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Optimal Planning and Operation of Electric Vehicles Battery Swapping Stations
No full textA Master of Science thesis in Electrical Engineering by Ahmed Ayman Ahmed Shalaby entitled, “Optimal Planning and Operation of Electric Vehicles Battery Swapping Stations”, submitted in May 2020. Thesis advisor is Dr. Mostafa Farouk Shaaban. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Electric Vehicles (EVs) nowadays have become increasingly prevalent due to the advancements in EV technology and their impact on reducing greenhouse emissions. However, there are still some factors affecting the fast deployment of EVs such as the limited driving range and the charging time. Due to the limited driving range, EVs need to be charged frequently, but charging requires a long period at traditional EV charging stations, whereas fast-charging stations still have concerns regarding the wait and the charging time, which might cause traffic jams near the station. In this thesis, new dynamic optimal operation and planning approaches of EV battery-swapping stations (BSS) are introduced. In the operation phase, the goal is to maximize the daily profit using a rolling horizon optimization (RHO) mechanism and determining the optimal operating schedule for swapping and charging/discharging processes. The problem is formulated as mixed-integer linear programming (MILP) problem with nonlinear battery degradation characteristics included. Long-short-term memory (LSTM) recurrent neural network is used as a time series forecasting engine for predicting the EVs' arrivals. The proposed approach is tested and compared with the unscheduled operation and day-ahead scheduling. The results show that the dynamic operations scheduling using the proposed RHO mechanism results in a higher profit. In the second phase, an optimal planning approach for a photovoltaic-based BSS system is proposed considering the PV system and EV arrivals uncertainty. The main goal of the planning part is to determine the optimal size of the BSS assets and to optimally allocate the BSS in the distribution network. Markov Chain Monte Carlo Simulation is used to tackle the uncertainty associated with photovoltaic output and EV arrivals. Simulation results show the effectiveness of the proposed BSS system and an optimal solution is obtained which maximizes the annualized profit.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Gold-Conjugated Curcumin as a Novel Therapeutic Agent against Brain-Eating Amoebae
No full textBalamuthia mandrillaris and Naegleria fowleri are free-living amoebae that cause infection of the central nervous system, granulomatous amoebic encephalitis (GAE) and primary amoebic meningoencephalitis (PAM), respectively. The fact that mortality rates for cases of GAE and PAM are more than 95% indicates the need for new therapeutic agents against those amoebae. Considering that curcumin exhibits a wide range of biological properties and has shown efficacy against Acanthamoeba castellanii, we evaluated the amoebicidal properties of curcumin against N. fowleri and B. mandrillaris. Curcumin showed significant amoebicidal activities with an AC₅₀ of 172 and 74 μM against B. mandrillaris and N. fowleri, respectively. Moreover, these compounds were also conjugated with gold nanoparticles to further increase their amoebicidal activities. After conjugation with gold nanoparticles, amoebicidal activities of the drugs were increased by up to 56 and 37% against B. mandrillaris and N. fowleri, respectively. These findings are remarkable and suggest that clinically available curcumin and our gold-conjugated curcumin nanoparticles hold promise in the improved treatment of fatal infections caused by brain-eating amoebae and should serve as a model in the rationale development of therapeutic interventions against other infections.American University of Sharja
The cultural barriers to a low-carbon future: A review of six mobility and energy transitions across 28 countries
No full textThis review focuses on how culture can complicate and impede attempts at promoting more efficient, more sustainable, and often more affordable forms of mobility as well as energy use in homes and buildings. In simpler terms: it illustrates the cultural barriers to a low-carbon, low-energy future across 28 countries. Rather than focus on energy supply, it deals intently with energy end-use, demand, and consumption. In terms of low-carbon transport and mobility, it examines the cultural barriers to aggressive driving, speeding, and eco-driving; automated vehicles; and ridesharing and carpooling. In terms of cooking and building energy use, it examines the cultural barriers to solar home systems, improved cookstoves, and energy efficient heating, cooling, and hot water practices. For each case, the review synthesizes a wide range of studies showing that culture can operate as a salient but often unacknowledged barrier to low-carbon transitions as well as sustainability transitions more generally. The paper concludes with recommendations aimed at catalyzing the effectiveness and efficiency with which policymakers, researchers and practitioners are able to research, develop, demonstrate and deploy culturally appropriate technologies and policies for a low-carbon transition
Functional Connectivity Analysis under Vigilance Decrement and Enhanced Mental States
No full textA Master of Science thesis in Biomedical Engineering by Omnia Hassanin entitled, “Functional Connectivity Analysis Under Vigilance Decrement and Enhanced Mental States”, submitted in June 2020. Thesis advisors are Dr. Hasan Al Nashash, Dr. Usman Tariq and Dr. Fares Yahya. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).This thesis proposes electroencephalogram (EEG) functional connectivity and graph theory analysis (GTA) to quantify brain activity under alertness, vigilance decrement, and enhanced mental states in four frequency bands. The vigilance decrement state was induced by performing a 30 min computerized incongruent Stroop color-word test (ISCWT). Meanwhile, the enhancement states were provoked by integrating a 250Hz pure sinusoidal tone (PST) or 16Hz beta binaural beats (BB) with the I-SCWT. We estimated functional connectivity using the phase-locking value (PLV) statistic and characterized the topological structure of the network based on concepts of node strength, clustering coefficient, and efficiency. We then evaluated the proposed methods using statistical analysis and a support vector machine classifier. The experimental results showed that the 30 min I-SCWT significantly elicited alteration in cortical connectivity (p < 0.05). PLV between brain regions significantly decreased with vigilance decrement (p<0.05), resulting in a less optimal network structure. Investigation of the intra-regional PLV networks suggested that changes in connectivity under vigilance decrement are specific to cortical areas and EEG frequency bands. Our Assessment results confirm that PLV+GTA provides a reliable index to quantify different aspects of cortical functional connectivity under different vigilance levels. Subject independent classification analysis based on GTA features corresponding to a single cortical region showed an average accuracy of 84.27% to discriminate vigilance decrement from alertness state. Under enhanced mental states, cortical connectivity remained high until the end of the total task duration. Also, significant improvements in the participants’ performance were observed in comparison to the no-audio condition. On average, PST stimulation showed a 25.84% improvement in the participants’ detection accuracy towards the end of the task. Similarly, BB stimulation showed a 26.01% improvement.College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
Characterization of transection spinal cord injuries by monitoring somatosensory evoked potentials and motor behavior
No full textStandardization of spinal cord injury (SCI) models is crucial for reproducible injury in research settings and their objective assessments. Basso, Beattie and Bresnahan (BBB) scoring, the traditional behavioral evaluation method, is subjective and susceptible to human error. On the other hand, neuro-electrophysiological monitoring, such as somatosensory evoked potential (SSEP), is an objective assessment method that can be performed continuously for longitudinal studies. We implemented both SSEP and BBB assessments on transection SCI model. Five experimental groups are designed as follows: left hemi-transection at T8, right hemi-transection at T10, double hemi-transection at left T8 and right T10, complete transection at T8 and control group which receives only laminectomy with intact dura and no injury on spinal cord parenchyma. On days 4, 7, 14 and 21 post-injury, first BBB scores in awake and then SSEP signals in anesthetized rats were obtained. Our results show SSEP signals and BBB scores are both closely associated with transection model and injury progression. However, the two assessment modalities demonstrate different sensitivity in measuring injury progression when it comes to late-stage double hemi-transection, complete transection and hemi-transection injury. Furthermore, SSEP amplitudes are found to be distinct in different injury groups and the progress of their attenuation is increasingly rapid with more severe transection injuries. It is evident from our findings that SSEP and BBB methods provide distinctive and valuable information and could be complementary of each other. We propose incorporating both SSEP monitoring and conventional BBB scoring in SCI research to more effectively standardize injury progression
FPGA-Based Network Traffic Classification Using Machine Learning
No full textReal-time classification of internet traffic is critical for the efficient management of networks. Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. Moreover, the optimal percentage of packets considered within a flow while extracting flow-level features is determined. Several experiments are conducted using naïve Bayes, support vector machine, k-nearest neighbor, random forest, and artificial neural networks on the University of Brescia (UNIBS) and the University of New Brunswick (UNB) datasets, which are both publicly available. The performed experiments show that 60% of flow packets are a good compromise that ensures high performance in the least processing time. The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. Further, and since software-based classifiers cannot meet the anticipated real-time requirements, we propose a Field-Programmable Gate Array (FPGA) based random forest implementation that utilizes a highly pipelined architecture to accelerate such a time-consuming task. The proposed design achieves an average throughput of 163.24 Gbps, exceeding throughputs of reported hardware-based classifiers that use comparable approaches, which in turn ensures the continuity of realtime traffic classification at congested data centers
An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
No full textA Master of Science thesis in Computer Engineering by Ahmed Fahmy entitled, “An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure”, submitted in February 2020. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Taha Landolsi. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
The Impact of Host Country Characteristics on Self-Initiated Expatriates’ Career Success
No full textThis chapter examines the impact of host country characteristics, the particularities of a location, on self-initiated expatriate (SIE)'s career success. For the SIE, therefore, the host country's institutional characteristics, culture, language, and reputation may have considerably more salience than they would for assigned expatriates. However, little is known about the impact of the host country's characteristics on SIEs' cross-border career success. The chapter first presents a brief discussion of SIE career success/satisfaction, to examine the host country's institutional and cultural characteristics that have an impact on SIE's career success. It then proposes a research model and agenda. Since there is almost no research on the impact of host country characteristics on SIEs' career success, the chapter reviews the general literature on expatriate career success and pull out from that the specific factors that will affect SIEs' career success
Freshwater budget in the Persian (Arabian) Gulf and exchanges at the Strait of Hormuz
No full textThis paper has two related data sets: (1) Campos, E. (2020). GULF HYCOM 1/12 Data Set for Paper PONE-D-20-06928R1. DANS. https://doi.org/10.17026/dans-xhy-3ap3 ; (2) Campus, E. (2020). Output from a 1/12-degree Global experiment with the Hybrid Coordinate Ocean Model (HYCOM), forced with with NCEP Reanalysis products - Data for the Persian Gulf and Strait of Hormuz. SEANOE. https://doi.org/10.17882/74042
This work is funded by the American University of Sharjah Faculty Research Grant (FRG) program (Grants FRG19-M-G67 to EJDC and FRG19-M-G74 to GC). The analyses used results of numerical experiments run at the Brazilian National Institute for Space Research (INPE) Tupã supercomputer and at the Laboratory for Ocean Modeling and Observations (LABMON), of the Oceanographic Institute of the University of São Paulo, Brazil, as part of Projects SAMOC-BR and SAMBAR, sponsored by the São Paulo State Foundation for Research Support (grants 2011/50552-4 and 2017/09659-6) to EJDC. EJDC acknowledges the Brazilian Council for Scientific and Technological Development (CNPq) for a Research Fellowship (Grant 302018/2014-0).Excess evaporation within the Persian (also referred as the Arabian) Gulf induces an inverse-estuary circulation. Surface waters are imported, via the Strait of Hormuz, while saltier waters are exported in the deeper layers. Using output of a 1/12-Degree horizontal resolution ocean general circulation model, the spatial structure and time variability of the circulation and the exchanges of volume and salt through the Strait of Hormuz are investigated in detail. The model's circulation pattern in the Gulf is found to be in good agreement with observations and other studies based on numerical models. The mean export of salty waters in the bottom layer is of 0.26±0.05Sv (Sverdrup = 1.0 × 106 m3 s−1 ). The net freshwater import, the equivalent of the salt export divided by a reference salinity, done by the baroclinic circulation across that vertical section is decomposed in an overturning and a horizontal components, with mean values of 7.2±2.1 × 10−3 Sv and 5.0±1.7 × 10−3 Sv respectively. An important, novel finding of this work is that the horizontal component is confined to the deeper layers, mainly in the winter. It is also described for the first time that both components are correlated at the same level with the basin averaged evaporation minus precipitation (E-P) over the Persian Gulf. The highest correlation (r2 = 0.59) of the total freshwater transport across 26˚N with E-P over the Gulf is found with a one-month time lag, with E-P leading. The time series of freshwater import does not show any significant trend in the period from 1980 to 2015. Power spectra analysis shows that most of the energy is concentrated in the seasonal cycle. Some intraseasonal variability, likely related to the Shamal wind phenomenon, and possible impacts of El-Nino are also detected. These results suggest that the overturning and the horizontal components of freshwater exchange across the Strait of Hormuz are both driven by dynamic and thermodynamic processes inside the Persian Gulf
High Order Methods for Solving Cardiac Models
No full textA Master of Science thesis in Mathematics by Maryam Alqasemi entitled, “High Order Methods for Solving Cardiac Models”, submitted in May 2020. Thesis advisor is Dr. Youssef Belhamadia. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Modeling of the heart became of great interest for both mathematicians and bioengineers over the past 25 years for the increasing impact of cardiovascular system problems in our every day lives. The bidomain model and its simplified version, the monodomain model, are the most used mathematical models for simulation of the electrical activity of the heart. These models consist of a system of non-linear partial differential equations coupled with a set of ordinary differential equations describing the electrochemical reaction in the cardiac cell. These models are computationally demanding and developing accurate numerical methods are needed. This thesis proposes methods to solve such systems with a higher order of accuracy, (order 3 and 4), for both space and time. For space discretization, the proposed method is based on an Alternating Direction Implicit (ADI) finite difference method, while for the time discretization, the Semi-Implicit Backward Difference Method (SBDF) is used to simplify the non-linearity in the cardiac model. The performance of our techniques is presented and tested using three cases: the planar wave, the regular wave, and the spiral wave.College of Arts and SciencesDepartment of Mathematics and StatisticsMaster of Science in Mathematics (MSMTH