The habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flowering to ripening of fruit in the morning and sometimes in afternoon also. The range of
the birds was recorded from 6 to 61 with a mean individual of 36.03 ± 15.37 hovering for
1.83 hr daily. This may be the behaviour for the feeding pattern of these flying insectivorous
birds which was not seen in other crop-fields with same insect diversity describing it as not
the only reason for this behaviour. To reveal this poorly understood behaviour of flying
insectivore birds, a detailed long term behavioural study with gut content analysis is needed to
explain the particular reason behind this behaviour of Barn swallows which will support the
conservation of these birds and control their population decline.
A study of the Torymid collection of Iraq. resulted in undescribed species of the genus
Liodontonierus Gah. L. longicorpus sp. n. with 2 figures.
In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.
Leucine amino peptidases (LAP; EC 3.4.11.1) constitute a diverse set of exopeptidases that catalyze the hydrolysis of leucine residues from the amino-terminal of protein or peptide substrates, (LAP) are present in animals, plants, and microbes. In this study, leucine amino peptidase was purified partial from Arachis hypogaea seeds by using gel filtration chromatography Sephadex G-100. The enzyme was purified 3.965 fold with a recovery of 29.4%. Its pH and temperature optimum were(8.7) and (37oC), respectively. The results show novel properties of LAP from Arachis hypogaea L. or peanut. The Km value for LAP (77 mM), with V max (1538 m mole min-1). We recommend a separate isoenzymeof the enzyme (LAP) from Arachis hypogaea on L. peanut seeds a
... Show MoreGenus Eucalyptus belongs to the family Myrtaceae that consists of more than 700 species, various hybrids and varieties. The majorly distributed species that are grown in Iraq are Eucalyptus alba, E. macarthurii, E. siderophloia and E. camaldulensis, E. tereticornis, E. vicina. Most Eucalyptus species are highly dependent on rainfall, and this is challenged by climatic changes owing to global warming making it difficult to effectively match the availability of mature trees and the market demand, especially for use as power transmission poles. With the widespread availability of other naturally occurring Eucalyptus species, it has become important to determine the genetic diversity and to analyze the phenotypic tra
... Show MoreThe speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
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