The increasing competition among industries has led to the emergence of numerous tools and methods to support decision making focused on assets maintenance in a company, since ensuring good maintenance is directly lin...
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In the field of intracellular phase separation, characterizing the composition and formation of liquid-like organelles is important to understanding their functional relevance. We introduce a microfluidic assay for in...
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The first open invited track in multi-objective optimisation for control systems was organised in 2017 with the idea of exchanging ideas and research about how those techniques are valuable for control engineers. Give...
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The first open invited track in multi-objective optimisation for control systems was organised in 2017 with the idea of exchanging ideas and research about how those techniques are valuable for control engineers. Given that control engineering problems are generally multi-objective problems, multi-objective optimisation offers an interesting approach via the simultaneous optimisation of all design objectives. Controller tuning is not except from this. In this paper we perform a review and analysis of the literature, limited to the IFAC environment, to appreciate and detect new tendencies in controller tuning applications via multi-objective optimisation. Time window under consideration is from 2015 to date, coinciding with a previous review on the topic, as well as the emigration of IFAC proceedings to Elsevier.
This present research examines the behavioral intentions of Filipinos to use online grocery applications during the novel COVID-19 pandemic. The study proposes an integration of the health belief model (HBM) and the U...
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Iterative algorithms are of utmost importance in decision and control. With an ever growing number of algorithms being developed, distributed, and proprietarized, there is a similarly growing need for methods that can...
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ISBN:
(数字)9781665467612
ISBN:
(纸本)9781665467629
Iterative algorithms are of utmost importance in decision and control. With an ever growing number of algorithms being developed, distributed, and proprietarized, there is a similarly growing need for methods that can provide classification and comparison. By viewing iterative algorithms as discrete-time dynamical systems, we leverage Koopman operator theory to identify (semi-)conjugacies between algorithms using their spectral properties. This provides a general framework with which to classify and compare algorithms.
Non-invasive vibration measurements from the knee offer a convenient and affordable alternative to benchtop or biomechanics lab joint health monitoring systems. Recently, joint acoustic emissions (JAEs) measured from ...
Non-invasive vibration measurements from the knee offer a convenient and affordable alternative to benchtop or biomechanics lab joint health monitoring systems. Recently, joint acoustic emissions (JAEs) measured from the knee were shown to be an indicator of knee health. However, the origin of JAEs is still not fully understood, which limits its acceptance and use by clinical experts. In this proof-of-concept study, rather than relying on the movements of the knee and corresponding frictional rubbing of internal surfaces to produce vibrations, we propose using an active vibration sensing approach with a known vibration source interrogating the knee. We aim to elucidate the linkage between knee vibration characteristics and structural changes in the joint following injuries. We measured tibial vibration responses of two participants using a laser vibrometer system to quantify the frequency band where the most repeatable tibial vibration measurement can be taken. Subsequently, a custom-designed wearable system measured mid-activity tibial vibration characteristics from four participants (five healthy knees and three knees with prior acute injury) during unloaded knee flexion-extensions. An active sensing knee health score was defined as the ratio of the changes in low- to high-frequency response during flexion-extension. Since changes in the boundary of tibia would alter low-frequency response more than high frequency response, we found that increased knee laxity with acute injuries resulted in an increased active sensing knee health score. Our findings demonstrate the potential of active vibration sensing as an interpretable, computationally inexpensive alternative to JAEs for wearable knee health assessment.
While several content management systems (CMS) and audience analytics tools are available for digital signage in the market, they are often sold separately and can be expensive. Therefore, this project aims to design ...
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General anaesthesia is a clinical procedure that involves the continuous monitoring of several parameters for the correct application of anaesthetics and associated drugs. Focusing on the automatic control in anaesthe...
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General anaesthesia is a clinical procedure that involves the continuous monitoring of several parameters for the correct application of anaesthetics and associated drugs. Focusing on the automatic control in anaesthesia, this work presents a multiobjective optimization design of controllers based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to solve the problem of drug delivery for induction of anaesthesia. Five Proportional-Integral-Derivative (PID) controllers in a decentralized scheme were tuned for one specific patient and tested in a total of 24 simulated patients. Acting over the infusions of Propofol, Remifentanil, Atracurium, Dobutamine, and Sodium Nitroprusside the proposed controllers could maintain the controlled variables in a safe range for surgical procedures.
Collision Avoidance/Mitigation System (CAMS) for autonomous vehicles is a crucial technology that ensures the safety and reliability of autonomous driving systems. Conventional collision avoidance approaches struggle ...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Collision Avoidance/Mitigation System (CAMS) for autonomous vehicles is a crucial technology that ensures the safety and reliability of autonomous driving systems. Conventional collision avoidance approaches struggle in complex and various scenarios by avoiding collisions based on rules for specific collision scenarios. This has led to learning-based methods using neural networks for adaptive collision avoidance. However, the approaches directly outputting control inputs through neural networks have drawbacks in interpretability and stability. To address these limitations, we propose a trajectory planning method for CAMS that combines deep reinforcement learning (DRL) and quintic polynomial (QP) trajectory planning. The proposed method determines the terminal state and confidence of the trajectory using DRL and plans a QP trajectory based on them. By utilizing the terminal state and confidence of the trajectory rather than direct control inputs as the output of the neural network, it generates a more realistic and continuous path. Moreover, this approach considers collision avoidance and mitigation in an integrated manner through the reward function of RL. Our experimental results demonstrate that the proposed method not only improves interpretability and stability compared to existing learning-based methods but also upholds performance in complex and various collision scenarios.
Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitati...
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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative
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