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Translation by Propagandist Media MEMRI as a Case Study
No full textA Master of Arts thesis in Translation and Interpreting MATI (English/Arabic/English) by Rana Ahmad Salah entitled, “Translation by Propagandist Media MEMRI as a Case Study”, submitted in March 2017. Thesis advisor is Dr. Said Faiq. Soft and hard copy available.The Middle East Media Research Institute (MEMRI) TV is a media agency which portrays, to an English-speaking audience, a stereotypical representation of Islam through subjective and selective translation. Despite its accurate translations on a linguistic level, MEMRI practices paralinguistic manipulation through its selective choices for translation to further its ideological agenda. This thesis aims to explore MEMRI’s skopos-driven selective translation by discussing two narratives it constructs: the Allahu-Akbar narrative and the terrorisation of childhood narrative. The consequences of this Islamophobic frame by such narratives are then investigated. In conclusion, the impact of MEMRI’s selective approach to translation is proven to be a biased strategy for the achievement of its political purposes and the reinforcement of Islamophobic discourse.College of Arts and SciencesDepartment of Arabic and Translation StudiesMaster of Arts in English/Arabic/English Translation and Interpreting (MATI
Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
No full textA Master of Science thesis in Electrical Engineering by Mohammad Tarek Khayata entitled, "Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available.This work proposes a new method for renewable distributed generation (DG) allocation in smart grid. The main objective is to minimize the overall investment which includes the capital cost of DG units, the operation and maintenance costs of DG units, and the cost of purchasing energy from the grid. The proposed approach takes into consideration the uncertainty and variability associated with generation, demand, and energy cost in addition to the communication infrastructure which is the main contribution of this work. The communication infrastructure under the smart grid paradigm will allow real-time control of the system assets. Therefore, considering this property during the planning phase enhances the system performance and optimizes the overall investment. The proposed approach relies on developing probabilistic models for each generation technology, energy prices, and demand. Then, these models are combined into one multi-state gen-load-price probabilistic model that describes all possible conditions of the system. The number of states in the final model is a tradeoff between the accuracy of results and computational time. Genetic algorithm (GA) optimization technique is utilized in this study to solve the DG planning problem. Simulation results on a typical distribution system are provided to prove the effectiveness of the proposed approach in increasing the renewable DG penetration in smart grids while maximizing the profit of the investment. Moreover, the results obtained through the use of the proposed smart operation are compared with the conventional planning methodologies to demonstrate the targeted added value. A significant cost saving of 28.3% and 254% higher percentage of DG penetration are achieved with the proposed DGs curtailment technique to mitigate technical system violations, which proves the significant advantage of adopting smart grid operation in planning problems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
No full textA Master of Science thesis in Mechatronics Engineering by Hassan Abdul-Rahman Umari entitled, "Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees," submitted in May 2017. Thesis advisor is Dr. Shayok Mukhopadhyay. Soft and hard copy available.Efficient robotic navigation requires a predefined map. In order to autonomously acquire a map, it is desired that robots have the ability to explore unknown environments with minimum cost and time, while ensuring complete map coverage. Meeting these
requirements is challenging, and has attracted a lot of research. Various autonomous map exploration strategies exist, which direct robots to unexplored space by detecting frontiers. Frontiers are boundaries separating known space form unknown space. Usually frontier detection utilizes image processing tools like edge detection, thus limiting it to two dimensional (2-D) exploration. In this work we present a new exploration strategy based on the use of multiple Rapidly-exploring Random Trees (RRTs). The RRT algorithm is chosen because it is biased towards unexplored regions. Also, using RRT provides a general approach which can be extended to higher dimensional spaces. The proposed strategy is implemented and tested using the Robot Operating System (ROS) framework. Additionally this work uses local and global trees for detecting frontier points, which enables efficient robotic exploration. Further more, a marketbased task allocation strategy for coordination between multiple robots is adopted. Simulations and experimental results show that the proposed strategy can successfully extract frontiers, and explore the entire map in a reasonable amount of time, and with a reduced map exploration cost. It is also shown in this work that the proposed approach has the above mentioned performance benefits without substantially losing performance when compared against image processing-based frontier detection techniques in two dimensional spaces.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT)
No full textThe powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. The resulting adaptive, high-performance technique is called Genetic Algorithm with Domain-Trimming (GADT). As a proof of concept, the GADT is applied to a widely used benchmark problem. The 10-dimensional truss optimization benchmark problem has well documented global and local minima. The GADT is shown to outperform several published solutions. Subsequently, the GADT is deployed onto three-dimensional structural design optimization for offshore wind turbine supporting structures. The design problem involves complex least-weight topology as well as member size optimizations. The GADT is applied to two popular design alternatives: tripod and quadropod jackets. The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. The considered design variables are the truss members end node coordinates, as well as the cross-sectional areas of the truss members, whereas the constraints are the maximum stresses in members and the maximum displacements of the nodes. These constraints are managed via dynamically modified, nonstationary penalty functions. The structures are subject to gravity, wind, wave, and earthquake loading conditions. The results show that the GADT method is superior in finding best discovered optimal solutions
Modelling and performance analysis of biomass fast pyrolysis in a solar-thermal reactor
No full textSolar-thermal conversion of biomass through pyrolysis process is an alternative option to storing energy in the form of liquid fuel, gas, and biochar. Fast pyrolysis is a highly endothermic process and essentially requires high heating rate and temperature > 400 °C. This study presents a theoretical study on biomass fast pyrolysis in a solar-thermal reactor heated by a parabolic trough concentrator. The reactor is part of a novel closed loop pyrolysis-gasification process. A Eulerian–Eulerian flow model, with constitutive closure equation derived from the kinetic theory of granular flow and incorporating heat transfer, drying, and pyrolysis reaction equations, was solved using ANSYS Fluent computational fluid dynamics (CFD) software. The highly endothermic pyrolysis was assumed to be satisfied by a constant solar heat flux concentrated on the reactor external wall. At the operating conditions considered, the reactor overall energy efficiency was found equal to 67.8% with the product consisting of 51.5% bio-oil, 43.7% char, and 4.8% noncondensable gases. Performance analysis is presented to show the competitiveness of the proposed reactor in terms of thermal conversion efficiency and environmental impact. It is hoped that this study will contribute to the global effort on securing diverse and sustainable energy generation technologies
Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
No full textA Master of Science thesis in Chemical Engineering by Rehab Ibrahim Khawaga entitled, “Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment”, submitted in December 2017. Thesis advisors are Dr. Sameer Al-Asheh and Dr. Nabil Abdel Jabber and thesis co-advisor is Dr. Mohamed Abouleish. Soft and hard copy available.Chlorination in wastewater treatment is regarded as a complicated process due to its ammonia and nitrite content. Chlorine added to such systems reacts with ammonia undergoing episodes of complex reactions, resulting in the chlorination breakpoint behavior. Most of the available chlorination mechanistic models are not easily applied which have restricted their practical utilization in treatment plants. In this study, a new mechanistic model for the chlorination breakpoint in an ammonia-nitrite system was developed with a user-friendly interface designed to be applicable to conditions occurring in wastewater treatment plants. The model was validated against laboratory studies reported in the literature and was also applied to forecast the chlorine residue in a wastewater treatment plant in the region. The model simulated both experimental and field data with high precision. Using the devised model, a full 43 factorial design was carried out to investigate the main effects of ammonia, nitrite, contact time, and their interactions. The outcome of the factorial designs has shown that as the ammonia proportion increases in the system, its effect prevails and diminishes that of nitrite. The carried out studies showed that this phenomenon occurs at ammonia/nitrie (A/N) ratio of 3. Artificial Neural Network modelling (ANN) was also applied to forecast the doses at which maximum and minimum total residual chlorine (TRC) of the breakpoint curve occur based on data generated using the developed model. ANN modelling was then integrated with fuzzy logic control (FLC) to optimize the chlorination process by minimizing its cost and maximizing its efficiency while operating within the plant’s budget. The developed FLC platform was applied to the Jebel Ali wastewater treatment plant and was able to improve the disinfection quality and reduce chlorine gas consumption by 18.18 %.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
Grass filter strip residence time- trap efficiency relationship
No full textThis paper investigates the relationship between trap efficiency and residence time in vegetative filter strips under unsteady flow conditions. A mathematical model, based on a kinematic‐wave formulation of overland flow and a mass balance equation for suspended sediments, is employed. An empirical equation is used to estimate sediment removal. The governing equations are written and solved numerically in terms of a set of dimensionless variables. The results indicate that the relationships between the trap efficiency and residence time depend on the shape of the inflow hydrograph. Further analysis of results identified another non‐dimensional parameter that can predict the trap efficiency if only the volume and the peak rate of inflow are known. While the mathematical model employed includes many elements of the sophisticated vegetative filter strip models previously reported, the resulting charts are as easy to use as the oversimplified design methods currently in use
Effective Approach for Increasing the Heteroatom Doping Levels of Porous Carbons for Superior CO2 Capture and Separation Performance
No full textDevelopment of efficient sorbents for carbon dioxide (CO2) capture from flue gas or its removal from natural gas and landfill gas is very important for environmental protection. A new series of heteroatom-doped porous carbon was synthesized directly from pyrazole/KOH by thermolysis. The resulting pyrazole-derived carbons (PYDCs) are highly doped with nitrogen (14.9–15.5 wt %) as a result of the high nitrogen-to-carbon ratio in pyrazole (43 wt %) and also have a high oxygen content (16.4–18.4 wt %). PYDCs have a high surface area (SABET = 1266–2013 m2 g–1), high CO2 Qst (33.2–37.1 kJ mol–1), and a combination of mesoporous and microporous pores. PYDCs exhibit significantly high CO2 uptakes that reach 2.15 and 6.06 mmol g–1 at 0.15 and 1 bar, respectively, at 298 K. At 273 K, the CO2 uptake improves to 3.7 and 8.59 mmol g–1 at 0.15 and 1 bar, respectively. The reported porous carbons also show significantly high adsorption selectivity for CO2/N2 (128) and CO2/CH4 (13.4) according to ideal adsorbed solution theory calculations at 298 K. Gas breakthrough studies of CO2/N2 (10:90) at 298 K showed that PYDCs display excellent separation properties. The ability to tailor the physical properties of PYDCs as well as their chemical composition provides an effective strategy for designing efficient CO2 sorbents
Use of Model Predictive Control and Artificial Neural Networks to Optimize the Ultrasonic Release of a Model Drug From Liposomes
No full textThe use of echogenic liposomes to deliver chemotherapeutic agents for cancer treatment has gained wide recognition in the last 20 years. Cancerous cells can develop multiple drug resistance (MDR), in part, due to the drop in concentration of chemotherapeutic agents below the therapeutic levels inside the tumor. This suggests that MDR can be reduced by controlling the level of drug release in the diseased area. In this paper, a model predictive controller based on neural networks is proposed to maintain a constant chemotherapeutic release at the cancer site. The proposed system was able to follow the set point by varying the U.S. intensity within preset constraints. The system simulated model is viable and it showed a high average fit when stimulated with variable input variations, indicating the robustness of the nonlinear model. By maintaining a constant release of the drug so that the concentration level is above a certain threshold, we hope to reduce cancer resistance towards chemotherapeutic agents
CEFR in UAE Public Schools: Pedagogical Impacts
No full textA Master of Arts thesis in Teaching English to Speakers of Other Languages (TESOL) by Seyed-Reza Hosseinifar entitled, "CEFR in UAE Public Schools: Pedagogical Impacts," submitted Jauary 2017. Thesis advisor is Dr. Ahmad Al-Issa. Soft and hard copy available.The Ministry of Education (MOE) in Dubai used the Common European Framework of Reference (CEFR) to develop the English Curriculum Framework (ECF) in 2011 - a framework that was piloted in 39 Madares Al Ghad (MAG) Schools in the United Arab Emirates (UAE) between 2011 and 2015. No study has been published to cast light on the impacts of adopting, adapting and implementing the CEFR in UAE public schools so far. This study attempts to act as a forerunner of such research. It examined 85 teachers', 31 teacher trainers' and 3 MOE administrators' perceptions of how lesson planning, teaching and assessment practices changed after the ECF had been implemented. Quantitative and qualitative data collected from semi-structured questionnaires were cross-checked against qualitative data collected from three focus group discussions. Both descriptive and inferential statistics were used to analyze quantitative data. Overall, it seems that after the ECF had been implemented, (a) teachers' lesson plans reflected curriculum standards and matched students' needs and interests more often; (b) curriculum strands, listening, speaking, reading and writing, especially the first two, were addressed more often; (c) the frequency of teaching vocabulary and pronunciation increased; (d) teachers' pedagogy became more action-oriented as there was a shift toward communicative, collaborative and self-reflective activities, and (e) instructional and assessment practices became more transparent. However, the participants also reported that they had faced some challenges during the early stages of the ECF implementation. Providing continuous professional development and preparing suitable instructional materials were the two key measures that helped the participants overcome the challenges they had faced. A few barriers persisted throughout the implementation.College of Arts and SciencesDepartment of EnglishMaster of Arts in Teaching English to Speakers of Other Languages (MA TESOL