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Data for Interaction Diagrams of Geopolymer FRC Slender Columns with Double-Layer GFRP and Steel Reinforcement
No full textThis article provides data of axial load-bending moment capacities of plain and fiber-reinforced geopolymer concrete (GPC, FRGPC) columns. The columns were reinforced by double layers of longitudinal and transverse reinforcement using steel and/or glass-fiber-reinforced polymer (GFRP) bars. The concrete fiber-reinforcing materials included steel and synthetic fibers. The columns data included different parameters like the longitudinal reinforcement ratio, the applied load eccentricity, and the columns’ slenderness ratio. The data was collected from different analysis output files then sorted and tabulated in usable formatted tables. The data can support the development of design axial load-bending moment interactions. In addition, further processing of the data can yield analytical strength curves which are useful in determining the columns stability under different structural loading configurations. Researchers and educators can make use of these data for illustrations and prospective new research suggestions.American University of Sharja
A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation
No full textA multistage approach to passive islanding detection is proposed that utilizes a decision tree (DT) like classification algorithm. The novelty of the proposed method is centered on the way in which features are passed to subsequent stages of the DT. Feature sets extracted using different sized time windows are passed to successive stages of the tree. This provides two important advantages: 1) cases that can be easily determined as either islanding or nonislanding events are flagged as soon as possible without waiting for the full feature set to become available; 2) because the algorithm allows for the use of different sized time windows, features are analyzed in time-scales that fit their natural patterns of temporal evolution. In this article, the proposed classifier is trained and tested using a database of feature vectors, obtained using PSCAD, which were designed to reflect a variety of commonly encountered events on an IEEE 34-bus distribution system. One of the key requirements for the proposed algorithm was that easy cases should be flagged as soon as possible; this property was confirmed by the observation that most events ( ≈ 79%) were detected within 10–20 ms, while at the same time retaining a very high detection rate overall cases ( >99 %).American University of Sharja
Using C++ to Calculate SO(10) Tensor Couplings
No full textModel building in SO(10), which is the leading grand unification framework, often involves large Higgs representations and their couplings. Explicit calculations of such couplings is a multi-step process that involves laborious calculations that are time consuming and error prone, an issue which only grows as the complexity of the coupling increases. Therefore, there exists an opportunity to leverage the abilities of computer software in order to algorithmically perform these calculations on demand. This paper outlines the details of such software, implemented in C++ using in-built libraries. The software is capable of accepting invariant couplings involving an arbitrary number of SO(10) Higgs tensors, each having up to five indices. The output is then produced in LATEX, so that it is universally readable and sufficiently expressive. Through the use of this software, SO(10) coupling analysis can be performed in a way that minimizes calculation time, eliminates errors, and allows for experimentation with couplings that have not been computed before in the literature. Furthermore, this software can be expanded in the future to account for similar Higgs–Spinor coupling analysis, or extended to include further SO(N) invariant couplings
Fog Computing Approach for Shared Mobility in Smart Cities
No full textSmart transportation a smart city application where traditional individual models are transforming to shared and distributed ownership. These models are used to serve commuters for inter- and intra-city travel. However, short-range urban transportation services within campuses, residential compounds, and public parks are not explored to their full capacity compared to the distributed vehicle model. This paper aims to explore and design an adequate framework for battery-operated shared mobility within a large community for short-range travel. This work identifies the characteristics of the shared mobility for battery-operated vehicles and accordingly proposes an adequate solution that deals with real-time data collection, tracking, and automated decisions. Furthermore, given the requirement for real-time decisions with low latency for critical requests, the paper deploys the proposed framework within the 3-tier computing model, namely edge, fog, and cloud tiers. The solution design considers the power consumption requirement at the edge by offloading the computational requests to the fog tier and utilizing the LoRaWAN communication technology. A prototype implementation is presented to validate the proposed framework for a university campus using e-bikes. The results show the scalability of the proposed design and the achievement of low latency for requests that require real-time decisions.American University of Sharja
A novel stochastic dynamic modeling for photovoltaic systems considering dust and cleaning
No full textStochastic photovoltaic (PV) modeling that can be used for long-term planning of power systems is essential for future renewable power generation. One of the most prevalent problems that PV systems face is the accumulation of dust on the PV panel surface that negatively impacts the output power. Wind speed along with other weather variables including relative humidity, temperature, and precipitation are some of the major factors that contribute to dust accumulation. This paper presents a novel dynamic model of the PV output power profile including the dust accumulation using a Markov chain model. The proposed model incorporates the seasonal variations in ambient temperature, solar irradiance, dust accumulation, and rate of dust accumulation as well as the desired cleaning frequency, which affect the overall energy yield of the PV system. The outcome of the model is virtually generated scenarios that can be used by the investors to decide on the optimal size of the PV system and the optimal cleaning frequency or each season. The model outcome shows an error of less than 5% when compared to actual data collected from the field without cleaning. This error can be reduced by increasing the number of states, which affects the computational time. Various case studies are presented to show the effectiveness of the proposed model and its benefits.American University of Sharja
Perceptions of Emotional Functionality: Similarities and Differences Among Dignity, Face, and Honor Cultures
No full textEmotions are linked to wide sets of action tendencies, and it can be difficult to predict which specific action tendency will be motivated or indulged in response to individual experiences of emotion. Building on a functional perspective of emotion, we investigate whether anger and shame connect to different behavioral intentions in dignity, face, and honor cultures. Using simple animations that showed perpetrators taking resources from victims, we conducted two studies across eleven countries investigating the extent to which participants expected victims to feel anger and shame, how they thought victims should respond to such violations, and how expectations of emotions were affected by enacted behavior. Across cultures, anger was associated with desires to reclaim resources or alert others to the violation. In face and honor cultures, but not dignity cultures, shame was associated with the desire for aggressive retaliation. However, we found that when victims indulged motivationally-relevant behavior, expected anger and shame were reduced and satisfaction increased in similar ways across cultures. Results suggest similarities and differences in expectations of how emotions functionally elicit behavioral responses across cultures.American University of Sharja
Ultrasound-Triggered Liposomes Encapsulating Quantum Dots as Safe Fluorescent Markers for Colorectal Cancer
No full textQuantum dots (QDs) are a promising tool to detect and monitor tumors. However, their small size allows them to accumulate in large quantities inside the healthy cells (in addition to the tumor cells), which increases their toxicity. In this study, we synthesized stealth liposomes encapsulating hydrophilic graphene quantum dots and triggered their release with ultrasound with the goal of developing a safer and well-controlled modality to deliver fluorescent markers to tumors. Our results confirmed the successful encapsulation of the QDs inside the core of the liposomes and showed no effect on the size or stability of the prepared liposomes. Our results also showed that low-frequency ultrasound is an effective method to release QDs encapsulated inside the liposomes in a spatially and temporally controlled manner to ensure the effective delivery of QDs to tumors while reducing their systemic toxicity.American University of SharjahSheikh Hamdan Award for Medical SciencesUniversity of Sharja
Evaluating velocity and temperature fields for Ranque Hilsch vortex tube using numerical simulation
No full textIn this study, a three-dimensional numerical investigation is carried out to study the flow field inside a Ranque-Hilsch vortex tube (RHVT) model. Flow parameters such as velocity, temperature, and pressure are plotted at various locations inside the tube. The study reports the effect of cold mass fraction on the energy separation of vortex tube . The results show that the flow inside RHVT consists of a free vortex from r/R=0 to 0.9 and a force vortex from r/R=0.9 to 1 and that heat transfer occurs from the inner core to the periphery of the tube. Furthermore, it is observed that the minimum cold temperature and the maximum hot temperature are achieved at different mass fractions, 0.19 and 0.8, respectively
Collaborative Caching for D2D Content Sharing in 5G
No full textA Master of Science thesis in Computer Engineering by Ansam Elfadil Kamel Abdelsalam entitled, “Collaborative Caching for D2D Content Sharing in 5G”, submitted in May 2021. Thesis advisor is Dr. Rana E. Ahmed. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Due to a huge number of mobile devices expected to be connected to 5G wireless networks and their expected demand for high data-rate multimedia services, the core network and backhaul links are expected to carry enormous amount of traffic. Caching the most popular files at the network edge and in user’s devices to support user proximity services in 5G will help to offload traffic in the core network and to increase the cache hit probability. Device-to-Device (D2D) communication in 5G can be utilized to share the cached files between any pair of devices with a minimal involvement from the base station. However, there are many challenges that are needed to be addressed including interference management, mode selection, device discovery, contents placement, popularity index calculation, and the non-cooperative situations in D2D. This thesis attempts to solve most of the above-mentioned problems via collaborative content caching and sharing using D2D communication in 5G networks. The primary objective of the research is to maximize the overall system offloading gain and the cache hit probability in downloading the popular file contents. The proposed system model exploits the social-networking concept, assuming the cell structure in a condensed populated area, such as a university campus or an auditorium. We combine the process of content caching and D2D communication in the WiFi range. In particular, joint resource allocation, mode selection, cache placement and replacement for multiple D2D devices are addressed. Data traffic offloading in three modes of operation, self-offloading, D2D offloading, and Base Station-to-Device (B2D) offloading and mode selection algorithm are implemented. Furthermore, we vary the network parameters and the cache model parameters to assess their impacts on the system performance. The performance of the proposed cache scheme is evaluated through extensive simulations and compared with the popular cache scheme and the baseline performance of the random cache scheme, and it is found that the proposed scheme outperforms the two schemes by 9.4% and 20%, respectively, with respect to cache hit probability. The effects of users’ mobility and disconnection on system performance are also investigated.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Decarbonizing the food and beverages industry: A critical and systematic review of developments, sociotechnical systems and policy options
No full textFrom farm to fork, food and beverage consumption can have significant negative impacts on energy consumption, water consumption, climate change, and other environmental subsystems. This paper presents a comprehensive, critical and systematic review of more than 350,000 sources of evidence, and a short list of 701 studies, on the topic of greenhouse gas emissions from the food and beverage industry. Utilizing a sociotechnical lens that examines food supply and agriculture, manufacturing, retail and distribution, and consumption and use, the review identifies the most carbon-intensive processes in the industry, as well as the corresponding energy and carbon “footprints”. It discusses multiple current and emerging options and practices for decarbonization, including 78 potentially transformative technologies. It examines the benefits to sector decarbonization—including energy and carbon savings, cost savings, and other co-benefits related to sustainability or health—as well as barriers across financial and economic, institutional and managerial, and behavioral and consumer dimensions. It lastly discusses how financing, business models, and policy can be harnessed to help overcome these barriers, and identifies a set of research gaps