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Review of current technologies used in municipal solid waste-to-energy facilities in Canada
No full textThe increasing amounts of municipal solid waste produced accompanied with the rising need for energy has caused a growth in the popularity of waste-to-energy (WTE) facilities as waste and energy solutions for many regions in Canada. The recent commercially viable WTE facilities across Canada show that the main technologies used in Canada are incineration, gasification, and plasma gasification. The aim of this study is to present these WTE technologies through the examination of case studies taken from the existing facilities across Canada. Background information on case studies, information on the WTE process, and a comparison highlighting the differences between the facilities are discussed
Solar Updraft Tower In Al-Ain
No full textA poster submitted in ENG 207 taught by Dr. David Prescott for the Fall 2014 semester.In recent years, the UAE has taken significant steps to protect the environment, such as building shams solar tower in Abu-Dhabi. The main source of air pollution in the UAE is the oil and gas industry, followed by the power and transportation sectors
Saturation Loadings on 13X (Faujasite) Zeolite above and below the Critical Conditions, Part I: Alkane Data Evaluation and Modeling
No full textThe saturation loadings for subcritical adsorption of n-, iso- and neo alkanes C1 –C8 in 13X zeolite are modeled using the modified Rackett model of Spencer and Danner (1972) for the saturated liquid densities combined with crystallographic data for the 13X zeolite. For validation of this model, alkane adsorption data in the literature is first critically evaluated and then compared to the model. The saturation loading of each isotherm that approaches saturation is extracted from the data. Log-log plots are used to determine whether each isotherm is near saturation; isotherms that exhibit a [del]lnq⁄[del]lnp slope of zero at their maximum pressure point are assumed to be saturated. Isotherms not fulfilling this criterion are deemed unsaturated and not considered further. The theoretical equation satisfactorily models the available experimental data for the n- alkanes. However, steric factors are required for the model to fit iso alkanes and neo-pentane. For supercritical temperatures, no model presently exists to explain the data. However, the data are satisfactorily modeled with an equation of the form qmax = 8.5 ± 2.5 g/100 g
Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition
No full textThis paper proposes a novel approach to continuous Arabic Sign Language recognition. We use a dataset which contains 40 sentences composed from 80 sign language words. The dataset is collected using sensor-based gloves. We propose a novel set of features suitable for sensor readings based on covariance, smoothness, entropy and uniformity. We also propose a novel classification approach based on a modified polynomial classifier suitable for sequential data. The proposed classification scheme is modified to take into account the context of the feature vectors prior to classification. This is achieved through the filtering of predicted class labels using median and mode filtering. The proposed work is compared against a vision-based solution. The proposed solution is found to outperform the vision-based solution as it yields an improved sentence recognition rate of 85 %
Ideal Safe Building
No full textA poster submitted in ENG 207 taught by Dr. David Prescott for the Fall 2014 semester.Natural disasters such as earthquakes, tsunamis, fires, and excessive winds are increasing worldwide. Areas on the north coast of the United Arab Emirates (UAE) such as Ras alKhaimah and Fujairah, in addition to some parts of Oman are highly prone to such disasters, because they are the closest areas to the sea
Liposomal drug release using ultrasound and modeling release dynamics for model predictive controller design
No full textA Master of Science thesis in Electrical Engineering by Hesham Gamal Moussa entitled, "Liposomal drug release using ultrasound and modeling release dynamics for model predictive controller design," submitted in June 2015. Thesis advisors are Dr. Nasser Qaddoumi and Dr. Ghaleb Husseini. Soft and hard copy available.Chemotherapy is widely used for cancer treatment; however, it causes unwanted side effects in patients such as fatigue, weight loss, pain, hair fall and nausea. Those side effects are due to the fact that most of the currently used therapeutic agents are in fact toxic to several organs, including the heart. In addition, many of them lead to the death of both cancerous and healthy cells. In the traditional way of treatment, when the patient was injected with the drug, a high dosage was required so that enough could reach the cancer cells and destroy them. These high dosages, however, can cause more harm than benefit, since they are responsible for the death of many healthy cells. To avoid these adverse effects, nanocarriers, called liposomes, have been developed, which can be loaded with the chemotherapeutic agents, and can be chemically modified to circulate for long periods in the blood stream while encapsulating the drugs and resisting any premature leakages. Additionally, ligands can be conjugated to their surface, allowing for their specific binding to receptors overexpressed on the surface of cancer cells and the subsequent internalization via endocytosis. Using ultrasound (US) as a triggering mechanism, the release of the drug is controlled temporally and spatially as it is induced inside the cells, hence avoiding drug release in systemic circulation, which in turn reduces the undesired side effects of conventional chemotherapy. US is of great interest to be used as a triggering technique as there is a lot of published work proving its usability in causing release from liposomes. Most of the work uses low frequency US as it causes the release at lower power densities; however, it is hardly focused unlike US at higher frequencies. The developed liposomes were tested against low frequency US (20 kHz) and focused-US at 1 MHz and 3 MHz and the results were compared to the literature. Moreover, the kinetics of the release were modeled to be used for many applications such as control systems and elimination of the need for further exhaustive laboratory experimentation.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression
No full textThis paper introduces two polynomial regression solutions for error concealment by predicting the values of motion vectors of lost macroblocks. The two solutions are online and offline polynomial regression modeling. In the former solution, the regression model is built during the decoding process whilst in the latter solution; the model is built during the encoding or the transcoding process and then used at the decoder for concealment. Both solutions make use of the spatially and temporally neighboring motion vectors for building the regression models. The advantages and disadvantages of the proposed solutions are elaborated upon. In comparison to existing work, the experimental results show that the proposed solutions have clear advantages of computational time requirements and motion vector prediction accuracy
Motivational Influences on Adult Arab Learners of English in the UAE
No full textA Master of Arts thesis in Teaching English to Speakers of Other Languages (TESOL) by Nour Al Okla entitled, "Motivational Influences on Adult Arab Learners of English in the UAE," submitted June 2015. Thesis advisor is Dr. Sara Cotterall. Soft and hard copy available.This study explores the motivational influences that impact seven Arab undergraduate learners of English in the UAE as they pursue two semesters of study. The study investigates the role of English in the participants' lives and the different factors that influence their motivation to learn and use English in the multi-national context of the UAE. During a sixteen-week period, three rounds of interviews with the participants were conducted and participants' written responses to four written prompts and a self-portrait were collected to obtain data on the participants' beliefs, emotions, and expectations of learning English. The study draws on Dӧrnyei's L2 motivational self-system (2005, 2009) to explore the role of English in learners' representations of themselves in the future and the extent to which they consider English a language they ought to learn. The findings of the study suggest that the principal motivational influences affecting the participants' language learning were their previous learning experiences, their personal orientations towards the language, and contextual factors in their formal and informal learning setting. Furthermore, the study highlighted the diversity, dynamicity and complexity of the construct of learner motivation in the learners' learning experiences. Despite apparent similarities amongst the study participants, the data revealed significant differences in the ways they responded to the learning setting, the extent to which they used English outside of class and their perception of the role of English in their lives. The data also reflected change over time in participants' emotions, preferences and investment in the language. Analysis of the data revealed complex interactions amongst the unique characteristics of individual learners and aspects of their motivation resulting in the complex, dynamic system known as the L2 motivational self-system (Dӧrnyei, 2005, 2009). The study calls for raising learners' awareness of the factors which influence their motivation and strategies which enable them to manage their emotions during the ongoing learning process. It also suggests raising language teachers' awareness of the complexity, dynamicity, and uniqueness of language learner motivation so that they can better monitor and address the multifaceted influences that impact their learners' motivation in different contexts.College of Arts and SciencesDepartment of EnglishMaster of Arts in Teaching English to Speakers of Other Languages (MA TESOL
Workforce localization and HRM practices in the Gulf countries: a literature review
No full textAs members of the Gulf Cooperation Council (GCC), the states of Bahrain, Kuwait, Qatar, Oman, Saudi Arabia and the United Arab Emirates pursue localization as a government policy aimed at increasing the participation of national citizens in the private sector. Workforce localization programs can be described as the recruitment and development of national citizens to increase their employability, thereby reducing the country’s dependence on an expatriate workforce (Cave, 2004). Government legislation to enhance workforce localization has changed the human resources landscape in the GCC (Randeree, 2009) and made localization policy a significant staffing consideration for international businesses operating in this particular environment (Mellahi, 2007, Rees et al, 2007). However, there is a lack of academic research on HRM in emerging markets in general, and especially in GCC countries. Although anecdotal records and literature on workforce localization exist in most GCC countries, there is still a lack of academic research on such programs (Randeree, 2012) and the HRM practices that support them. Although several researchers have addressed particular HR practices with respect to localization, there has been no comprehensive study encompassing the key HR processes. This article reviews the literature on workforce localization programs in the GCC and on the HRM practices that facilitate the implementation of these programs
Brain Source Localization in the Presence of Leadfield Perturbations
No full textA Master of Science thesis in Electrical Engineering by Rabiya Nakhat Momin entitled, "Brain Source Localization in the Presence of Leadfield Perturbations," submitted in May 2015. Thesis advisors are Dr. Hasan Mir and Dr. Hasan Al-Nashash. Soft and hard copy available.Brain source localization enables us to localize different areas of the brain that are activated during any mental activity. This thesis makes use of Electroencephalography (EEG) recordings which is an important noninvasive tool for studying the temporal dynamics of the human brain. EEG source localization finds its applications in cognitive neuroscience in order to develop a Brain Computer Interface (BCI), and in psychopharmacology and psychiatry, to localize sources in certain frequency bands. Unfortunately, EEG readings cannot directly indicate the location of the source of brain activity using the signals measured on the scalp, which contributes to the ambiguity of the inverse problem. In order to solve the ill-posed inverse problem, array processing methods are implemented, in conjunction with various techniques that are applied, to improve the localization in the presence of calibration errors. In this thesis, a recently developed G-MUSIC algorithm is applied to the problem of brain source localization. G-MUSIC is a form of weighted MUSIC that performs better in scenarios where only limited sample support is available. Two transfer function based calibration algorithms are also developed to estimate the accurate location of neural activity in the brain when the measured leadfield is perturbed. The localization performance of G-MUSIC is compared to the traditional MUSIC algorithm and quantified in terms of the localization error. This thesis also addresses the problem of localization when exact knowledge of the leadfield matrix, for an individual head anatomy, is not available, by developing an iterative algorithm. This algorithm includes a high resolution localization technique, recently used in radar field, called Source Affine Image Reconstruction Algorithm (SAFFIRE) that can determine the model order (number of sources) and their locations. A beamformer is then designed in order to estimate the dipole source amplitudes. Finally, the EEG signal is reconstructed and related to the actual EEG signal via a calibration matrix. This procedure is repeated until a convergence criteria is met. The performance of this algorithm is quantified in terms of the localization error and accuracy and further validated by applying it to experimental data. In conclusion, the algorithm is also tested on non-stationary EEG signal, where a variant of the conventional adaptive beamformer is applied in order to estimate the source signal amplitudes.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE