Deception is defined as a linguistic and non-linguistic behavior that is used in interaction in order to make the addressees believe what is believed to be false or lack evidence. McCornack (1992) classifies deception into four manipulative strategies (i.e., fabrication, distortion, equivocation and concealment), other scholars argue that deception encompasses the strategies of “fabrication (outright lying), equivocation (being vague and ambiguous), or concealment (with holding relevant information) Thus, the present study investigates the deception strategies and motives that are used by Johnny Depp and Amber Heard during their defamation trials. Qualitative and quantitative methods are employed when analyzing the data in question. The first method is achieved via using Buller & Burgoon’s (2004) strategies of deception and Ekman’s (1995) motives of deception, while the second method is achieved via counting frequencies and percentages. It is found that the strategies of fabrication and equivocation are frequently used by Johnny Depp, while the strategies of fabrication and concealment are frequently used by Amber Heard. It is concluded that deception can be achieved via using the strategy of fabrication in order to avoid embarrassment, get rid of an awkward situation and get the admiration of others.
Recently, Social Sustainability has gained significant value as it was considered by the late studies as a principal dimension along with the environmental and economic sustainability. And because of, on the other hand, the significant social role of the school for forming the student’s personality, this research is an appeal for rehabilitating and promoting Iraqi Schools according the issue of social sustainability.As there is no evaluation for the Iraqi Schools, the research is dedicated to this problem, aiming to carry out the stated evaluation and define the design treatments needed for the rehabilitation process. To achieve this goal, a theoretical background for the concept of social sustainability, its criteria, the school and i
... Show MoreThis research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB
... Show MoreThis Paper assesses the knowledge management system (KMS) requirements at Al-Ameed University concerning ISO 30401:2022. Specifically, the research aims to ascertain the degree to which international standards have been complied with and gaps that have been identified. A case study was conducted using field observations, interviews, and checklists to assess the institution's compliance with the KMS framework. The level of implementation and documentation of knowledge management processes was assessed using a seven-point scale. The findings reveal that Al-Ameed University has severe gaps in knowledge creation, sharing, and support for knowledge management in terms of strategic leadership. While certain elements like availability of r
... Show MoreThe nonlinear refractive (NLR) index and third order susceptibility (X3) of carbon quantum dots (CQDs) have been studied using two laser wavelengths (473 and 532 nm). The z-scan technique was used to examine the nonlinearity. Results showed that all concentrations have negative NLR indices in the order of 10−10 cm2/W at two laser wavelengths. Moreover, the nonlinearity of CQDs was improved by increasing the concentration of CQDs. The highest value of third order susceptibility was found to be 3.32*10−8 (esu) for CQDs with a concentration of 70 mA at 473 nm wavelength.
This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others
In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.
Form the series of generalization of the topic of supra topology is the generalization of separation axioms . In this paper we have been introduced (S * - SS *) regular spaces . Most of the properties of both spaces have been investigated and reinforced with examples . In the last part we presented the notations of supra *- -space ( =0,1) and we studied their relationship with (S * - SS *) regular spaces.
Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin
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