Abstract: The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.
Abstract: The scope of this paper is to describe a real electrical
installation of renewable energy using photovoltaic cells. The
displayed power grid connected network was established in 2007 at
area of Northern Greece. The photovoltaic park is composed of 6120
photovoltaic cells able to deliver a total power of 1.101.600 Wp. For
the transformation of DC voltage to AC voltage have been used 25
stand alone three phases inverters and for the connection at the
medium voltage network of Greek Power Authority have been
installed two oil immersed transformer of 630 kVA each one. Due to
the wide space area of installation a specific external lightning
protection system has been designed. Additionally, due to the
sensitive electronics of the control and protection systems of park,
surge protection, equipotent bonding and shielding were also of
major importance.
Abstract: XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.
Abstract: Main goal of preventive healthcare problems are at
decreasing the likelihood and severity of potentially life-threatening
illnesses by protection and early detection. The levels of
establishment and staffing costs along with summation of the travel
and waiting time that clients spent are considered as objectives
functions of the proposed nonlinear integer programming model. In
this paper, we have proposed a bi-objective mathematical model for
designing a network of preventive healthcare facilities so as to
minimize aforementioned objectives, simultaneously. Moreover, each
facility acts as M/M/1 queuing system. The number of facilities to be
established, the location of each facility, and the level of technology
for each facility to be chosen are provided as the main determinants
of a healthcare facility network. Finally, to demonstrate performance
of the proposed model, four multi-objective decision making
techniques are presented to solve the model.
Abstract: The security of computer networks plays a strategic
role in modern computer systems. Intrusion Detection Systems (IDS)
act as the 'second line of defense' placed inside a protected
network, looking for known or potential threats in network traffic
and/or audit data recorded by hosts. We developed an Intrusion
Detection System using LAMSTAR neural network to learn patterns
of normal and intrusive activities, to classify observed system
activities and compared the performance of LAMSTAR IDS with
other classification techniques using 5 classes of KDDCup99 data.
LAMSAR IDS gives better performance at the cost of high
Computational complexity, Training time and Testing time, when
compared to other classification techniques (Binary Tree classifier,
RBF classifier, Gaussian Mixture classifier). we further reduced the
Computational Complexity of LAMSTAR IDS by reducing the
dimension of the data using principal component analysis which in
turn reduces the training and testing time with almost the same
performance.
Abstract: The theoretical investigation is carried out to describe
the effect of increase of pressure waves amplitude in clean and bubbly liquid. The goal of the work is to capture the regime of multiple magnification of acoustic and shock waves in the liquid,
which enables to get appropriate conditions to enlarge collapses of
micro-bubbles. The influence of boundary conditions and frequency
of the governing acoustic field is studied for the case of the
cylindrical acoustic resonator. It has been observed the formation of
standing waves with large amplitude at resonant frequencies. The
interaction of the compression wave with gas and vapor bubbles is
investigated for the convergent channel. It is shown theoretically that
the chemical reactions, which occur inside gas bubbles, provide additional impulse to the wave, that affect strongly on the collapses
of the vapor bubbles
Abstract: This paper in essence presents comparative
experimental data on the mechanical performance of steel and
synthetic fibre-reinforced concrete under compression, tensile split
and flexure. URW1050 steel fibre and HPP45 synthetic fibre, both
with the same concrete design mix, have been used to make cube
specimens for a compression test, cylinders for a tensile split test and
beam specimens for a flexural test. The experimental data
demonstrated steel fibre reinforced concrete to be stronger in flexure
at early stages, whilst both fibre reinforced concrete types displayed
comparatively the same performance in compression, tensile splitting
and 28-day flexural strength. In terms of post-crack controlHPP45
was preferable.
Abstract: As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.
Abstract: Information and communication technology (ICT) is
essential to the operation of business, and create many employment
opportunities. High volumes of students graduate in ICT however
students struggle to find job placement. A discrepancy exists between
graduate skills and industry skill requirements. To address the need
for ICT skills required, universities must create programs to meet the
demands of a changing ICT industry. This requires a partnership
between industry, universities and other stakeholders. This situation
may be viewed as a critical systems thinking problem situation as
there are various role players each with their own needs and
requirements. Jackson states a typical critical systems methods has a
pluralistic nature. This paper explores the applicability and suitability
of Maslow and Dooyeweerd to guide understanding and make
recommendations for change in ICT WIL, to foster an all-inclusive
understanding of the situation by stakeholders. The above methods
provide tools for understanding softer issues beyond the skills
required. The study findings suggest that besides skills requirements,
a deeper understanding and empowering students from being a
student to a professional need to be understood and addressed.
Abstract: Arrack is one of the forms of alcoholic beverage or
liquor which is produced from palm or date juice and commonly
consumed by the lower social class of all religious/ethnic
communities in the north-western villages of Bangladesh. The
purpose of the study was to compare arrack drinking patterns
associated with socio-demographic status among the Muslim, Hindu,
Santal, and Oraon communities in the Rasulpur union of Bangladesh.
A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89,
Oraon n-90) selected by cluster random sampling were interviewed
by ADP (Arrack Drinking Pattern) questionnaire. The results of
Pearson Chi-Squire test revealed that arrack drinking patterns were
significantly differed among the Muslim, Hindu, Santal, and Oraon
communities- drinkers. In addition, the results of Spearman-s
bivariate correlation coefficients also revealed that sociodemographic
characteristics of the communities- drinkers were the
significantly positive and negative associations with the arrack
drinking patterns in the Rasulpur union, Bangladesh. The study
suggests that further cross-cultural researches should be conducted
on the consequences of arrack drinking patterns on the communities-
drinkers.
Abstract: The recognition of handwritten numeral is an
important area of research for its applications in post office, banks
and other organizations. This paper presents automatic recognition of
handwritten Kannada numerals based on structural features. Five
different types of features, namely, profile based 10-segment string,
water reservoir; vertical and horizontal strokes, end points and
average boundary length from the minimal bounding box are used in
the recognition of numeral. The effect of each feature and their
combination in the numeral classification is analyzed using nearest
neighbor classifiers. It is common to combine multiple categories of
features into a single feature vector for the classification. Instead,
separate classifiers can be used to classify based on each visual
feature individually and the final classification can be obtained based
on the combination of separate base classification results. One
popular approach is to combine the classifier results into a feature
vector and leaving the decision to next level classifier. This method
is extended to extract a better information, possibility distribution,
from the base classifiers in resolving the conflicts among the
classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy
k-NN) as base classifier for individual feature sets, the results of
which together forms the feature vector for the final k Nearest
Neighbor (k-NN) classifier. Testing is done, using different features,
individually and in combination, on a database containing 1600
samples of different numerals and the results are compared with the
results of different existing methods.
Abstract: In this experiment, we investigated the performance of
two types of heat sink, swaged- and extruded-type, used in the inverter
of industrial electricity generator. The swaged-type heat sink has 62
fins, and the extruded-type has 38 fins having the same dimension as
that of the swaged-type. But the extruded-type heat sink maintains the
same heat transfer area by the laterally waved surface which has 1 mm
in radius. As a result, the swaged- and extruded-type heat sinks
released 71% and 64% of the heat incoming to the heat sink,
respectively. The other incoming heat were naturally convected and
radiated to the ambient. In spite of 40% decrease in number of fins, the
heat release performance of the extruded-type heat sink was lowered
only 7% than that of the swaged-type. We believe that, this shows the
increment of effective heat transfer area by the laterally waved surface
of fins and the better heat transfer property of the extruded-type heat
sink.
Abstract: The deterministic quantum transfer-matrix (QTM)
technique and its mathematical background are presented. This
important tool in computational physics can be applied to a class of
the real physical low-dimensional magnetic systems described by the
Heisenberg hamiltonian which includes the macroscopic molecularbased
spin chains, small size magnetic clusters embedded in some
supramolecules and other interesting compounds. Using QTM, the
spin degrees of freedom are accurately taken into account, yielding
the thermodynamical functions at finite temperatures.
In order to test the application for the susceptibility calculations to
run in the parallel environment, the speed-up and efficiency of
parallelization are analyzed on our platform SGI Origin 3800 with
p = 128 processor units. Using Message Parallel Interface (MPI)
system libraries we find the efficiency of the code of 94% for
p = 128 that makes our application highly scalable.
Abstract: A numerical method for solving the time-independent Schrödinger equation of a particle moving freely in a three-dimensional
axisymmetric region is developed. The boundary of the region
is defined by an arbitrary analytic function. The method uses a
coordinate transformation and an expansion in eigenfunctions. The
effectiveness is checked and confirmed by applying the method to a
particular example, which is a prolate spheroid.
Abstract: Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.
Abstract: The performance of mortar subjected to high
temperature and cooled in normal ambient temperature was examined
in the laboratory to comply with the situation of burning & cooling of
a structure. Four series of cubical (5 X 5 X 5 cm) mortar specimens
were made from OPC, and partial replacement (10, 15, 20, 25 &
30%) of OPC by Rice Husk Ash (RHA) produced in the uncontrolled
environment. These specimens were heated in electric furnace to 200,
300, 400, 500 and 7000C. The specimens were kept in normal room
temperature for cooling. They were then tested for mechanical
properties and the results shows that particular 20% RHA mixed
mortar shows better fire performance.
Abstract: This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The performances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.
Abstract: In this paper, the fuzzy linear programming formulation
of fuzzy maximal flow problems are proposed and on the basis of the
proposed formulation a method is proposed to find the fuzzy optimal
solution of fuzzy maximal flow problems. In the proposed method all
the parameters are represented by triangular fuzzy numbers. By using
the proposed method the fuzzy optimal solution of fuzzy maximal
flow problems can be easily obtained. To illustrate the proposed
method a numerical example is solved and the obtained results are
discussed.
Abstract: Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.
Abstract: In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based
on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.