1,934 research outputs found

    Proceedings of the 10th International congress on architectural technology (ICAT 2024): architectural technology transformation.

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    The profession of architectural technology is influential in the transformation of the built environment regionally, nationally, and internationally. The congress provides a platform for industry, educators, researchers, and the next generation of built environment students and professionals to showcase where their influence is transforming the built environment through novel ideas, businesses, leadership, innovation, digital transformation, research and development, and sustainable forward-thinking technological and construction assembly design

    Canada\u27s Evergreen Playground: A History of Snow in Vancouver

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    The City of Vancouver is not as snowy as the rest of Canada; rain, not snow, is its defining weather feature. But snow is a common seasonal occurrence, having fallen there nearly every winter since the 1850s. This dissertation places snow at the centre of the City of Vancouverā€™s history. It demonstrates how cultural and natural factors influenced human experiences and relationships with snow on the coast between the 1850s and 2000s. Following Vancouverā€™s incorporation, commercial and civic boosters constructed ā€“ and settlers adopted ā€“ what I call an evergreen mentality. Snow was reconceptualized as a rare and infrequent phenomenon. The evergreen mentality was not completely false, but it was not entirely true, either. This mindset has framed human relationships with snow in Vancouver ever since. While this idea was consistent, how coastal residents experienced snow evolved in response to societal developments (such as the rise of the automobile and the adoption of new snow-clearing technologies) and regional climate change. I show that the history of snow in Vancouver cannot be fully understood without incorporating the southern Coast Mountains. Snow was a connecting force between the coastal metropolis and mountainous hinterland. Settlers drew snowmelt to the urban environment for its energy potential and life-sustaining properties; snow drew settlers to the mountains for recreation and economic opportunities. Mountain snow became a valuable resource for coastal residents throughout the twentieth century. Human relationships with snow in the mountains were shaped, as they were in the city, by seasonal expectations, societal circumstances, and shifting climate conditions. In charting a history of snow in Vancouver and the southern Coast Mountains, this dissertation clears a new path in Canadian environmental historiography by bringing snow to the historiographical forefront. It does so in an urban space not known for snow, broadening the existing geography of snow historiography. In uncovering snowā€™s impact on year-round activities, this work also expands the fieldā€™s temporal boundaries. Through this work, one sees how snow helped to make Canadaā€™s Evergreen Playground

    Bringing Back the Love. The Emotional Connection of Growth and Change through Multi-Community Local Area Planning in Calgary, AB.

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    This study examines the complexities of community planning and the significant role of human emotion in the process. Using a practice-based approach, the study explored an innovative codesign strategy as implemented in the Local Area Planning Program (LAP) of The City of Calgary to address these challenges. The LAPs embody a community-led approach to policy and growth planning in established areas, prioritizing emotional co-authorship and the integration of community-specific knowledge in planning. Using a series of semi-structured interviews, six distinguished practitioners provided their diverse perspectives and approaches, with the goal of generating new considerations, tools, and recommendations to integrate into my practice. Applying the LAPs as working models of community connection, this study employed a design science methodology to collect information, reflect, and obtain expert feedback on both practice and design. The aim was to curate a contemporary collection of practice-based tools, strategies, and insights that contribute to The Handbook for Community Connection, a practitioner's guide for fostering emotional connections between communities and the redevelopment process. The Handbook offers a range of practical tools that can fit into a variety of contexts, scales, and available resources, enabling a redefinition of planning processes. The study concludes that by prioritizing empathy and building relationships, redefining planning processes becomes more habitual in practice. Furthermore, continually reflecting on your practice is key to facilitating meaningful connections within community. Relying solely on policy to address societal issues yields limited results; the profession needs a more nuanced and holistic approach. Ultimately, with the study in mind, community planning can be an act of of caring, one that helps to build stronger, more connected, and loving communities

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This ļ¬fth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ļ¬elds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiļ¬ed Proportional Conļ¬‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiļ¬ers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiļ¬cation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiļ¬cation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiļ¬cation, and hybrid techniques mixing deep learning with belief functions as well

    Improving patient safety by learning from near misses ā€“ insights from safety-critical industries

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    Background Patients are at risk of being harmed by the very processes meant to help them. To improve patient safety, healthcare organisations attempt to identify the factors that contribute to incidents and take action to optimise conditions to minimise repeats. However, improvements in patient safety have not matched those observed in other safety-critical industries. One difference between healthcare and other safety-critical industries may be how they learn from near misses when seeking to make safety improvements. Near misses are incidents that almost happened, but for an interruption in the sequence of events. Management of near misses includes their identification, reporting and investigation, and the learning that results. Safety theory suggests that acting on near misses will lead to actions to help prevent incidents. However, evidence also suggests that healthcare has yet to embrace the learning potential that patient safety near misses offer. The aims of this research, in support of this thesis, were to explore how best healthcare can learn from patient safety near misses to improve patient safety, and to identify what guidance non-healthcare safety-critical industries, which have implemented effective near-miss management systems, can offer healthcare. As this research progressed the aims were updated to include consideration of whether healthcare should seek to learn from patient safety near misses. Methods This research took a mixed-methods approach augmented by scoping reviews of the healthcare (study 1) and non-healthcare safety-critical industry (study 3) literature. A qualitative case study (study 2) was undertaken to explore the management of patient safety near misses in the English National Health Service. Seventeen interviews were undertaken with patient safety leads across acute hospitals, ambulance trusts, mental health trusts, primary care, and national bodies. A questionnaire was also used to help access the views of frontline staff. A grounded theory (study 4) was used to develop a set of principles, based on learning from non-healthcare safety-critical industries, around how best near misses can be managed. Thirty-five interviews were undertaken across aviation, maritime, and rail, with nuclear later added as per the theoretical sampling. Results The scoping reviews contributed 125 healthcare and 108 non-healthcare safety-critical industry academic articles, published internationally between 2000 and 2022, to the evidence gained from the qualitative case study and grounded theory. Safety cultures and maturity with safety management processes were found to vary in and across the different industries, and there was a reluctance for healthcare to learn about safety and near misses from other industries. Healthcare has yet to establish effective processes to manage patient safety near misses. There is an absence of evidence that learning has led to improvements in patient safety. The definition of a patient safety near miss varies, and organisations focus their efforts on reporting and investigating incidents, with limited attention to patient safety near misses. In non-healthcare safety-critical industries, near-miss management is more established, but process maturity varies in and across industries. Near misses are often defined specifically for an industry, but there is limited evidence that learning from them has improved safety. Information about near misses are commonly aggregated and may contribute to company and industry safety management systems. Exploration of the definition of a patient safety near miss led to the identification of the features of a near miss. The features have not been previously defined in the manner presented in this thesis. A patient safety near miss is context-specific and complex, involves interruptions, highlights system vulnerabilities, and is delineated from an incident by whether events reach a patient. Across healthcare and non-healthcare safety-critical industries the impact of learning from near misses is often assumed or extrapolated based on the common cause hypothesis. The hypothesis is regularly cited in safety literature and is used as the basis for justifying a focus on patient safety near misses. However, the validity of the hypothesis has been questioned and has not been validated for different patient safety near miss and incident types. Conclusions The research findings challenge long-held beliefs that learning from patient safety near misses will lead to improvements in patient safety. These beliefs are based on traditional safety theory that is unlikely to now be valid in the complexity of modern-day systems where incidents are the result of multiple factors and can emerge without apparent warning. Further research is required to understand the relationship between learning from patient safety near misses and patient safety, and whether the common cause hypothesis is valid for different types of healthcare safety event. While there are questions about the value of learning directly from patient safety near misses, the contribution of near misses to safety management systems in non-healthcare safety-critical industries looks to be beneficial for safety improvement. Safety management systems have yet to be implemented in the National Health Service and future research should look to understand how best this may be achieved and their value. In the meantime, patient safety near misses may help healthcareā€™s understanding of systems and their optimisation to create barriers to incidents and build resilience. This research offers an evidence-based definition of a patient safety near miss and describes principles to support identification, reporting, prioritisation, investigation, aggregation, learning, and action to help improve patient safety

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Systemic Circular Economy Solutions for Fiber Reinforced Composites

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    This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

    Everyday Streets

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    Everyday streets are both the most used and most undervalued of citiesā€™ public spaces. They are places of social aggregation, bringing together those belonging to different classes, genders, ages, ethnicities and nationalities. They comprise not just the familiar outdoor spaces that we use to move and interact but also urban blocks, interiors, depths and hinterlands, which are integral to their nature and contribute to their vitality. Everyday streets are physically and socially shaped by the lives of the people and things that inhabit them through a reciprocal dance with multiple overlapping temporalities. The primary focus of this book is an inclusive approach to understanding and designing everyday streets. It offers an analysis of many aspects of everyday streets from cities around the globe. From the regular rectilinear urban blocks of Montreal to the military-regulated narrow alleyways of Naples, and from the resilient market streets of London to the crammed commercial streets of Chennai, the streets in this book were all conceived with a certain level of control. Everyday Streets is a palimpsest of methods, perspectives and recommendations that together provide a solid understanding of everyday streets, their degree of inclusiveness, and to what extent they could be more inclusive

    Evaluating EEGā€“EMG Fusion-Based Classification as a Method for Improving Control of Wearable Robotic Devices for Upper-Limb Rehabilitation

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    Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices. One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor fusion techniques have been proposed to combine EEG and EMG; however, further development is required to enhance the capabilities of EEGā€“EMG fusion beyond basic motion classification. To this end, the goals of this thesis were to investigate expanded methods of EEGā€“EMG fusion and to develop a novel control system based on the incorporation of EEGā€“EMG fusion classifiers. A dataset of EEG and EMG signals were collected during dynamic elbow flexionā€“extension motions and used to develop EEGā€“EMG fusion models to classify task weight, as well as motion intention. A variety of fusion methods were investigated, such as a Weighted Average decision-level fusion (83.01 Ā± 6.04% accuracy) and Convolutional Neural Network-based input-level fusion (81.57 Ā± 7.11% accuracy), demonstrating that EEGā€“EMG fusion can classify more indirect tasks. A novel control system, referred to as a Task Weight Selective Controller (TWSC), was implemented using a Gain Scheduling-based approach, dictated by external load estimations from an EEGā€“EMG fusion classifier. To improve system stability, classifier prediction debouncing was also proposed to reduce misclassifications through filtering. Performance of the TWSC was evaluated using a developed upper-limb brace simulator. Due to simulator limitations, no significant difference in error was observed between the TWSC and PID control. However, results did demonstrate the feasibility of prediction debouncing, showing it provided smoother device motion. Continued development of the TWSC, and EEGā€“EMG fusion techniques will ultimately result in wearable devices that are able to adapt to changing loads more effectively, serving to improve the user experience during operation

    Evaluating behavioral intention to increase classroom Geotechnology usage following geoinquiry implementation

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    As educational practices include foundational and cutting-edge preparation, the value of problem-based instruction employing industry-standard technologies increases. Geospatial technologies (GST), are a group of professional technologies, including GIS (Geographic Information Systems), used by industries to make informed decisions with spatial data. This study investigated educator behavioral intention to use GIS/GST in classroom practice, and the moderating effect, if any, of the GeoInquiry, a curricular resource. The UTAUT framework was employed to evaluate and quantify the factors impacting behavioral intention (performance expectancy, effort expectancy, social influence, and facilitating conditions). These data were examined to identify moderation by GeoInquiry usage. One hundred and two surveys were completed by educators in 27 states. The survey results indicate a moderate statistically significant relationship between each of the factors and behavioral intention. An increase in any factor will increase behavioral intention. The mean response increased for the group that used GeoInquiries in classroom instruction, indicating correlation between each factor and GeoInquiry usage. Statistically significant differences related to using GeoInquiries in classroom instruction were identified for effort expectancy, facilitating conditions, and behavioral intention. Similar results related to the degree of GeoInquiry usage were not found. Implications include professional development for both educators and administrators, the continued development of curricular resources, and an alignment of both professional development and curricular resources to high yield instructional strategies, standards, and student engagement. Recommendations for future research include expanding the number of survey respondents, modifying items, conducting structured interviews, social network analysis, and developing curricular resources, which could impact student learning with digital mapping technology
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