Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In addition, the energy, and the entropy which based on the gray level values in an image is too considered as the features. In addition to statistical approaches, models of artificial intelligence produce a desirable methodology that enhances performance in information retrieval systems, and the genetic algorithm depicts one of them. The GA is preferred for its power and because it can be used without any specific information of the domain. The experimental results conclude that using GA gives a good performance and it decreases the average search time to (60.15 milliseconds) compared with (722.25milliseconds) for traditional search.
The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ
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Laboratory experiments were carried out in Technical college AL- Mussiab / Babylon during 2005 to study bioactivity of different concentration from ( aqueous , alcohol and hexane) extracts of bee venom collected from different workers of bees against some bacterial types that cause European Foul – brood Melissococcus plutom , Bacillus alvei and B. letrosporus which had been isolated from infected arched with disease . Two diffusion methods (digging and paper discs) were followed for the extraction of the venom . Results showed that digging diffusion method was more efficient for test of bacterial inhibition which led to increase the activity of bee venom extract with general a
... Show MoreThe amino thiadiazole [I] on treatment with aromatic aldehydes yielded Schiff bases [IIa-c] , which cyclized to thiazolidinone [IIIa-c] derivatives by reaction with thioglycolic acid .Reaction of carbon disulfide and methyl iodide with [I] gavedithiomethyl[IV] which on treatment with o-phenylenediamine gave the condensed N-Imidazolythiadiazolylamine [V] , However , reaction of [I] with phenylisocyanate and phenylisothiocyanate afforded the carbamideand carbothiamide derivatives[VI.VII]a-c. The structure of these compounds was characterized from their melting point , FTIR spectroscopy and elementalanalysis
Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem
... Show MoreThe fingerprinting DNA method which depends on the unique pattern in this study was employed to detect the hydatid cyst of Echinococcus granulosus and to determine the genetic variation among their strains in different intermediate hosts (cows and sheep). The unique pattern represents the number of amplified bands and their molecular weights with specialized sequences to one sample which different from the other samples. Five hydatitd cysts samples from cows and sheep were collected, genetic analysis for isolated DNA was done using PCR technique and Random Amplified Polymorphic DNA reaction(RAPD) depending on (4) random primers, and the results showed:
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It is not often easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom, a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.
The feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, objec
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