Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
The bioequivalence of a single dose tablet containing 5 mg amlodipine as a test product in comparison to Norvasc® 5 mg tablet (Pfizer USA) as the reference product was studied. Both products were administered to twenty eight healthy male adult subjects applying a fasting, single-dose, two-treatment, two-period, two-sequence, randomized crossover design with two weeks washout period between dosing. Twenty blood samples were withdrawn from each subject over 144 hours period. Amlodipine concentrations were determined in plasma by a validated HPLC-MS/MS method. From the plasma concentration-time data of each individual, the pharmacokinetic parameters; Cmax, Tmax, AUC0-t, AUC0-
This research was conducted in order to monitor and measure the dimensions of media policy in satellite channels directed from the point of view of the communicator, and this research is classified among the descriptive studies, as the researcher used the survey method to answer the questions that were formulated in light of the research problem represented by the main question: What are the dimensions of media policy in Directed satellite channels? .
To achieve the objectives of the study, the researcher used the following tools:
The questionnaire, in order to survey the attitudes of communicators about the extent to which the media policy during crises reflects on their professional standards. The research community is represente
representing the media and communication problems and phenomena fertile material and of great importance in the media research, especially as they relate to various aspects of life and its impact on the culture of the community and on individuals and public opinion about the behavior of the various issues. The media incitement to violence and hatred of the most prominent media phenomena that increased the danger and expanded not at the local level, but also in the world. So we found it is important to study this problem from the standpoint of academic and professional. And according to the progress of this research is trying to answer a number of questions including:
A. What are the Iraqi Satellite TV channels most watched and follow
In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.
This research is based on the idea of showing the extent to which the public relies on satellite channels as sources for news of the demonstrations in Iraq .This was the essence of the problem for which the researcher set several goals, including knowing the public’s confidence in the news of these satellite channels and comparing them with others. The researcher chose an available intended sample of (117) respondents in Baghdad - Karkh and Rusafa by adopting the survey method and applying a questionnaire form and the theory of media dependence for the period from 15/11/2019 to 1/1/2021 . By using statistical methods, the researcher reached many results, the most important of which are: Satellite channels are a source for 79% of the pu
... Show MoreBored piles settlement behavior under vertical loaded is the main factor that affects the design requirements of single or group of piles in soft soils. The estimation of bored pile settlement is a complicated problem because it depends upon many factors which may include ground conditions, validation of bored pile design method through testing and validation of theoretical or numerical prediction of the settlement value. In this study, a prototype single and bored pile group model of arrangement (1*1, 1*2 and 2*2) for total length to diameter ratios (L/D) is 13.33 and clear spacing three times of diameter, subjected to vertical axial loads. The bored piles model used for the test was 2000
... Show MoreA study of taxonomic quality of soil algae was conducted with some environmental variables in three sites of local gardens (Kadhimiya, Adhamiya and Dora) within the governorate of Baghdad for the period from October 2016 to March 2017. The study identified 28 species belonging to 16 species in which the predominance of blue green algae (18 species) Followed by Bacillarophyta algae (7 species) and three types of Chlorophyta. The study showed an increase in species of Oscillatoria. The results showed no significant differences between sites in temperature, pH and relative humidity, while there were clear differences between sites for salinity and nutrient The study showed a difference of irrigation water quality and use of different fertilize
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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