8,984 research outputs found

    Functional Nanomaterials and Polymer Nanocomposites: Current Uses and Potential Applications

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    This book covers a broad range of subjects, from smart nanoparticles and polymer nanocomposite synthesis and the study of their fundamental properties to the fabrication and characterization of devices and emerging technologies with smart nanoparticles and polymer integration

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    Reliable Sensor Intelligence in Resource Constrained and Unreliable Environment

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    The objective of this research is to design a sensor intelligence that is reliable in a resource constrained, unreliable environment. There are various sources of variations and uncertainty involved in intelligent sensor system, so it is critical to build reliable sensor intelligence. Many prior works seek to design reliable sensor intelligence by developing robust and reliable task. This thesis suggests that along with improving task itself, task reliability quantification based early warning can further improve sensor intelligence. DNN based early warning generator quantifies task reliability based on spatiotemporal characteristics of input, and the early warning controls sensor parameters and avoids system failure. This thesis presents an early warning generator that predicts task failure due to sensor hardware induced input corruption and controls the sensor operation. Moreover, lightweight uncertainty estimator is presented to take account of DNN model uncertainty in task reliability quantification without prohibitive computation from stochastic DNN. Cross-layer uncertainty estimation is also discussed to consider the effect of PIM variations.Ph.D

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    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

    Financial and Economic Review 22.

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    Measuring the impact of COVID-19 on hospital care pathways

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    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Évaluation et modulation des fonctions exécutives en neuroergonomie - Continuums cognitifs et expérimentaux

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    Des études en neuroergonomie ont montré que le pilote d’avion pouvait commettre des erreurs en raison d’une incapacité transitoire à faire preuve de flexibilité mentale. Il apparait que certains facteurs, tels qu’une forte charge mentale ou une pression temporelle importante, un niveau de stress trop élevé, la survenue de conflits, ou une perte de conscience de la situation, peuvent altérer temporairement l’efficience des fonctions exécutives permettant cette flexibilité. Depuis mes travaux initiaux, dans lesquels je me suis intéressé aux conditions qui conduisent à une négligence auditive, j’ai souhaité développer une approche scientifique visant à quantifier et limiter les effets délétères de ces différents facteurs. Ceci a été fait à travers l’étude des fonctions exécutives chez l’être humain selon le continuum cognitif (du cerveau lésé au cerveau en parfait état de fonctionnement) et le continuum expérimental (de l’ordinateur au monde réel). L’approche fondamentale de l’étude des fonctions exécutives en neurosciences combinée à l’approche neuroergonomique graduelle avec des pilotes et des patients cérébro-lésés, a permis de mieux comprendre la manière dont ces fonctions sont mises en jeu et altérées. Cette connaissance à contribuer par la suite à la mise en place de solutions pour préserver leur efficacité en situation complexe. Après avoir rappelé mon parcours académique, je présente dans ce manuscrit une sélection de travaux répartis sur trois thématiques de recherche. La première concerne l’étude des fonctions exécutives impliquées dans l’attention et en particulier la façon dont la charge perceptive et la charge mentale peuvent altérer ces fonctions. La deuxième correspond à un aspect plus appliqué de ces travaux avec l’évaluation de l’état du pilote. Il a été question d’analyser cet état selon l’activité de pilotage elle-même ou à travers la gestion et la supervision d’un système en particulier. La troisième et dernière thématique concerne la recherche de marqueurs prédictifs de la performance cognitive et l’élaboration d’entraînements cognitifs pour limiter les troubles dysexécutifs, qu’ils soient d’origine contextuelle ou lésionnelle. Ces travaux ont contribué à une meilleure compréhension des troubles cognitifs transitoires ou chroniques, mais ils ont aussi soulevé des questions auxquelles je souhaite répondre aujourd’hui. Pour illustrer cette réflexion, je présente en dernière partie de ce document mon projet de recherche qui vise à développer une approche multifactorielle de l’efficience cognitive, éthique et en science ouverte

    Various Applications of Methods and Elements of Adaptive Optics

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    This volume is focused on a wide range of topics, including adaptive optic components and tools, wavefront sensing, different control algorithms, astronomy, and propagation through turbulent and turbid media

    Compute-proximal Energy Harvesting for Mobile Environments: Fundamentals, Applications, and Tools

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    Over the past two decades, we have witnessed remarkable achievements in computing, sensing, actuating, and communications capabilities of ubiquitous computing applications. However, due to the limitations in stable energy supply, it is difficult to make the applications ubiquitous. Batteries have been considered a promising technology for this problem, but their low energy density and sluggish innovation have constrained the utility and expansion of ubiquitous computing. Two key techniques—energy harvesting and power management—have been studied as alternatives to overcome the battery limitations. Compared to static environments such as homes or buildings, there are more energy harvesting opportunities in mobile environments since ubiquitous systems can generate various forms of energy as they move. Most of the previous studies in this regard have been focused on human movements for wearable computing, while other mobile environments (e.g., cars, motorcycles, and bikes) have received limited attention. In this thesis, I present a class of energy harvesting approaches called compute-proximal energy harvesting, which allows us to develop energy harvesting technology where computing, sensing, and actuating are needed in vehicles. Computing includes sensing phenomena, executing instructions, actuating components, storing information, and communication. Proximal considers the harvesting of energy available around the specific location where computation is needed, reducing the need for excessive wiring. A primary goal of this new approach is to mitigate the effort associated with the installation and field deployment of self-sustained computing and lower the entry barriers to developing self-sustainable systems for vehicles. In this thesis, I first select an automobile as a promising case study and discuss the opportunities, challenges, and design guidelines of compute-proximal energy harvesting with practical yet advanced examples in the automotive domain. Second, I present research in the design of small-scale wind energy harvesters and the implementation and evaluation of two advanced safety sensing systems—a blind spot monitoring system and a lane detection system—with the harvested power from wind. Finally, I conduct a study to democratize the lessons learned from the automotive case studies for makers and people with no prior experience in energy harvesting technology. In this study, I seek to understand what problems they have encountered and what possible solutions they have considered while dealing with energy harvesting technology. Based on the findings, I develop a comprehensive energy harvesting toolkit and examine its utility, usability, and creativity through a series of workshops.Ph.D
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