Abstract: To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.
Abstract: In this paper, a frequency-variation based method has
been proposed for transistor parameter estimation in a commonemitter
transistor amplifier circuit. We design an algorithm to estimate
the transistor parameters, based on noisy measurements of the output
voltage when the input voltage is a sine wave of variable frequency
and constant amplitude. The common emitter amplifier circuit has
been modelled using the transistor Ebers-Moll equations and the
perturbation technique has been used for separating the linear and
nonlinear parts of the Ebers-Moll equations. This model of the amplifier
has been used to determine the amplitude of the output sinusoid as
a function of the frequency and the parameter vector. Then, applying
the proposed method to the frequency components, the transistor
parameters have been estimated. As compared to the conventional
time-domain least squares method, the proposed method requires
much less data storage and it results in more accurate parameter
estimation, as it exploits the information in the time and frequency
domain, simultaneously. The proposed method can be utilized for
parameter estimation of an analog device in its operating range of
frequencies, as it uses data collected from different frequencies output
signals for parameter estimation.
Abstract: Let the vertices of a graph such that every two
adjacent vertices have different color is a very common problem in
the graph theory. This is known as proper coloring of graphs. The
possible number of different proper colorings on a graph with a given
number of colors can be represented by a function called the
chromatic polynomial. Two graphs G and H are said to be
chromatically equivalent, if they share the same chromatic
polynomial. A Graph G is chromatically unique, if G is isomorphic to
H for any graph H such that G is chromatically equivalent to H. The
study of chromatically equivalent and chromatically unique problems
is called chromaticity. This paper shows that a wheel W12 is
chromatically unique.
Abstract: This study investigates the use of genetic algorithms
in information retrieval. The method is shown to be applicable to
three well-known documents collections, where more relevant
documents are presented to users in the genetic modification. In this
paper we present a new fitness function for approximate information
retrieval which is very fast and very flexible, than cosine similarity
fitness function.
Abstract: Since 1991 Ethiopia has officially adopted multi-party democracy. At present, there are 89 registered political parties in the country. Though political parties play an important role in the functioning of a democratic government, how to fund them is an issue of major concern. Political parties and individual candidates running for political office have to raise funds for election campaigns, and to survive as political candidates. The aim of this paper is to examine party funding problems in Africa by taking the case of Ethiopia as an example. The paper also evaluates the motives of local and international donors in giving financial and material support to political parties in emerging democracies and assesses the merits and de-merits of their donations.
Abstract: A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.
Abstract: High Strength Concrete (HSC) is defined as concrete
that meets special combination of performance and uniformity
requirements that cannot be achieved routinely using conventional
constituents and normal mixing, placing, and curing procedures. It is
a highly complex material, which makes modeling its behavior a very
difficult task. This paper aimed to show possible applicability of
Neural Networks (NN) to predict the slump in High Strength
Concrete (HSC). Neural Network models is constructed, trained and
tested using the available test data of 349 different concrete mix
designs of High Strength Concrete (HSC) gathered from a particular
Ready Mix Concrete (RMC) batching plant. The most versatile
Neural Network model is selected to predict the slump in concrete.
The data used in the Neural Network models are arranged in a format
of eight input parameters that cover the Cement, Fly Ash, Sand,
Coarse Aggregate (10 mm), Coarse Aggregate (20 mm), Water,
Super-Plasticizer and Water/Binder ratio. Furthermore, to test the
accuracy for predicting slump in concrete, the final selected model is
further used to test the data of 40 different concrete mix designs of
High Strength Concrete (HSC) taken from the other batching plant.
The results are compared on the basis of error function (or
performance function).
Abstract: This research attempts to explore gaps in Information
Systems (IS) and innovation literatures by developing a model of
Information Technology (IT) capability in enabling innovation. The
research was conducted by using semi-structured interview with six
innovators in business consulting, financial, healthcare and academic
organizations. The interview results suggest four elements of ITenabled
innovation capability which are information (ability to
capture ideas and knowledge), connectivity (ability to bridge
geographical boundary and mobilize human resources),
communication (ability to attain and engage relationships between
human resources) and transformation (ability to change the functions
and process integrations) in defining IT-enabled innovation platform.
The results also suggests innovators- roles and IT capability.
Abstract: The present study addresses problems and solutions
related to new functional food production. Wheat (Triticum aestivum
L) bran obtained from industrial mill company “Dobeles
dzirnavieks”, was used to investigate them as raw material like
nutrients for Bifidobacterium lactis Bb-12. Enzymatic hydrolysis of
wheat bran starch was carried out by α-amylase from Bacillus
amyloliquefaciens (Sigma Aldrich). The Viscozyme L purchased
from (Sigma Aldrich) were used for reducing released sugar.
Bifidibacterium lactis Bb-12 purchased from (Probio-Tec® CHR
Hansen) was cultivated in enzymatically hydrolysed wheat bran
mash. All procedures ensured the number of active Bifidobacterium
lactis Bb-12 in the final product reached 105 CFUg-1. After enzymatic
and bacterial fermentations sample were freeze dried for analysis of
chemical compounds. All experiments were performed at Faculty of
Food Technology of Latvia University of Agriculture in January-
March 2013. The obtained results show that both types of wheat bran
(enzymatically treated and non-treated) influenced the fermentative
activity and number of Bifidibacterium lactis Bb-12 viable in wheat
bran mash. Amount of acidity strongly increase during the wheat
bran mash fermentation. The main objective of this work was to
create low-energy functional enzymatically and bacterially treated
food from wheat bran using enzymatic hydrolysis of carbohydrates
and following cultivation of Bifidobacterium lactis Bb-12.
Abstract: Factoring Boolean functions is one of the basic operations in algorithmic logic synthesis. A novel algebraic factorization heuristic for single-output combinatorial logic functions is presented in this paper and is developed based on the set theory paradigm. The impact of factoring is analyzed mainly from a low power design perspective for standard cell based digital designs in this paper. The physical implementation of a number of MCNC/IWLS combinational benchmark functions and sub-functions are compared before and after factoring, based on a simple technology mapping procedure utilizing only standard gate primitives (readily available as standard cells in a technology library) and not cells corresponding to optimized complex logic. The power results were obtained at the gate-level by means of an industry-standard power analysis tool from Synopsys, targeting a 130nm (0.13μm) UMC CMOS library, for the typical case. The wire-loads were inserted automatically and the simulations were performed with maximum input activity. The gate-level simulations demonstrate the advantage of the proposed factoring technique in comparison with other existing methods from a low power perspective, for arbitrary examples. Though the benchmarks experimentation reports mixed results, the mean savings in total power and dynamic power for the factored solution over a non-factored solution were 6.11% and 5.85% respectively. In terms of leakage power, the average savings for the factored forms was significant to the tune of 23.48%. The factored solution is expected to better its non-factored counterpart in terms of the power-delay product as it is well-known that factoring, in general, yields a delay-efficient multi-level solution.
Abstract: In this study, numerical simulations on laminar flow in
sinusoidal wavy shaped tubes were conducted for mean Reynolds
number of 250, which is in the range of physiological flow-rate and
investigated flow structures, pressure distribution and particle
trajectories both in steady and periodic inflow conditions. For
extensive comparisons, various wave lengths and amplitudes of sine
function for geometry of tube models were employed. The results
showed that small amplitude secondary curvature has significant
influence on the nature of flow patterns and particle mixing
mechanism. This implies that characterizing accurate geometry is
essential in accurate predicting of in vivo hemodynamics and may
motivate further study on any possibility of reflection of secondary
flow on vascular remodeling and pathophysiology.
Abstract: This paper will first describe predictor controllers
when the proportional-integral-derivative (PID) controllers are
inactive for procedures that have large delay time (LDT) in transfer
stage. Therefore in those states, the predictor controllers are better
than the PID controllers, then compares three types of predictor
controllers. The value of these controller-s parameters are obtained
by trial and error method, so here an effort has been made to obtain
these parameters by Ziegler-Nichols method. Eventually in this paper
Ziegler-Nichols method has been described and finally, a PIP
controller has been designed for a thermal system, which circulates
hot air to keep the temperature of a chamber constant.
Abstract: This paper is a part of research, in which the way the
biomedical engineers follow in their work is analyzed. The goal of
this paper is to present a method for specification of user
requirements in the medical devices maintenance process. Data
Gathering Methods, Research Model Phases and Descriptive
Analysis is presented. These technology and verification rules can be
implemented in Medical devices maintenance management process to
the maintenance process.
Abstract: SeqWord Gene Island Sniffer, a new program for
the identification of mobile genetic elements in sequences of bacterial chromosomes is presented. This program is based on the
analysis of oligonucleotide usage variations in DNA sequences. 3,518 mobile genetic elements were identified in 637 bacterial
genomes and further analyzed by sequence similarity and the
functionality of encoded proteins. The results of this study are stored in an open database http://anjie.bi.up.ac.za/geidb/geidbhome.
php). The developed computer program and the database provide the information valuable for further investigation of the
distribution of mobile genetic elements and virulence factors among bacteria. The program is available for download at www.bi.up.ac.za/SeqWord/sniffer/index.html.
Abstract: In this paper, a novel scheme is proposed for ownership identification and authentication using color images by deploying Cryptography and Digital Watermarking as underlaying technologies. The former is used to compute the contents based hash and the latter to embed the watermark. The host image that will claim to be the rightful owner is first transformed from RGB to YST color space exclusively designed for watermarking based applications. Geometrically YS ÔèÑ T and T channel corresponds to the chrominance component of color image, therefore suitable for embedding the watermark. The T channel is divided into 4×4 nonoverlapping blocks. The size of block is important for enhanced localization, security and low computation. Each block along with ownership information is then deployed by SHA160, a one way hash function to compute the content based hash, which is always unique and resistant against birthday attack instead of using MD5 that may raise the condition i.e. H(m)=H(m'). The watermark payload varies from block to block and computed by the variance factorα . The quality of watermarked images is quite high both subjectively and objectively. Our scheme is blind, computationally fast and exactly locates the tampered region.
Abstract: With the advance of information technology in the
new era the applications of Internet to access data resources has
steadily increased and huge amount of data have become accessible
in various forms. Obviously, the network providers and agencies,
look after to prevent electronic attacks that may be harmful or may
be related to terrorist applications. Thus, these have facilitated the
authorities to under take a variety of methods to protect the special
regions from harmful data. One of the most important approaches is
to use firewall in the network facilities. The main objectives of
firewalls are to stop the transfer of suspicious packets in several
ways. However because of its blind packet stopping, high process
power requirements and expensive prices some of the providers are
reluctant to use the firewall. In this paper we proposed a method to
find a discriminate function to distinguish between usual packets and
harmful ones by the statistical processing on the network router logs.
By discriminating these data, an administrator may take an approach
action against the user. This method is very fast and can be used
simply in adjacent with the Internet routers.
Abstract: The present paper aims to present the significant role that the concept of governance can play in order to combine naturals resources as useful funding basis for the formation of a stable and effective welfare state model. The combination of those two different fields aims to represent the modern trends of our era as the means to solve the severe financial and economic issues caused mostly due to the malfunction of the welfare state and its public sector. European Union and Asian countries (especially China) are the main areas of interest since EU experiences a fiscal and economic crisis while China rules the area of the natural resources exploiting 97% of rare earths elements worldwide.
Abstract: In the proposed method for Web page-ranking, a
novel theoretic model is introduced and tested by examples of order
relationships among IP addresses. Ranking is induced using a
convexity feature, which is learned according to these examples
using a self-organizing procedure. We consider the problem of selforganizing
learning from IP data to be represented by a semi-random
convex polygon procedure, in which the vertices correspond to IP
addresses. Based on recent developments in our regularization
theory for convex polygons and corresponding Euclidean distance
based methods for classification, we develop an algorithmic
framework for learning ranking functions based on a Computational
Geometric Theory. We show that our algorithm is generic, and
present experimental results explaining the potential of our approach.
In addition, we explain the generality of our approach by showing its
possible use as a visualization tool for data obtained from diverse
domains, such as Public Administration and Education.
Abstract: Fruits and vegetables are the essentials of a healthy
diet, mainly because of their antioxidant properties contributing to
disease blockage especially for some certain types of cancer. Being a
favourite fruit, citrus are produced for economic and commercial
purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has
an important place in export products of Turkey. Lemon has a great
importance on human nutrition with regard to being a source of
nutrients, flavonoids, vitamin C and minerals. It is used for food
flavouring and pickling and also processed for lemonade. By
processing citrus into fruit juices, consumption may increase and also
become easier. Like many fruits and vegetables lemons are cheap and
abundant during harvesting period, while they are quite expensive in
other seasons. Lemon juice and concentrate production allows
consumers to get benefits from lemon fruit in any time of the year.
Lemonade is getting in to the focus of consumers’ attention
preferring non-carbonated drinks. The demand of healthy, convenient
functional foods affects consumer trends through innovative
products. For this reason, lemonade could be enriched with different
natural herb extracts such as ginger (Zingiber officinale), linden (Tilia
cordata), and mint (Mentha piperita).
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.