recommends items to a particular user based on user
preferences and previous high ratings. Various recommendation
schemes such as collaborative filtering and content-based approaches
are used to build a recommendation system. Most of current
recommendation systems were developed to fit a certain domain such
as books, articles, and movies. We propose1 a hybrid framework
recommendation system to be applied on two dimensional spaces
(User × Item) with a large number of Users and a small number
of Items. Moreover, our proposed framework makes use of both
favorite and non-favorite items of a particular user. The proposed
framework is built upon the integration of association rules mining
and the content-based approach. The results of experiments show
that our proposed framework can provide accurate recommendations
to users.
Abstract: An algorithm is a well-defined procedure that takes
some input in the form of some values, processes them and gives the
desired output. It forms the basis of many other algorithms such as
searching, pattern matching, digital filters etc., and other applications
have been found in database systems, data statistics and processing,
data communications and pattern matching. This paper introduces
algorithmic “Enhanced Bidirectional Selection” sort which is
bidirectional, stable. It is said to be bidirectional as it selects two
values smallest from the front and largest from the rear and assigns
them to their appropriate locations thus reducing the number of
passes by half the total number of elements as compared to selection
sort.
Abstract: Images are important source of information used as
evidence during any investigation process. Their clarity and accuracy
is essential and of the utmost importance for any investigation.
Images are vulnerable to losing blocks and having noise added to
them either after alteration or when the image was taken initially,
therefore, having a high performance image processing system and it
is implementation is very important in a forensic point of view. This
paper focuses on improving the quality of the forensic images.
For different reasons packets that store data can be affected,
harmed or even lost because of noise. For example, sending the
image through a wireless channel can cause loss of bits. These types
of errors might give difficulties generally for the visual display
quality of the forensic images.
Two of the images problems: noise and losing blocks are covered.
However, information which gets transmitted through any way of
communication may suffer alteration from its original state or even
lose important data due to the channel noise. Therefore, a developed
system is introduced to improve the quality and clarity of the forensic
images.
Abstract: The present study was conducted to evaluate the
potential applicability of biological trickling filter system for the
treatment of simulated textile wastewater containing reactive azo
dyes with bacterial consortium under non-sterile conditions. The
percentage decolorization for the treatment of wastewater containing
structurally different dyes was found to be higher than 95% in all
trials. The stable bacterial count of the biofilm on stone media of the
trickling filter during the treatment confirmed the presence,
proliferation, dominance and involvement of the added microbial
consortium in the treatment of textile wastewater. Results of
physicochemical parameters revealed the reduction in chemical
oxygen demand (58.5-75.1%), sulphates (18.9-36.5%), and
phosphates (63.6-73.0%). UV-Visible and FTIR spectroscopy
confirmed decolorization of dye containing wastewater was ultimate
consequence of biodegradation. Toxicological studies revealed the
nontoxic nature of degradative metabolites.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: The reliability of the filtered HVBK model is now
investigated via some large eddy simulations (LES) of freely
decaying isotropic superfluid turbulence. For homogeneous
turbulence at very high Reynolds numbers, comparison of the terms
in the spectral kinetic energy budget equation indicates, in the
energy-containing range, that the production and energy transfer
effects become significant except for dissipation. In the inertial range,
where the two fluids are perfectly locked, the mutual friction maybe
neglected with respect to other terms. Also, the LES results for the
other terms of the energy balance are presented.
Abstract: There are a variety of reference current identification
methods, for the shunt active power filter (SAPF), such as the
instantaneous active and reactive power, the instantaneous active and
reactive current and the synchronous detection method are evaluated
and compared under ideal, non sinusoidal and unbalanced voltage
conditions. The SAPF performances, for the investigated
identification methods, are tested for a non linear load. The
simulation results, using Matlab Power System Blockset Toolbox
from a complete structure, are presented and discussed.
Abstract: Powder metallurgy (P/M) is the only economic way to
produce porous parts/products. P/M can produce near net shape parts
hence reduces wastage of raw material and energy, avoids various
machining operations. The most vital use of P/M is in production of
metallic filters and self lubricating bush bearings and siding surfaces.
The porosity of the part can be controlled by varying compaction
pressure, sintering temperature and composition of metal powder
mix. The present work is aimed for experimental analysis of friction
and wear properties of self lubricating copper and tin bush bearing.
Experimental results confirm that wear rate of sintered component
is lesser for components having 10% tin by weight percentage. Wear
rate increases for high tin percentage (experimented for 20% tin and
30% tin) at same sintering temperature. Experimental results also
confirms that wear rate of sintered component is also dependent on
sintering temperature, soaking period, composition of the preform,
compacting pressure, powder particle shape and size.
Interfacial friction between die and punch, between inter powder
particles, between die face and powder particle depends on
compaction pressure, powder particle size and shape, size and shape
of component which decides size & shape of die & punch, material of
die & punch and material of powder particles.
Abstract: In today’s era, it is no news that organizations should
demonstrate honest conduct as well as ethical administration.
Therefore, the concept of corporate social responsibility
(subsequently CSR) has created its tag upon the company’s focal
point as well as marketing communications, and will continue in the
future. The importance of CSR has increased in the last decade, and
this concept has attracted global attention. The notion of CSR has
strategic significance for many organizations. However, businesses
are not adapting the activities of CSR that benefit to all of its
stakeholders (including society). The main reason is the practitioners
are unfortunately unable to comprehend its importance; and
therefore, the activities of the CSR are so detached from the business
activities. Hence, it is required to develop an understanding that the
activities of CSR are not only beneficial for the society but it also
benefit to business. This paper focuses on the concept of strategic
CSR, and develops a theoretical framework that will help
practitioners to filter and chose the activities of CSR that are strategic
in nature.
Abstract: This study is purposed to develop an efficient fault
detection method for Global Navigation Satellite Systems (GNSS)
applications based on adaptive noise covariance estimation. Due to the
dependence on radio frequency signals, GNSS measurements are
dominated by systematic errors in receiver’s operating environment.
In the proposed method, the pseudorange and carrier-phase
measurement noise covariances are obtained at time propagations and
measurement updates in process of Carrier-Smoothed Code (CSC)
filtering, respectively. The test statistics for fault detection are
generated by the estimated measurement noise covariances. To
evaluate the fault detection capability, intentional faults were added to
the filed-collected measurements. The experiment result shows that
the proposed method is efficient in detecting unhealthy measurements
and improves GNSS positioning accuracy against fault occurrences.
Abstract: This paper presents a real-time visualization technique
and filtering of classified LiDAR point clouds. The visualization is
capable of displaying filtered information organized in layers by the
classification attribute saved within LiDAR datasets. We explain the
used data structure and data management, which enables real-time
presentation of layered LiDAR data. Real-time visualization is
achieved with LOD optimization based on the distance from the
observer without loss of quality. The filtering process is done in two
steps and is entirely executed on the GPU and implemented using
programmable shaders.
Abstract: In this paper two approaches to joint signal detection,
time of arrival (ToA) and angle of arrival (AoA) estimation in
multi-element antenna array are investigated. Two scenarios were
considered: first one, when the waveform of the useful signal
is known a priori and, second one, when the waveform of the
desired signal is unknown. For first scenario, the antenna array
signal processing based on multi-element matched filtering (MF)
with the following non-coherent detection scheme and maximum
likelihood (ML) parameter estimation blocks is exploited. For second
scenario, the signal processing based on the antenna array elements
covariance matrix estimation with the following eigenvector analysis
and ML parameter estimation blocks is applied. The performance
characteristics of both signal processing schemes are thoroughly
investigated and compared for different useful signals and noise
parameters.
Abstract: The Sigma-Delta A/D converters have been proposed
as a practical application for A/D conversion at high rates because of
its simplicity and robustness to imperfections in the circuit, also
because the traditional converters are more difficult to implement in
VLSI technology. These difficulties with conventional conversion
methods need precise analog components in their filters and
conversion circuits, and are more vulnerable to noise and
interference. This paper aims to analyze the architecture, function and
application of Analog-Digital converters (A/D) Sigma-Delta to
overcome these difficulties, showing some simulations using the
Simulink software and Multisim.
Abstract: Voltage sags are the most common power quality
disturbance in the distribution system. It occurs due to the fault in the
electrical network or by the starting of a large induction motor and
this can be solved by using the custom power devices such as
Dynamic Voltage Restorer (DVR). In this paper DVR is proposed to
compensate voltage sags on critical loads dynamically. The DVR
consists of VSC, injection transformers, passive filters and energy
storage (lead acid battery). By injecting an appropriate voltage, the
DVR restores a voltage waveform and ensures constant load voltage.
The simulation and experimental results of a DVR using MATLAB
software shows clearly the performance of the DVR in mitigating
voltage sags.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.