Abstract: Mathematical justifications are given for a simulation technique of multivariate nonGaussian random processes and fields based on Rosenblatt-s transformation of Gaussian processes. Different types of convergences are given for the approaching sequence. Moreover an original numerical method is proposed in order to solve the functional equation yielding the underlying Gaussian process autocorrelation function.
Abstract: Visually impaired people find it extremely difficult to
acquire basic and vital information necessary for their living.
Therefore, they are at a very high risk of being socially excluded as a
result of poor access to information. In recent years, several attempts
have been made in improving the communication methods for
visually impaired people which involve tactile sensation such as
finger Braille, manual alphabets and the print on palm method and
several other electronic devices. But, there are some problems which
arise in such methods such as lack of privacy and lack of
compatibility to computer environment. This paper describes a low
cost Braille hand glove for blind people using slot sensors and
vibration motors with the help of which they can read and write emails,
text messages and read e-books. This glove allows the person
to type characters based on different Braille combination using six
slot sensors. The vibration in six different positions of the glove
which matches to the Braille code allows them to read characters.
Abstract: Introduction: Obesity is a major health risk issue in
the present day of life for one and all globally. Obesity is one of the
major concerns for public health according to recent increasing trends
in obesity-related diseases such as Type 2 diabetes. ( Kazuya,
1994).and hyperlipidemia, (Sakata,1990) .which are more prevalent
in Japanese adults with body mass index (BMI) values Z25 kg/m2.(
Japanese Ministry of Health and Welfare,1997). The purpose of the
study was to assess the effect of twelve weeks of brisk walking on
blood pressure and body mass index, anthropometric measurements
of obese males. Method: Thirty obese (BMI= above 30) males, aged
18 to 22 years, were selected from King Fahd University of
Petroleum & Minerals, Saudi Arabia. The subject-s height (cm) was
measured using a stadiometer and body mass (kg) was measured with
a electronic weighing machine. BMI was subsequently calculated
(kg/m2). The blood pressure was measured with standardized
sphygmomanometer in mm of Hg. All the measurements were taken
twice before and twice after the experimental period. The pre and
post anthropometric measurements of waist and hip circumference
were measured with the steel tape in cm. The subjects underwent
walking schedule two times in a week for 12 weeks. The 45 minute
sessions of brisk walking were undertaken at an average intensity of
65% to 85% of maximum HR (HRmax; calculated as 220-age).
Results & Discussion: Statistical findings revealed significant
changes from pre test to post test in case of both systolic blood
pressure and diastolic blood pressure in the walking group. Results
also showed significant decrease in their body mass index and
anthropometric measurements i.e. (waist & hip circumference).
Conclusion: It was concluded that twelve weeks brisk walking is
beneficial for lowering of blood pressure, body mass index, and
anthropometric circumference of obese males.
Abstract: Physical urban form is recognized to be the media for
human transactions. It directly influences the travel demand of people
in a specific urban area and the amount of energy used for
transportation. Distorted, sprawling form often creates sustainability
problems in urban areas. It is declared in EU strategic planning
documents that compact urban form and mixed land use pattern must
be given the main focus to achieve better sustainability in urban
areas, but the methods to measure and compare these characteristics
are still not clear.
This paper presents the simple methods to measure the spatial
characteristics of urban form by analyzing the location and
distribution of objects in an urban environment. The extended CA
(cellular automata) model is used to simulate urban development
scenarios.
Abstract: Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.
Abstract: This paper presents a system for discovering
association rules from collections of unstructured documents called
EART (Extract Association Rules from Text). The EART system
treats texts only not images or figures. EART discovers association
rules amongst keywords labeling the collection of textual documents.
The main characteristic of EART is that the system integrates XML
technology (to transform unstructured documents into structured
documents) with Information Retrieval scheme (TF-IDF) and Data
Mining technique for association rules extraction. EART depends on
word feature to extract association rules. It consists of four phases:
structure phase, index phase, text mining phase and visualization
phase. Our work depends on the analysis of the keywords in the
extracted association rules through the co-occurrence of the keywords
in one sentence in the original text and the existing of the keywords
in one sentence without co-occurrence. Experiments applied on a
collection of scientific documents selected from MEDLINE that are
related to the outbreak of H5N1 avian influenza virus.
Abstract: The crossed cube is one of the most notable variations of hypercube, but some properties of the former are superior to those of the latter. For example, the diameter of the crossed cube is almost the half of that of the hypercube. In this paper, we focus on the problem embedding a Hamiltonian cycle through an arbitrary given edge in the crossed cube. We give necessary and sufficient condition for determining whether a given permutation with n elements over Zn generates a Hamiltonian cycle pattern of the crossed cube. Moreover, we obtain a lower bound for the number of different Hamiltonian cycles passing through a given edge in an n-dimensional crossed cube. Our work extends some recently obtained results.
Abstract: This study investigates the possibility providing gully
erosion map by the supervised classification of satellite images
(ETM+) in two mountainous and plain land types. These land types
were the part of Varamin plain, Tehran province, and Roodbar subbasin,
Guilan province, as plain and mountain land types,
respectively. The position of 652 and 124 ground control points were
recorded by GPS respectively in mountain and plain land types. Soil
gully erosion, land uses or plant covers were investigated in these
points. Regarding ground control points and auxiliary points, training
points of gully erosion and other surface features were introduced to
software (Ilwis 3.3 Academic). The supervised classified map of
gully erosion was prepared by maximum likelihood method and then,
overall accuracy of this map was computed. Results showed that the
possibility supervised classification of gully erosion isn-t possible,
although it need more studies for results generalization to other
mountainous regions. Also, with increasing land uses and other
surface features in plain physiography, it decreases the classification
of accuracy.
Abstract: Seaweed farming is emerging as a viable alternative
activity in the Indonesian fisheries sector. This paper aims to
investigate people-s perceptions of seaweed farming, to analyze its
social and economic impacts and to identify the problems and
obstacles hindering its continued development. Structured and
semi-structured questionnaires were prepared to obtain qualitative
data, and interviews were conducted with fishermen who also plant
seaweed. The findings showed that fishermen in the Laikang Bay were
enthusiastic about cultivating seaweeds and that seaweed plays a major
role in supporting the household economy of fishermen. However,
current seaweed drying technologies cannot support increased
seaweed production on a farm or plot, especially in the rainy season.
Additionally, variable monsoon seasons and long marketing channels
are still major constraints on the development of the industry. Finally,
capture fisheries, the primary economic livelihood of fishermen of
older generations, is being slowly replaced by seaweed farming.
Abstract: Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.
Abstract: Bio-chips are used for experiments on genes and
contain various information such as genes, samples and so on. The
two-dimensional bio-chips, in which one axis represent genes and the
other represent samples, are widely being used these days. Instead of
experimenting with real genes which cost lots of money and much
time to get the results, bio-chips are being used for biological
experiments. And extracting data from the bio-chips with high
accuracy and finding out the patterns or useful information from such
data is very important. Bio-chip analysis systems extract data from
various kinds of bio-chips and mine the data in order to get useful
information. One of the commonly used methods to mine the data is
classification. The algorithm that is used to classify the data can be
various depending on the data types or number characteristics and so
on. Considering that bio-chip data is extremely large, an algorithm that
imitates the ecosystem such as the ant algorithm is suitable to use as an
algorithm for classification. This paper focuses on finding the
classification rules from the bio-chip data using the Ant Colony
algorithm which imitates the ecosystem. The developed system takes
in consideration the accuracy of the discovered rules when it applies it
to the bio-chip data in order to predict the classes.
Abstract: Knowledge Discovery of Databases (KDD) is the
process of extracting previously unknown but useful and significant
information from large massive volume of databases. Data Mining is
a stage in the entire process of KDD which applies an algorithm to
extract interesting patterns. Usually, such algorithms generate huge
volume of patterns. These patterns have to be evaluated by using
interestingness measures to reflect the user requirements.
Interestingness is defined in different ways, (i) Objective measures
(ii) Subjective measures. Objective measures such as support and
confidence extract meaningful patterns based on the structure of the
patterns, while subjective measures such as unexpectedness and
novelty reflect the user perspective. In this report, we try to brief the
more widely spread and successful subjective measures and propose
a new subjective measure of interestingness, i.e. shocking.
Abstract: Surface water pollution is one of the serious
environmental problems in rural areas of South Africa due to
discharge of household waste into the streams, turning them into
open sewers. In this study, samples of water were collected from a
stream in Soshanguve and analysed. The result showed that pollution
in the area was caused by man and its activities. The water quality in
the area was found to have deterioted significantly after water runoff
from farms and household wastes. The result shows, fertilizer runoff
contributes 50% of the pollution while pesticides and sediments
contribute up to 10% respectively in the streams, while household
waste contributes up to 30%. This study gives an outline of the
sources of water pollution in the area and provides a process of
creating a clean and unpolluted environment for Soshanguve
community in Pretoria north in order to achieve the 7th aim of the
millennium development goals by 2015, which is ensuring
environmental sustainability.
Abstract: Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.
Abstract: Piezoelectric transformers are electronic devices made
from piezoelectric materials. The piezoelectric transformers as the
name implied are used for changing voltage signals from one level to another. Electrical energy carried with signals is transferred by means of mechanical vibration. Characterizing in both electrical and
mechanical properties leads to extensively use and efficiency enhancement of piezoelectric transformers in various applications. In
this paper, study and analysis of electrical and mechanical properties of multi-layer piezoelectric transformers in forms of potential and
displacement distribution throughout the volume, respectively. This
paper proposes a set of quasi-static mathematical model of electromechanical
coupling for piezoelectric transformer by using a set of
partial differential equations. Computer-based simulation utilizing the three-dimensional finite element method (3-D FEM) is exploited
as a tool for visualizing potentials and displacements distribution
within the multi-layer piezoelectric transformer. This simulation was
conducted by varying a number of layers. In this paper 3, 5 and 7 of
the circular ring type were used. The computer simulation based on
the use of the FEM has been developed in MATLAB programming environment.
Abstract: This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.
Abstract: Polynomial bases and normal bases are both used for
elliptic curve cryptosystems, but field arithmetic operations such as
multiplication, inversion and doubling for each basis are implemented
by different methods. In general, it is said that normal bases, especially
optimal normal bases (ONB) which are special cases on normal bases,
are efficient for the implementation in hardware in comparison with
polynomial bases. However there seems to be more examined by
implementing and analyzing these systems under similar condition. In
this paper, we designed field arithmetic operators for each basis over
GF(2233), which field has a polynomial basis recommended by SEC2
and a type-II ONB both, and analyzed these implementation results.
And, in addition, we predicted the efficiency of two elliptic curve
cryptosystems using these field arithmetic operators.
Abstract: The main aim of this paper is to present the research
findings on the solution of centralized Web-Services for students by
adopting a framework and a prototype for Service Oriented
Architecture (SOA) Web-Services. The current situation of students-
Web-based application services has been identified and proposed an
effective SOA to increase the operational efficiency of Web-Services
for them it was necessary to identify the challenges in delivering a
SOA technology to increase operational efficiency of Web-Services.
Moreover, the SOA is an emerging concept, used for delivering
efficient student SOA Web-Services. Therefore, service reusability
from SOA Web-Services is provided and logically divided services
into smaller services to increase reusability and modularity. In this
case each service is a modular unit by itself and interoperability
services.
Abstract: A feed-forward, back-propagation Artificial Neural
Network (ANN) model has been used to forecast the occurrences of
wastewater overflows in a combined sewerage reticulation system.
This approach was tested to evaluate its applicability as a method
alternative to the common practice of developing a complete
conceptual, mathematical hydrological-hydraulic model for the
sewerage system to enable such forecasts. The ANN approach
obviates the need for a-priori understanding and representation of the
underlying hydrological hydraulic phenomena in mathematical terms
but enables learning the characteristics of a sewer overflow from the
historical data.
The performance of the standard feed-forward, back-propagation
of error algorithm was enhanced by a modified data normalizing
technique that enabled the ANN model to extrapolate into the
territory that was unseen by the training data. The algorithm and the
data normalizing method are presented along with the ANN model
output results that indicate a good accuracy in the forecasted sewer
overflow rates. However, it was revealed that the accurate
forecasting of the overflow rates are heavily dependent on the
availability of a real-time flow monitoring at the overflow structure
to provide antecedent flow rate data. The ability of the ANN to
forecast the overflow rates without the antecedent flow rates (as is
the case with traditional conceptual reticulation models) was found to
be quite poor.
Abstract: The utilization of renewable energy sources in electric
power systems is increasing quickly because of public apprehensions
for unpleasant environmental impacts and increase in the energy
costs involved with the use of conventional energy sources. Despite
the application of these energy sources can considerably diminish the
system fuel costs, they can also have significant influence on the
system reliability. Therefore an appropriate combination of the
system reliability indices level and capital investment costs of system
is vital. This paper presents a hybrid wind/photovoltaic plant, with
the aim of supplying IEEE reliability test system load pattern while
the plant capital investment costs is minimized by applying a hybrid
particle swarm optimization (PSO) / harmony search (HS) approach,
and the system fulfills the appropriate level of reliability.