Abstract: This paper proposes five level diode clamped Z source
Inverter. The existing PWM techniques used for ZSI are restricted for
two level. The two level Z Source Inverter have high harmonic
distortions which effects the performance of the grid connected PV
system. To improve the performance of the system the number of
voltage levels in the output waveform need to be increased. This
paper presents comparative analysis of a five level diode clamped Z
source Inverter with different carrier based Modified Pulse Width
Modulation techniques. The parameters considered for comparison
are output voltage, voltage gain, voltage stress across switch and total
harmonic distortion when powered by same DC supply. Analytical
results are verified using MATLAB.
Abstract: Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
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: Hurling a successful Construction and Demolition
Waste (C&DW) recycling operation around the globe is a challenge
today, predominantly because secondary materials markets are yet to
be integrated. Reducing, Reusing and recycling of (C&DW) have
been employed over the years, and various techniques have been
investigated. However, the economic and environmental viability of
its application seems limited. This paper discusses the costs and
benefits in using secondary materials and focus on investigating reuse
and recycling process for five major types of construction materials:
concrete, metal, wood, cardboard/paper and plasterboard. Data
obtained from demolition specialists and contractors are considered
and evaluated. The research paper found that construction material
recovery process fully incorporate a 3R’s principle contributing to
saving energy and natural resources. This scrutiny leads to the
empathy of grand challenges in construction material recovery
process. Recommendations to deepen material recovery process are
also discussed.
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.
Abstract: Over the past four decades, the fatigue behavior of
nickel-based alloys has been widely studied. However, in recent
years, significant advances in the fabrication process leading to grain
size reduction have been made in order to improve fatigue properties
of aircraft turbine discs. Indeed, a change in particle size affects the
initiation mode of fatigue cracks as well as the fatigue life of the
material. The present study aims to investigate the fatigue behavior of
a newly developed nickel-based superalloy under biaxial-planar
loading. Low Cycle Fatigue (LCF) tests are performed at different
stress ratios so as to study the influence of the multiaxial stress state
on the fatigue life of the material. Full-field displacement and strain
measurements as well as crack initiation detection are obtained using
Digital Image Correlation (DIC) techniques. The aim of this
presentation is first to provide an in-depth description of both the
experimental set-up and protocol: the multiaxial testing machine, the
specific design of the cruciform specimen and performances of the
DIC code are introduced. Second, results for sixteen specimens
related to different load ratios are presented. Crack detection, strain
amplitude and number of cycles to crack initiation vs. triaxial stress
ratio for each loading case are given. Third, from fractographic
investigations by scanning electron microscopy it is found that the
mechanism of fatigue crack initiation does not depend on the triaxial
stress ratio and that most fatigue cracks initiate from subsurface
carbides.
Abstract: In this paper, we used data mining to extract
biomedical knowledge. In general, complex biomedical data
collected in studies of populations are treated by statistical methods,
although they are robust, they are not sufficient in themselves to
harness the potential wealth of data. For that you used in step two
learning algorithms: the Decision Trees and Support Vector Machine
(SVM). These supervised classification methods are used to make the
diagnosis of thyroid disease. In this context, we propose to promote
the study and use of symbolic data mining techniques.
Abstract: In this paper, reliable consensus of multi-agent systems
with sampled-data is investigated. By using a suitable
Lyapunov-Krasovskii functional and some techniques such as
Wirtinger Inequality, Schur Complement and Kronecker Product, the
results of such system are obtained by solving a set of Linear Matrix
Inequalities (LMIs). One numerical example is included to show the
effectiveness of the proposed criteria.
Abstract: This paper presents powerful techniques for the
development of a new monitoring method based on multi-scale
entropy (MSE) in order to characterize the behaviour of the
concentrations of different gases present in the synthesis of Ammonia
and soft-sensor based on Principal Component Analysis (PCA).
Abstract: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.
Abstract: Natural hydrocarbon seepage has helped petroleum
exploration as a direct indicator of gas and/or oil subsurface
accumulations. Surface macro-seeps are generally an indication of a
fault in an active Petroleum Seepage System belonging to a Total
Petroleum System. This paper describes a case study in which
multiple analytical techniques were used to identify and characterize
trace petroleum-related hydrocarbons and other volatile organic
compounds in groundwater samples collected from Sousse aquifer
(Central Tunisia). The analytical techniques used for analyses of
water samples included gas chromatography-mass spectrometry (GCMS),
capillary GC with flame-ionization detection, Compound
Specific Isotope Analysis, Rock Eval Pyrolysis. The objective of the
study was to confirm the presence of gasoline and other petroleum
products or other volatile organic pollutants in those samples in order
to assess the respective implication of each of the potentially
responsible parties to the contamination of the aquifer. In addition,
the degree of contamination at different depths in the aquifer was also
of interest. The oil and gas seeps have been investigated using
biomarker and stable carbon isotope analyses to perform oil-oil and
oil-source rock correlations. The seepage gases are characterized by
high CH4 content, very low δ13CCH4 values (-71,9 ‰) and high
C1/C1–5 ratios (0.95–1.0), light deuterium–hydrogen isotope ratios (-
198 ‰) and light δ13CC2 and δ13CCO2 values (-23,8‰ and-23,8‰
respectively) indicating a thermogenic origin with the contribution of
the biogenic gas. An organic geochemistry study was carried out on
the more ten oil seep samples. This study includes light hydrocarbon
and biomarkers analyses (hopanes, steranes, n-alkanes, acyclic
isoprenoids, and aromatic steroids) using GC and GC-MS. The
studied samples show at least two distinct families, suggesting two
different types of crude oil origins: the first oil seeps appears to be
highly mature, showing evidence of chemical and/or biological
degradation and was derived from a clay-rich source rock deposited
in suboxic conditions. It has been sourced mainly by the lower
Fahdene (Albian) source rocks. The second oil seeps was derived
from a carbonate-rich source rock deposited in anoxic conditions,
well correlated with the Bahloul (Cenomanian-Turonian) source rock.
Abstract: Multi-Level Inverter technology has been developed in the area of high-power medium-voltage energy scheme, because of their advantages such as devices of lower rating can be used thereby enabling the schemes to be used for high voltage applications. Reduced Total Harmonic Distortion (THD).Since the dv/dt is low; the Electromagnetic Interference from the scheme is low. To avoid the switching losses Lower switching frequencies can be used. In this paper present a survey of various topologies, control strategy and modulation techniques used by these inverters. Here the regenerative and superior topologies are also discussed.
Abstract: The aim of this paper is to select the most accurate
forecasting method for predicting the future values of the
unemployment rate in selected European countries. In order to do so,
several forecasting techniques adequate for forecasting time series
with trend component, were selected, namely: double exponential
smoothing (also known as Holt`s method) and Holt-Winters` method
which accounts for trend and seasonality. The results of the empirical
analysis showed that the optimal model for forecasting
unemployment rate in Greece was Holt-Winters` additive method. In
the case of Spain, according to MAPE, the optimal model was double
exponential smoothing model. Furthermore, for Croatia and Italy the
best forecasting model for unemployment rate was Holt-Winters`
multiplicative model, whereas in the case of Portugal the best model
to forecast unemployment rate was Double exponential smoothing
model. Our findings are in line with European Commission
unemployment rate estimates.
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: Maize constitutes a major agrarian production for use
by the vast population but despite its economic importance; it has not
been produced to meet the economic needs of the country. Achieving
optimum yield in maize can meaningfully be supported by land
suitability analysis in order to guarantee self-sufficiency for future
production optimization. This study examines land suitability for
maize production through the analysis of the physicochemical
variations in soil properties and other land attributes over space using
a Geographic Information System (GIS) framework.
Physicochemical parameters of importance selected include slope,
landuse, physical and chemical properties of the soil, and climatic
variables. Landsat imagery was used to categorize the landuse,
Shuttle Radar Topographic Mapping (SRTM) generated the slope and
soil samples were analyzed for its physical and chemical components.
Suitability was categorized into highly, moderately and marginally
suitable based on Food and Agricultural Organisation (FAO)
classification, using the Analytical Hierarchy Process (AHP)
technique of GIS. This result can be used by small scale farmers for
efficient decision making in the allocation of land for maize
production.
Abstract: Analysis of the properties of coconut (Cocos nucifera)
and its oil was evaluated in this work using standard analytical
techniques. The analyses carried out include proximate composition
of the fruit, extraction of oil from the fruit using different process
parameters and physicochemical analysis of the extracted oil. The
results showed the percentage (%) moisture, crude lipid, crude
protein, ash and carbohydrate content of the coconut as 7.59, 55.15,
5.65, 7.35 and 19.51 respectively. The oil from the coconut fruit was
odourless and yellowish liquid at room temperature (30oC). The
treatment combinations used (leaching time, leaching temperature
and solute: solvent ratio) showed significant differences (P
Abstract: Standard processes, similar and limited production
lines, the production of high direct costs will be more accurate than
the use of parts of the traditional cost systems in the literature.
However, direct costs, overhead expenses, in turn, decrease the
burden of increasingly sophisticated production facilities, a situation
that led the researchers to look for the cost of traditional systems of
alternative techniques. Variety cost management approaches for
example Total quality management (TQM), just-in-time (JIT),
benchmarking, kaizen costing, targeting cost, life cycle costs (LLC),
activity-based costing (ABC) value engineering have been
introduced. Management and cost applications have changed over the
past decade and will continue to change. Modern cost systems can
provide relevant and accurate cost information. These methods
provide the decisions about customer, product and process
improvement. The aim of study is to describe and explain the
adoption and application of costing systems in SME. This purpose
reports on a survey conducted during 2014 small and medium sized
enterprises (SME) in Ankara. The survey results were evaluated
using SPSS18 package program.
Abstract: The performance and analysis of speech recognition
system is illustrated in this paper. An approach to recognize the
English word corresponding to digit (0-9) spoken by 2 different
speakers is captured in noise free environment. For feature extraction,
speech Mel frequency cepstral coefficients (MFCC) has been used
which gives a set of feature vectors from recorded speech samples.
Neural network model is used to enhance the recognition
performance. Feed forward neural network with back propagation
algorithm model is used. However other speech recognition
techniques such as HMM, DTW exist. All experiments are carried
out on Matlab.
Abstract: Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.
Abstract: In recent years, the hair building fiber has become
popular, in other words, it is an effective method which helps people
who suffer hair loss or sparse hair since the hair building fiber is
capable to create a natural look of simulated hair rapidly. In the
markets, there are a lot of hair fiber brands that have been designed to
formulate an intense bond with hair strands and make the hair appear
more voluminous instantly. However, those products have their own
set of properties. Thus, in this report, some measurement techniques
are proposed to identify those products. Up to five different brands of
hair fiber are tested. The electrostatic and dielectric properties of the
hair fibers are macroscopically tested using design DC and high
frequency microwave techniques. Besides, the hair fibers are
microscopically analysis by magnifying the structures of the fiber
using scanning electron microscope (SEM). From the SEM photos,
the comparison of the uniformly shaped and broken rate of the hair
fibers in the different bulk samples can be observed respectively.