In this study, the aqueous extract of (Typha domingensis Pers.) pollen grain (qurraid) to know its ability to manufacture silver nanoparticles. Qurraid is a semi-solid yellow food substance, sold in Basra markets and eaten by the local population. It is made from the pollen of the T. domingensis Pers. plant after being pressed and treated with water vapor. The Gas chromatography–mass spectrometry (GC-MS) reaction was done to identify the active compounds of qurraid aqueous extract. The ability of the aqueous extract of qurraid to manufacture silver nanoparticles was tested, and the construction of silver nanoparticles was inferred by the reaction mixture's color, which ranged from yellow to dark brown. The synthesized silver nanoparticles (AgNPs) were described by UV-Vis, FTIR, XRD, SEM, and EDX. Then its anti-bacterial activity was estimated by the agar well diffusion method. The findings of the GC-MS analysis of the qurraid aqueous extract showed the major components with their ratio were: 5-Hydroxymethylfurfural with RT% 13.6196, 3-Deoxy-d-mannoic lactone 6.4285,. alpha.-L-lyxo-Hexopyranoside, methyl 3-amino-2,3,6-trideoxy- 4.264, 4H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl- 3.2078, and 1,3-Methylene-d-arabitol 3.1257. The construction of silver nanoparticles was described by spectroscopic methods, where the highest peak was recorded at 400nm by UV-Vis spectrum, which indicates the silver spectrum. The mineral nature of AgNPs was confirmed by XRD analysis, in which the highest peaks were, 111, 300, and 330 were recorded. In addition, the qrdAgNPs nanoparticles were spherical with sizes ranging from 20-70nm. The results of the EDX confirmed that the chemical composition of AgNPs was silver. The ability of the AgNPs was tested against four bacterial species, three of which were Gram-negative Escherichia coli A1, Escherichia coli A2, Alcaligenes faecalis AL1, and the fourth was Gram-positive bacteria Bacillus zanthoxyli B1 , which were identified by traditional and molecular methods using 16SrRNA gene sequencing, antibacterial activity results of AgNPs showed that it increases with increasing of AgNPs concentration, and the most sensitive species to silver particles was Alcaligenes faecalis AL1bacteria.
This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as
... Show More<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi
... Show MoreThis paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
... Show MoreA number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V col
... Show MoreTThe property of 134−140Neodymium nuclei have been studied in framework Interacting Boson Model (IBM) and a new method called New Empirical Formula (NEF). The energy positive parity bands of 134−140Nd have been calculated using (IBM) and (NEF) while the negative parity bands of 134−140Nd have been calculated using (NEF) only. The E-GOS curve as a function of the spin (I) has been drawn to determine the property of the positive parity yrast band. The parameters of the best fit to the measured data are determined. The reduced transition probabilities of these nuclei was calculated. The critical point has been determined for 140Nd isotope. The potential energy surfaces (PESs) to the IBM Hamiltonian have been obtained using the intrin
... Show MoreThis article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.