8,186 research outputs found

    Unleashing the power of artificial intelligence for climate action in industrial markets

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    Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change

    Graduate Catalog of Studies, 2023-2024

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    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

    Measurement Platform for Latency Characterization of Wide Area Monitoring, Protection and Control Systems

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    Wide area monitoring, protection and control (WAMPAC) systems have emerged as a critical technology to improve the reliability, resilience, and stability of modern power grids. They are based on phasor measurement unit (PMU) technology and synchronized monitoring on a wide area. Since these systems are required to make rapid decisions and control actions on the grid, they are characterized by stringent time constraints. For this reason, the latency of WAMPAC systems needs to be appropriately assessed. Following this necessity, this article presents the design and implementation of a measurement platform that allows latency characterization of different types of WAMPAC systems in several operating conditions. The proposed WAMPAC Characterizer has been metrologically characterized through a WAMPAC Emulator and then used to measure the latency of a WAMPAC system based on an open-source platform frequently used by transmission system operators (TSOs) for the implementation of their PMU-based wide area systems

    Seamless Multimodal Biometrics for Continuous Personalised Wellbeing Monitoring

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    Artificially intelligent perception is increasingly present in the lives of every one of us. Vehicles are no exception, (...) In the near future, pattern recognition will have an even stronger role in vehicles, as self-driving cars will require automated ways to understand what is happening around (and within) them and act accordingly. (...) This doctoral work focused on advancing in-vehicle sensing through the research of novel computer vision and pattern recognition methodologies for both biometrics and wellbeing monitoring. The main focus has been on electrocardiogram (ECG) biometrics, a trait well-known for its potential for seamless driver monitoring. Major efforts were devoted to achieving improved performance in identification and identity verification in off-the-person scenarios, well-known for increased noise and variability. Here, end-to-end deep learning ECG biometric solutions were proposed and important topics were addressed such as cross-database and long-term performance, waveform relevance through explainability, and interlead conversion. Face biometrics, a natural complement to the ECG in seamless unconstrained scenarios, was also studied in this work. The open challenges of masked face recognition and interpretability in biometrics were tackled in an effort to evolve towards algorithms that are more transparent, trustworthy, and robust to significant occlusions. Within the topic of wellbeing monitoring, improved solutions to multimodal emotion recognition in groups of people and activity/violence recognition in in-vehicle scenarios were proposed. At last, we also proposed a novel way to learn template security within end-to-end models, dismissing additional separate encryption processes, and a self-supervised learning approach tailored to sequential data, in order to ensure data security and optimal performance. (...)Comment: Doctoral thesis presented and approved on the 21st of December 2022 to the University of Port

    Tradition and Innovation in Construction Project Management

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    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Emerging Power Electronics Technologies for Sustainable Energy Conversion

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    This Special Issue summarizes, in a single reference, timely emerging topics related to power electronics for sustainable energy conversion. Furthermore, at the same time, it provides the reader with valuable information related to open research opportunity niches

    Improving approaches to material inventory management in construction industry in the UK

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    Materials used in construction constitute a major proportion of the total cost of construction projects. An important factor of great concern that adversely affects construction projects is the location and tracking of materials, which normally come in bulk with minimal identification. There is inadequate integration of modern wireless technologies (such as Radio Frequency Identification (RFID), Personal Digital Assistant (PDA) or Just-in-Time (JIT)) into project management systems for easier and faster materials management and tracking and to overcome human error. This research focuses on improving approaches to material inventory management in the UK construction industry through the formulation of RFID-based materials management tracking process system with projects. Existing literature review identified many challenges/problems in material inventory management on construction projects, such as supply delays, shortages, price fluctuations, wastage and damage, and insufficient storage space. Six construction projects were selected as exploratory case studies and cross-case analysis was used to investigate approaches to material inventory management practices: problems, implementation of ICT, and the potential for using emerging wireless technologies and systems (such as RFID and PDA) for materials tracking. Findings showed that there were similar problems of storage constraints and logistics with most of the construction projects. The synthesis of good practices required the implementation of RFID-facilitated construction management of materials tracking system to make material handling easier, quicker, more efficient and less paperwork. There was also a recommendation to implement Information and Communication Technology (ICT) tools to integrate plant, labour and materials into one system. The findings from the cases studies and the literature review were used to formulate a process for real-time material tracking using Radio Frequency Identification (RFID) that can improve material inventory management in the UK construction industry. Testing and validation undertaken assisted in formulating a process that can be useful, functional and acceptable for a possible process system’s development. Finally, research achievements/contributions to knowledge, and limitations were discussed and some suggestions for further research were outlined
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