Schulich School of Engineering Research & Publications

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    Open Access
    Use of GNSS Doppler for Prediction in Kalman Filtering for Smartphone Positioning
    (IEEE Journal of Indoor and Seamless Positioning and Navigation, 2023-11-28) Agarwal, Naman; O'Keefe, Kyle
    This article demonstrates an alternative approach that uses global navigation satellite system (GNSS) Doppler measurements in a Kalman filter (KF) to improve the accuracy of GNSS smartphone positioning. The proposed method automates the process of estimating the uncertainty of the dynamics model of the system, which is still a challenge for the conventional KF-based GNSS positioning methods that require heuristic tuning. Automation of dynamics model uncertainty estimation also demonstrates notable improvement in GNSS outlier detection or fault detection and exclusion. In addition, this article will perform a quality assessment of the GNSS observations obtained from two Android smartphones and investigate the performance of the proposed method when using GPS L1 + Galileo E1 signals compared to GPS L5 + Galileo E5a signals.
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    Open Access
    Metal-Organic Framework Reinforced Highly Stretchable and Durable Conductive Hydrogel-Based Triboelectric Nanogenerator for Biomotion Sensing and Wearable Human-Machine Interfaces
    (Wiley, 2023-07-17) Rahman, Muhammad Toyabur; Rahman, Md Sazzadur; Kumar, Hitendra; Kim, Keekyoung; Kim, Seonghwan
    Flexible triboelectric nanogenerators (TENGs) with multifunctional sensing capabilities offer an elegant solution to address the growing energy supply challenges for wearable smart electronics. Herein, a highly stretchable and durable electrode for wearable TENG is developed using ZIF-8 as a reinforcing nanofiller in a hydrogel with LiCl electrolyte. ZIF-8 nanocrystals improve the hydrogel's mechanical properties by forming hydrogen bonds with copolymer chains, resulting in 2.7 times greater stretchability than pure hydrogel. The hydrogel electrode is encapsulated by microstructured silicone layers that act as triboelectric materials and prevent water loss from the hydrogel. Optimized ZIF-8-based hydrogel electrodes enhance the output performance of TENG through the dynamic balance of electric double layers (EDLs) during contact electrification. Thus, the as-fabricated TENG delivers an excellent power density of 3.47 Wm–2, which is 3.2 times higher than pure hydrogel-based TENG. The developed TENG can scavenge biomechanical energy even at subzero temperatures to power small electronics and serve as excellent self-powered pressure sensors for human-machine interfaces (HMIs). The nanocomposite hydrogel-based TENG can also function as a wearable biomotion sensor, detecting body movements with high sensitivity. This study demonstrates the significant potential of utilizing ZIF-8 reinforced hydrogel as an electrode for wearable TENGs in energy harvesting and sensor technology.
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    Open Access
    In situ encapsulation of ZrQ in UiO-66 (Zr-BDC) for pore size control to enhance detection of a nerve agent simulant dimethyl methyl phosphonate (DMMP)
    (Wiley, 2022-06-08) Wong, Danny; Kim, Seonghwan; Abuzalat, Osama
    Chemical warfare agents are toxic chemicals that require rapid, easy-to-use, sensitive, and selective sensors to countermeasure. Simulants, such as dimethyl methyl phosphonate (DMMP), are used to test the effectiveness of sensors toward nerve agents. Metal organic frameworks (MOFs) offer large surface area and selective accessibility to active sites making them appealing for chemical sensing applications. In this work, we propose a fast, facile, direct synthesis method for manufacturing fluorescent MOFs with high sensitivity and selectivity. Zr-BDC is synthesized with 1, 4-benzenedicarboxylic acid (BDC) as an organic ligand and zirconium (Zr) metal. Fluorescent materials are then encapsulated in a novel and rapid in situ approach with strong solvents. X-ray diffraction, UV–visible spectroscopy, Fourier-transform infrared spectroscopy, and Raman spectroscopy are used to verify the successful formation of fluorescent MOFs. Compared to other methods, the gel synthesis method helps to control crystal growth leading to higher BET surface areas of ~1150 m2 g−1 for Zr-BDC and 850 m2 g−1 for ZrQ@Zr-BDC. Titration experiments show the sensitivity of the material to DMMP down to 8.3 nM with a highly linear response. Enhanced fluorescence and occupation of mesopores by ZrQ enable lower limit of detection than those of comparable works in literature. The encapsulation mechanism also prevents substantial defects that would otherwise lead to water adsorption.
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    Embargo
    Object positional uncertainty modelling in 2D viewpoint planning
    (Elsevier--Automation in Construction, 2023)
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    Open Access
    Advancing Smart Cities through Novel Social Media Text Analysis: A Case Study of Calgary
    (2023 IEEE Symposium Series on Computational Intelligence, 2023-09-15) Mitra Mirshafiee; Dr. Ann Barcomb; Dr. Benjamin Tan
    In numerous cities, population expansion and technological advancements necessitate proactive modernization and integration of technology. However, the existing bureaucratic structure often hinders local officials' efforts to effectively address and monitor residents' needs and enhance the city accordingly. Understanding what people find important and useful can be inferred from their posts on social media. Twitter, as one of the most popular social media platforms, provides us with valuable data that, with the right tools and analysis, can provide insights into the performance of urban services and residents' perception of them. In this study, we used the city of Calgary as an exemplar to gather tweets and analyze topics relating to city development, urban planning, and minorities. Natural language processing (NLP) techniques were used and developed to preprocess stored tweets, classify the emotions, and identify the topics present in the dataset to eventually provide a set of topics with the prevalent emotion in that topic. We utilized a variety of methods to analyze the collected data. BERTopic for topic modeling and few-shot learning using Setfit for emotion analysis outperformed the others. Hence, we identify issues related to city development, senior citizens, taxes, and unemployment using these methods, and we demonstrate how delving into these analyses can improve urban planning.