Hyperbole is an obvious and intentional exaggeration in the sense that it takes things to such an extreme that the audience goes too far and then pulls itself back to a more reasonable position, i.e. it is an extravagant statement or figure of speech not intended to be taken literally. This paper focuses on the formal and functional perspectives in the analysis of hyperbole which American candidates produce in their speeches in electoral campaigns, for it is hypothesized that candidates in their electoral campaigns use hyperbolic expressions excessively to persuade voters of the objectives of their electoral campaign programs. Hence, it aims to analyze hyperbole in context to determine the range of pragmatic functions that this figure fulfills and to present a formal analysis of hyperbole to demonstrate which formal realizations employed with a hyperbolic function are more or less likely to serve the persuasive aspect of hyperbole. To achieve these aims, three campaign speeches by Barack Obama from the 2012 Presidential Election, chosen at random from the American Presidency Project, were analyzed, and the occurrences of hyperbolic expressions identified. The frequency findings, in terms of the formal analysis, reveal that the exaggerated content found in single words is the type which represents the most common realization of hyperbole in Obama's speeches. In terms of the functional analysis, the results reveal that emphasis and evaluation appear to be the most prominent functions suggesting that the intended impression on voters is only constructed through the combined effects of these two devices.
Image 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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Background: Periodontal diseases (PD) are inflammatory conditions of the tissues supporting the teeth, most often gingivitis and periodontitis. Maxillary chronic rhinosinusitis (MCRS) is the inflammation of the maxillary sinuses which is last for at least 12 consecutive weeks duration. Aims of study: Distribution of periodontal diseases among patients with Maxillary chronic rhinosinusitis according to gender and age. Materials and methods: Males and females subjects (25-45 years), divided into two groups; 150 patients suffer from MCRS and 130 subjects without MCRS. Clinical periodontal parameters; Plaque Index (PL.I), Gingival Index (G.I), Probing Pocket Depth (PPD), Clinical Attachment Level (CAL) and Bleeding On Probing (BOP) recorded f
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This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.
Molecular barcoding was widely recognized as a powerful tool for the identification of organisms during the past decade; the aim of this study is to use the molecular approach to identify the diatoms by using the environmental DNA. The diatom specimens were taken from Tigris River. The environmental DNA(e DNA) extraction and analysis of sequences using the Next Generation Sequencing (NGS) method showed the highest percentage of epipelic diatom genera including Achnanthidium minutissimum (Kützing) Czarnecki, 1994 (21.1%), Cocconeis placentula Ehrenberg, 1838 (21.3%) and Nitzschia palea (Kützing) W. Smith, 1856 (16.3%).
Five species of diatoms: Achnanthidiu
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The performance of composite prestressed concrete beam topped with reinforced concrete flange structures in fire depends upon several factors, including the change in properties of the two different materials due to fire exposure and temperature distribution within the composition of the composite members of the structure. The present experimental work included casting of 12 identical simply supported prestressed concrete beams grouped into 3 categories, depending on the strength of the top reinforced concrete deck slab (20, 30, and 40 MPa). They were connected together by using shear connector reinforcements. To simulate the real practical fire disasters, 3 composite prestressed concrete beams from each group were exposed to high t
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Exponential distribution is one of most common distributions in studies and scientific researches with wide application in the fields of reliability, engineering and in analyzing survival function therefore the researcher has carried on extended studies in the characteristics of this distribution.
In this research, estimation of survival function for truncated exponential distribution in the maximum likelihood methods and Bayes first and second method, least square method and Jackknife dependent in the first place on the maximum likelihood method, then on Bayes first method then comparing then using simulation, thus to accomplish this task, different size samples have been adopted by the searcher us
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In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement
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Background: Since the invention of laser in 1960, lasers have been developed and approved in many fields. Lasers can now be regarded as practical tools with unique properties that have been utilized effectively in several applications in fields of medical and biological sciences.Objectives: The aim of the current study was to preparation of vaccines (live attenuated and killed) by irradiation of the bacteria by the low level diode laser.Methods: six bacterial isolates were isolated from human samples of diabetic foot infections, which used for preparation of vaccines. The experiment was conducted on fifteen adult male rabbits; they were divided into three groups with 5 rabbits each. Blood samples were collected from the marginal ear vein
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