As the nature of systems changes, systems thinking must also change. A currently happening strong change is proliferation of highly intellectualized and socially deeply embedded engineered systems, which raise many no...
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After a major earthquake, quick inspections are conducted to confirm buildings' safety immediately, but these inspections require experts in architectural engineering. In this study, earthquake response analyses a...
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In this study, a simple theory-based framework is developed to show the relationship between expected and realised returns on stocks by dividend-oriented investors. The framework shows that the expected returns of inv...
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Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constraine...
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Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI technology has been applied to learning analytics (LA), aiming at a more accurate, consistent and scalable understanding of learning to compensate for challenges that human intelligence faces. However, machine intelligence has been criticized for lacking contextual understanding and difficulties dealing with complex human emotions and social cues. In this work, we aim to understand learners' internal cognitive processes based on the external behavioural cues of learners in a digital reading context, using a hybrid intelligence (HI) approach, bridging human and machine intelligence. Based on the behavioural frameworks and the insights from human experts, we scope specific behavioural cues that are known to be relevant to learners' attention regulation, which is highly relevant for learners' cognitive processes. We utilize the public WEDAR dataset with 30 subjects' video data, behaviour annotation and pre–post tests on multiple choice and summarization tasks. We apply the explainable AI (XAI) approach to train the machine learning model so that human evaluators can also understand which behavioural features were essential for predicting the usage of the cognitive processes (ie, higher-order thinking skills [HOTS] and lower-order thinking skills [LOTS]) of learners, providing insights for the next-round feature engineering and intervention design. The result indicates that the dominant use of attention regulation behaviours is a reliable indicator of low use of LOTS with 79.33% prediction accuracy, while reading speed is a valuable indicator for predicting the overall usage of HOTS and LOTS, ranging from 60.66% to 78.66% accuracy,
Hazardous substances, or substances of concern (SoC), are present in numerous products and may be the source of significant risks to human health and the environment. In addition, the presence of SoC in products chall...
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Hazardous substances, or substances of concern (SoC), are present in numerous products and may be the source of significant risks to human health and the environment. In addition, the presence of SoC in products challenges the transition towards a circular economy. By implementing strategies such as reuse or recycling, SoC can be reintroduced in subsequent lifecycles, generating new forms of risk. Addressing SoC in the early stages of the product development process is necessary to mitigate the hazards and risks they may present throughout multiple lifecycles. Product designers hence need appropriate tools and methods to address SoC in products. However, we have observed that current research primarily focuses on the development of non-toxic chemical alternatives and approaches that mitigate the risks of SoC at a chemical and material level (i.e., substitution), lacking the necessary holistic approach to avoid trade-offs or unforeseen consequences. Available design specific methods, tools, and information to address SoC in products are extremely limited and have too a material focus. To address this, we investigated five cases to understand how SoC were dealt with across the product lifecycle and identify mitigation interventions used. We then analyzed the interventions and classified them into five levels of influence, i.e., chemical, material, component, product, and system, and evaluated their respective implications for design, advantages, and drawbacks. Our analysis results in three groups of mitigation strategies that are specifically relevant to product design: Avoid, which entails any modification to the product that eliminates the SoC, Control, in which the SoC remains in use, but its emissions are prevented, and Reduce, which includes any modification that results in the reduction of the volume of the SoC or its emissions. Our findings establish the potential contribution of designers in the mitigation SoC in products and constitute a basis for the develop
This paper innovatively adopts an interdisciplinary method, which is urban design,combined with social investigation, statistical analysis, and case analysis. In this study, 1350residents in 45 blocks of Lansing were ...
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This paper innovatively adopts an interdisciplinary method, which is urban design,combined with social investigation, statistical analysis, and case analysis. In this study, 1350residents in 45 blocks of Lansing were selected as samples to investigate the related issuesof social capital, which include safety, contact with others, and sense of support for peopleliving in certain areas. There are two ways to measure the distance from the center of thecommunity to the nearest green space. One is the straight distance, while the other is pathdistance. Through statistical analysis, the path distance of less than 250 m is also added intothe variables. The results overturned the hypotheses and showed that the distance of greenspace was positively correlated with social capital. The residents of Lansing may prefer thedistant green space for recreational activities and create a way to participate in civic *** research can not only provide a basis for Lansing to formulate the appropriate resourcemanagement rules and norms and promote the accumulation of residents’ social capital, butalso provide a reference for urban green space planning in other areas. At the same time, inthe context of developing a smart city and constructing a new public system, we hope thatthe better optimization of the green space allocation will be achieved.
The paper investigates the amalgamation of LightGBM and Enhanced Colliding Bodies Optimization (ECBO) to establish a resilient framework for sustainable interior design optimization in residential projects. The main g...
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作者：
Matveeva, AngelicaResearch
Development and Innovation Section Faculty of Technology Art and Design Oslo Metropolitan University Oslo Norway
This article examines performance-based funding (PBF) as a governance tool in higher education through a meta-narrative review of recent literature. Rather than offering yet another extensive critique of neoliberalism...
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Patrol robots in hospital wards are expected not only to ensure the safety of their movements, but also to perform gait measurement as part of their monitoring functions. In this study, we present a system that enable...
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