The aim of this research is to identify the effect of Webinar technique on digital culture in the College of Education for pure sciences at Ibin Haitham, University of Baghdad. The research samples consisted of (68) male and female students from the Chemistry Department who are following classes during the (2019- 2020) academic year. The samples represent (42%) of the total number of (162) students split into control and experimental groups. For this purpose, the scientific contents for testing were determined. The experimental part is based on analysis of the results from experiments in (preliminary standard solutions, refractive index, Beer-Lambert law). To achieve the aim of the research in testing the measure of student's digital culture, the researcher developed two testing mechanisms, the first one consists of 20 items, (15) of them represent multiple choice type of questions and the remaining (5) represent descriptive answers. The other is to develop a measure of digital culture. This one consists of (38) multiple-choice questions, each with (5) alternatives. The results showed a significant statistical difference in the measure of the digital culture between the two groups in favor of the experimental group which was taught using the Webinar technique.
The present work is qualitative descriptive. It aims to examine the idiosyncratic schema when deciphering the selected violence-based panel from Nasser Ibrahim’s caricatures. The researchers accordingly adopted part of Sharifian’s (2011) Cultural Schema model, particularly that part that is concerned with the examining the micro/idiosyncratic level of understanding. The study has revealed that the participants have not only differed among themselves regarding the way a figure is being denotatively conceptualized, they also highlighted different exact conceptualizations for the same figure, such as: using various adjectives that reflect various levels of intensity, emphasizing the behavioral aspect or the appearance of the figure, ado
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p
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Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.
Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.
This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis
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