The expansion of the social media environment has created its own linguistic realities which involve more colloquial communication and practical employment of language. This research focuses on nominalizations in detail, which are originally formed words that have been changed for a noun role. These nominalizations are examined within the context of Facebook posts. The research aims to discover the various nominalizations used and how often they appear in a large sample of data from Public Facebook Posts Corpora. Computational linguistics opened new fields of study and enabled researchers to study large amounts of data easily, making it easier to identify patterns. Two computational methods of identifying nominalization in a large dataset were tested and evaluated from different aspects. Additionally, machine learning analysis tools were conducted to determine how nominalization affects the complexity and readability of the texts. Accordingly, Flesch-Kincaid Grade Level and Flesch Readability results were studied to identify nominalizations’ effect on the texts. The results present a high density of verbal nominalizations indicating that there is a preference to refer to actions or processes in an abbreviated manner. Instead, the study also explores the semantic and functional properties of nominalizations, discovering their employment for emotions and opinions, focusing on the ideas and informal nature of Facebook. Despite what the readability formulas imply about the relation between nominalization density and text difficulty, the research does not discount the fact that these metrics have their shortcomings, especially when comprehending direct user understanding is not taken under consideration. In conclusion, this study adds to the current literature on nominalizations by identifying their role in the social media discourse and importing important knowledge on the progressive changes in online linguistic usage
This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
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Metoclopramide (MCP) ion selective electrodes based on metoclopramide-phosphotungstic acid (MCP-PT) ion pair complex in PVC matrix membrane were constructed. The plasticizers used were tri-butyl phosphate (TBP), di-octyl phenyl phosphonate (DOPP), di-butyl phthalate (DBPH), di-octyl phthalate (DOP), di-butyl phosphate (DBP), bis 2-ethyl hexyl phosphate (BEHP). The sensors based on TBP, DOPP, DBPH and DOP display a fast, stable and linear response with slopes 59.9, 57.7, 57.4, 55.3 mV/decade respectively at pH ranged 2-6. The linear concentration range between 1.0×10-5 – 1.0×10-2 M with detection limit 3.0×10-6 and 4.0×10-6 M for electrodes using TBP, DOPP and DBPH while e
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The important factor in the success of construction projects is its ability to objective estimate of the cost of the project and adapt to the changes of the external environment, which is affected by a lot of elements and the requirements of the competitive environment. The faces of those projects are several problems in order to achieve particular goals. To overcome these difficulties has been the development of research in the last two decades and turn the focus on the role of the cost of project management, by providing information and assist management in planning and control of the budget among the main elements of the project, namely, (time-cost-quality),The research aims at the possibility of developing and implementing mechanisms
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.
Cognitive stylistics also well-known as cognitive poetics is a cognitive approach to language. This study aims at examining literary language by showing how Schema Theory and Text World Theory can be useful in the interpretation of literary texts. Further, the study attempts to uncover how readers can connect between the text world and the real world. Putting it differently, the study aims at showing how the interaction between ‘discourse world’ and ‘text world’. How readers can bring their own experience as well as their background knowledge to interact with the text and make interpretive connections.
Schema and text world theories are useful tools in cognitive stylistic stud
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
... Show MoreDrilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
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The aim of this work is to detect the best operating conditions that effect on the removal of Cu2+, Zn2+, and Ni2+ ions from aqueous solution using date pits in the batch adsorption experiments. The results have shown that the Al-zahdi Iraqi date pits demonstrated more efficient at certain values of operating conditions of adsorbent doses of 0.12 g/ml of aqueous solution, adsorption time 72 h, pH solution 5.5 ±0.2, shaking speed 300 rpm, and smallest adsorbent particle size needed for removal of metals. At the same time the particle size of date pits has a little effect on the adsorption at low initial concentration of heavy metals. The adsorption of metals increases with increas
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