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Evaluating the Effectiveness of Smart City & IoT Solutions in Improving Urban Sustainability, Mobility, and Quality of Life in the UAE
No full textThe United Arab Emirates has an aim to develop smart cities incorporating advanced technologies such as the Internet of Things (IoT), to enhance urban sustainability, mobility, and improve citizens quality of life. However, based on the significant funds invested by the government, there exists an important gap within the government systems in measuring the effectiveness of such activities given the lack of data quantifying the benefits gained from such smart initiatives. To address this gap, this study delivers the benefits gained from smart initiatives by using a mixed-methods approach combining both quantitative and qualitative data. The research is based on a time-limited before and after an analysis where the time periods (2018 2021) constitutes the before phase and (2022 2024) is the after phase which is the period of large-scale IoT implementation at the start of 2022. The results show that the key performance indicators have increased significantly after the introduction of these solutions. The indoor PM2.5 concentration decreased by 43%. Journey time decreased by 48% and citizen satisfaction increased by 57%. Even though the disclosure of data sources was limited by the need to maintain confidentiality, the general tendencies are quite convincing of the positive effect caused by the process of IoT-based smart cities. All in all, this study can emphasize the advantages of smart cities and IoT applications in the UAE as well as the obstacles to their implementation. The research provides useful information to aid policymakers and city planners, as well as advance the scientific knowledge on technology-based urban development
Parameter Estimation of Eccentric Binary Black Holes using Targeted Numerical Relativity Simulations
No full textGravitational wave events detected by the LIGO-Virgo-KAGRA (LVK) collaboration are the result of compact binary mergers which produce gravitational wave (GW) emission. The observed waveform carries information about the source properties, such as masses, spins, and orbital eccentricity. Events harboring eccentricity upon entrance of the LVK sensitivity band at 10 Hz are believed to have been formed through dynamical channels, where the binary has interacted with other astrophysical objects leading to a merger faster than an isolated binary. Therefore, the identification of eccentric gravitational wave events and accurate determination of their parameters is vital to understanding the population of binary black holes that form and merge dynamically. In consideration of this, we have analyzed LVK gravitational wave events that have shown evidence of eccentricity, from both the literature and our own analysis using the effective-one-body model TEOBResumS, and confronted them independently with an analysis using full numerically generated waveforms from our bank of nearly two thousand simulations of binary black holes. We have used RIFT for Bayesian parameter estimation for both the model-based and numerical relativity (NR) analyses, where results from the model-based analysis are used to generate new targeted NR simulations in the highest likelihood region of parameter space as determined by the model-based analysis. Using the full bank of simulations (including the targeted simulations) we found through a kernel density estimate of the RIFT produced posteriors that GW200208_22 favors eccentricities e20 = 0.198(+0.119/−0.180) upon entering the LVK sensitivity band at 20 Hz within a 90% credible interval. Due to our method of generating targeted simulations at the intrinsic parameters of peak likelihood models, we have found that numerical relativity waveforms return a general improvement of likelihood for waveforms of the same intrinsic parameters. For GW200208_22 we find a new peak likelihood waveform, compared to model-based analysis, with an estimated eccentricity at 20 Hz, e20 = 0.200, thus reinforcing the eccentric hypothesis of the binary. We have also used our full bank of numerical waveforms on GW190620 finding that the KDE estimate favors eccentricities at 10 Hz in e10 = 0.190(+0.046/−0.186). However, new specifically targeted simulations will be required to narrow this eccentricity range
The Heart Seat™: An In Home Cardiovascular Monitoring Device
No full textHeart failure (HF) is one of the most common disorders, affecting an estimated 64 million people globally. Although heart failure incidence is stabilizing in some countries, prevalence is rising because of an aging population, improved post-myocardial infarction survival, and advances in treatment. High mortality, morbidity, reduced quality of life, and significant healthcare costs are results of heart failure (Shahim et al., 2023). Recurrent heart failure episodes are associated with an increased risk of death. Heart monitoring systems exist in several forms, including implantable cardiac devices, wearable and portable monitors, and remote patient monitoring systems. Each type differs in monitoring needs, from once-a-day tracking to critical real time data transmission but each type of device has its own strengths and drawbacks. One such drawback of patient compliance is using a monitoring device, but that can be mitigated with a device that requires minimal patient involvement and infrequent charging (Conn et al., 2018). Dr. David Borkholder and Dr. Nicholas Conn collaboratively created an in-home toilet seat based cardiovascular monitoring system, known as The Heart Seat™, which seeks to alleviate the downfalls of commonly used in home monitoring systems for heart failure, while simultaneously creating trend data of accurate measurements of blood pressure, stroke volume, and blood oxygenation levels in a clinical level accuracy at home. The purpose of this project is to create a short animation, along with a poster to introduce The Heart Seat™ to patients with heart failure, and show them that it can track recently discharged patient’s vitals and leave time for early intervention. The animation consists of two parts: (1) To describe the need for such a device and (2) to illustrate The Heart Seat™’s uses and functions. A poster is presented highlighting key features of the device
Enhanced Pulsar Timing Precision for the Era of Nanohertz Gravitational Wave Astronomy
No full textIn 2023, several international collaborations comprising the International Pulsar Timing Array achieved a major scientific milestone with the first detection of a signal in pulsar timing observations consistent with the signature expected from a stochastic gravitational wave background, created by an ensemble of unresolved supermassive black hole binaries in the early Universe. The next breakthrough in the field is expected to be the first detection of a continuous wave from a single such binary, which would allow us to better understand their evolution and that of our Universe. However, this feat will require unprecedented precision in our timing measurements. To that end, in this thesis we conduct a detailed exploration of different noise budgeting techniques to improve the timing precision achieved by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). We present three distinct approaches: 1) Quantifying previously unaccounted-for error sources in pulsar observations. In particular, we study the biases introduced in the modeling of frequency-dependent effects due to incomplete frequency sampling. 2) Developing novel machine-learning-based algorithms to characterize single-pulse jitter and mitigate the timing uncertainty introduced by single-pulse variability, which causes deviations of the integrated pulse profile from the long-term average. 3) Incorporating high-precision pulsar astrometric estimates obtained using Very Long Baseline Interferometry (VLBI) measurements into NANOGrav’s timing models to eliminate the need to fit for those parameters in the timing solution, thereby mitigating potential power absorption from gravitational wave signals. We find that, for selected sources and after appropriate data processing, these techniques can enhance the quality of NANOGrav’s current datasets. In particular, we obtain consistent improvements as large as approximately 0.3 microseconds in timing precision when clustering single pulses of PSR J2145−0750 by fluence. We quantify that the error in time-of-arrival measurements from narrowband observations of PSR J1643−1224 may be underestimated by as much as approximately 22 microseconds. We also find a VLBI-consistent astrometric solution for PSR J0030+0451 that could prevent red-noise processes with residual amplitudes as large as approximately 0.8 microseconds from being absorbed into the pulsar astrometric fit. Applications of these techniques include refining current data processing pipelines and providing more robust error estimates for legacy observations, thereby increasing the effective time baseline using already available data
A Novel Nephron: 3D Visualization of Glomerular Filtration in the Kidney
No full textRenal physiology, particularly the process of glomerular filtration, remains one of the most conceptually challenging topics in medical education due to its microscopic scale, dynamic pressure relationships, and structural complexity. Understanding how plasma passes through the glomerular filtration barrier requires spatial reasoning across multiple levels—from the gross anatomy of the kidney to the ultrastructure of capillaries, podocytes, and the glomerular basement membrane. This thesis addresses these challenges through the development of a scientifically accurate three-dimensional (3D) animation that illustrates glomerular filtration within its anatomical and physiological context. Designed as a visual teaching aid, the animation aims to improve comprehension of renal microanatomy, demonstrate the functional relationship between structure and process, and depict both normal and pathological filtration dynamics. Development began with an extensive review of primary anatomical and physiological sources, including Brenner and Rector’s The Kidney (9th ed.) and Gray’s Anatomy: The Anatomical Basis of Clinical Practice (41st ed.), supplemented by recent research on glomerular barrier function. Conceptual sketches synthesized spatial relationships and established consistent color conventions before 3D modeling. Anatomical assets—including the glomerular capillary tuft, podocytes, Bowman’s capsule, and renal tubules—were primarily sculpted in ZBrush, while Autodesk Maya was used for animation and rendering. Procedural systems such as MASH, nParticles, and lattice deformers simulated blood flow, filtrate movement, and barrier disruption. Final compositing and narration were completed in Adobe After Effects, integrating narration, labeling, and sound design to create a cohesive visual narrative. The completed animation presents glomerular filtration from both normal and pathological perspectives, visualizing the delicate balance of forces and structures that sustain renal function. By combining anatomical accuracy, educational design, and aesthetic clarity, the project transforms an abstract physiological process into a clear and tangible experience. This work demonstrates how biomedical visualization can enhance engagement and comprehension in renal physiology education while underscoring the broader potential of 3D animation as a tool for teaching complex biological systems
Spike-Based Architectures for Energy-Efficient Audio Enhancement
No full textDeep Neural Networks (DNNs) have shown remarkable success in speech denoising; however, their high computational and energy requirements make realtime deployment on edge devices challenging. In contrast, Spiking Neural Networks (SNNs) operate using sparse, event-driven spikes—offering a biologically inspired and energy-efficient alternative. In this study, we delve into a Spiking Neural Network (SNN) model that leverages the temporal dynamics of spiking neurons to capture long-range dependencies in the audio signal. By encoding the input audio into sparse and event-driven computations, the SNN can efficiently process the temporal information while requiring significantly fewer computations compared to DNNs. We present a real-time speech denoising system that maps noisy audio to sparse spike trains and processes them using diverse SNN architectures that aim to exploit time- and frequency-domain features. We investigated various baseline models and propose the Dual-Signal Transformation Spiking Network, a hybrid model that conducts frequency-domain enhancement through spectrogram masking and supplements it with raw waveform-based reconstruction in the time domain. Our experiments show that SNNs -- especially the Dual-Signal model -- are able to achieve competitive denoising performance while substantially lowering the computational cost—opening up possibilities for efficient and real-time auditory processing on neuromorphic hardware. This potentially contribute to the development of real time audio denoiser using SNN
The Role of Self-Awareness, Advocacy, and Support in STEM Success: Stories from Landmark College\u27s AIE-STEMPLOS Program
No full textNeurodivergent individuals bring unique perspectives and talents to STEM fields while facing distinct challenges, particularly in higher education environments that often rely on traditional learning models. Landmark College’s AIE-STEMPLOS program provides an innovative framework to empower neurodivergent STEM scholars by fostering self-awareness, advocacy, and community support. Grounded in Universal Design for Learning (UDL) principles and strengths-based approaches, the program leverages tools like the Birkman Method® to help students articulate their strengths and communication styles in professional terms. This paper examines how accessible learning strategies, peer mentorship, and individualized advising cultivate belonging, confidence, and resilience among neurodivergent STEM scholars, offering a model for inclusive and sustainable success in STEM education
What Do Future Nutrition Professionals Think About WIC Jobs? A Study of Nutrition Career Perceptions
No full textBackground: The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) program faces a critical workforce shortage, yet little is known about the knowledge, attitudes, and beliefs of nutrition students and recent graduates regarding WIC career pathways, requirements, and compensation. Understanding these factors is essential to design strategies to strengthen recruitment and build a sustainable WIC workforce. Objective: To identify and describe knowledge, attitudes and beliefs on entering the WIC workforce among college nutrition and dietetics students and recent graduates. Design: A mixed-methods, sequential study design which included a cross-sectional survey and two focus groups was employed to ascertain perceptions of WIC careers among college nutrition and dietetic students and recent graduates. Participants: Participants were age 18 years or older, able to speak, read and write in English, enrolled or recently graduated within the last 12 months from a dietetics-related undergraduate or graduate program, completed a course involving community or lifecycle nutrition, and did not have previous WIC employment. A total of 364 accessed the survey and n=208 were included in the analysis. Focus group participants were recruited from the survey sample. Analysis: Quantitative results were reported using descriptive statistics, including frequencies, range, mean and standard deviation. Chi-square tests were conducted to evaluate the relationship between unpaid professional experience and interest level towards becoming a WIC Qualified Nutritionist as well as the highest degree participants intended to pursue and their feelings on how much of their degree they would use in a WIC career. Focus group transcripts were digitally transcribed verbatim. Codes were developed using an inductive thematic approach. Results: A total of 208 individuals completed the survey: 181 were current undergraduate or graduate students and 27 were recent graduates. Sixteen of these respondents participated in focus groups, including 14 students and 2 recent graduates. Participants largely understood WIC program and job offerings but lacked certainty regarding WIC job requirements. Participants overwhelmingly believed that WIC was an important program and believed that they would be internally fulfilled working at WIC, but external factors such as low compensation, job stability, additional education requirements and perceived limitations in scope of practice and growth are barriers to entering into a WIC career. Conclusions: While nutrition students and graduates view WIC careers as meaningful, barriers such as limited career awareness, unclear pathways for growth, perceived low compensation, and perceptions of limiting roles may hinder recruitment. These results demonstrate the need for clearer communication, salary transparency, experiential learning opportunities, and visibility of bachelor’s-level opportunities. Future research is needed to analyze themes within individual participants’ responses and examine the impact of policy changes, such as the new master’s degree requirement for RDNs, on workforce diversity and accessibility
Multimedia-Based Interventions to Improve Science Learning Outcomes for Deaf students at Wangsel Institute for the Deaf.
No full textEfforts have been made to ensure inclusive learning opportunities for all students, including those from diverse backgrounds. One key strategy to enhance children’s learning and academic performance involves the thoughtful selection and application of instructional tools tailored to meet learners\u27 specific needs. This study examines the impact of multimedia-based instruction on science achievement among deaf students at Wangsel Institute for the Deaf in Bhutan. Using a quasi-experimental design, the research compared pretest and post-test results between a control group and an experimental group. Data analysis included descriptive statistics (t-test) and ANCOVA. The findings indicated a statistically significant differences (p = .025) in the experimental group’s post-test scores (M = 9.60, SE = 0.39) compared to the control group (M = 8.16, SE = 0.42). The study concludes that multimedia-based teaching is an effective approach for science education among deaf students, and its integration into science lessons can positively influence overall academic performance
Leveraging AI, IoT, and Predictive Analytics for Crisis Management and Urban Resilience in Dubai
No full textThe thesis will discuss how smart technologies could be incorporated in the crisis management structures of Dubai to make the city more resilient. As Dubai grows more urbanized, it experiences increased problems with managing its crisis especially in the high population density places, traffic congestion, utility disruption, and extreme weather. This paper discusses how artificial intelligence (AI), the Internet of Things (IoT), and predictive analytics can be used to ameliorate the response to emergencies, manage the allocation of resources, and enhance the coordination between different agencies. The crisis management systems at Dubai are still ineffective despite the level of technologies employed because of traffic congestions and the lack of coordination. The proposed research will address the following question: How can smart technologies enhance crisis management in Dubai and enhance urban resilience? It was performed as a mixed-method strategy, which included secondary data in Dubai Pulse and primary data in surveys with major stakeholders in the Dubai Police, Fire Department, and Health Authority. It also analyzed comparative case studies of Singapore, Amsterdam and Barcelona in order to determine the best practices. The evidence indicates that victims have philosophical delays in the way they respond to the crisis, especially in the high-density locations such as Dubai Marina due to traffic jam and the absence of sufficient coordination. AI, IoT, and predictive analytics integration would potentially address the problem of delays and resource optimization as well as increase the level of agency collaboration. But obstacles like the cost involved, privacy issues and training are still present. To incorporate smart technologies into the Dubai infrastructure and enhance the city resiliency, this paper is suggesting the Smart Urban Resilience Framework (SURF)