2,075 research outputs found

    Water, politics and river basin governance : repoliticizing approaches to river basin management

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    Water management is commonly assumed to be a mere technical matter where experts and managers endeavour to match supply and demand by using technology, through rational problem-solving and by engaging stakeholders. This article, in contrast, emphasizes that river basin development and management is about the shifting patterns of access to a contested and scarce resource and is inherently a political process. An investigation of the physical and social characteristics and constraints of river basins must be conducted in parallel with an analysis of the convergent interests manifest in capital intensive water investments, and an attention to how discursive power is used in the justification of large-scale investments. Thus, repoliticizing river basin management offers a different and complementary perspective that allows a better understanding of society/environment relationships

    Visual AI and Linguistic Intelligence Through Steerability and Composability

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    This study explores the capabilities of multimodal large language models (LLMs) in handling challenging multistep tasks that integrate language and vision, focusing on model steerability, composability, and the application of long-term memory and context understanding. The problem addressed is the LLM's ability (Nov 2023 GPT-4 Vision Preview) to manage tasks that require synthesizing visual and textual information, especially where stepwise instructions and sequential logic are paramount. The research presents a series of 14 creatively and constructively diverse tasks, ranging from AI Lego Designing to AI Satellite Image Analysis, designed to test the limits of current LLMs in contexts that previously proved difficult without extensive memory and contextual understanding. Key findings from evaluating 800 guided dialogs include notable disparities in task completion difficulty. For instance, 'Image to Ingredient AI Bartender' (Low difficulty) contrasted sharply with 'AI Game Self-Player' (High difficulty), highlighting the LLM's varying proficiency in processing complex visual data and generating coherent instructions. Tasks such as 'AI Genetic Programmer' and 'AI Negotiator' showed high completion difficulty, emphasizing challenges in maintaining context over multiple steps. The results underscore the importance of developing LLMs that combine long-term memory and contextual awareness to mimic human-like thought processes in complex problem-solving scenarios

    The Cord Weekly (October 6, 1999)

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    Practice of strategy

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    Sustainability in design: now! Challenges and opportunities for design research, education and practice in the XXI century

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    Copyright @ 2010 Greenleaf PublicationsLeNS project funded by the Asia Link Programme, EuropeAid, European Commission

    Workload-aware systems and interfaces for cognitive augmentation

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    In today's society, our cognition is constantly influenced by information intake, attention switching, and task interruptions. This increases the difficulty of a given task, adding to the existing workload and leading to compromised cognitive performances. The human body expresses the use of cognitive resources through physiological responses when confronted with a plethora of cognitive workload. This temporarily mobilizes additional resources to deal with the workload at the cost of accelerated mental exhaustion. We predict that recent developments in physiological sensing will increasingly create user interfaces that are aware of the user’s cognitive capacities, hence able to intervene when high or low states of cognitive workload are detected. In this thesis, we initially focus on determining opportune moments for cognitive assistance. Subsequently, we investigate suitable feedback modalities in a user-centric design process which are desirable for cognitive assistance. We present design requirements for how cognitive augmentation can be achieved using interfaces that sense cognitive workload. We then investigate different physiological sensing modalities to enable suitable real-time assessments of cognitive workload. We provide empirical evidence that the human brain is sensitive to fluctuations in cognitive resting states, hence making cognitive effort measurable. Firstly, we show that electroencephalography is a reliable modality to assess the mental workload generated during the user interface operation. Secondly, we use eye tracking to evaluate changes in eye movements and pupil dilation to quantify different workload states. The combination of machine learning and physiological sensing resulted in suitable real-time assessments of cognitive workload. The use of physiological sensing enables us to derive when cognitive augmentation is suitable. Based on our inquiries, we present applications that regulate cognitive workload in home and work settings. We deployed an assistive system in a field study to investigate the validity of our derived design requirements. Finding that workload is mitigated, we investigated how cognitive workload can be visualized to the user. We present an implementation of a biofeedback visualization that helps to improve the understanding of brain activity. A final study shows how cognitive workload measurements can be used to predict the efficiency of information intake through reading interfaces. Here, we conclude with use cases and applications which benefit from cognitive augmentation. This thesis investigates how assistive systems can be designed to implicitly sense and utilize cognitive workload for input and output. To do so, we measure cognitive workload in real-time by collecting behavioral and physiological data from users and analyze this data to support users through assistive systems that adapt their interface according to the currently measured workload. Our overall goal is to extend new and existing context-aware applications by the factor cognitive workload. We envision Workload-Aware Systems and Workload-Aware Interfaces as an extension in the context-aware paradigm. To this end, we conducted eight research inquiries during this thesis to investigate how to design and create workload-aware systems. Finally, we present our vision of future workload-aware systems and workload-aware interfaces. Due to the scarce availability of open physiological data sets, reference implementations, and methods, previous context-aware systems were limited in their ability to utilize cognitive workload for user interaction. Together with the collected data sets, we expect this thesis to pave the way for methodical and technical tools that integrate workload-awareness as a factor for context-aware systems.TagtĂ€glich werden unsere kognitiven FĂ€higkeiten durch die Verarbeitung von unzĂ€hligen Informationen in Anspruch genommen. Dies kann die Schwierigkeit einer Aufgabe durch mehr oder weniger Arbeitslast beeinflussen. Der menschliche Körper drĂŒckt die Nutzung kognitiver Ressourcen durch physiologische Reaktionen aus, wenn dieser mit kognitiver Arbeitsbelastung konfrontiert oder ĂŒberfordert wird. Dadurch werden weitere Ressourcen mobilisiert, um die Arbeitsbelastung vorĂŒbergehend zu bewĂ€ltigen. Wir prognostizieren, dass die derzeitige Entwicklung physiologischer Messverfahren kognitive Leistungsmessungen stets möglich machen wird, um die kognitive Arbeitslast des Nutzers jederzeit zu messen. Diese sind in der Lage, einzugreifen wenn eine zu hohe oder zu niedrige kognitive Belastung erkannt wird. Wir konzentrieren uns zunĂ€chst auf die Erkennung passender Momente fĂŒr kognitive UnterstĂŒtzung welche sich der gegenwĂ€rtigen kognitiven Arbeitslast bewusst sind. Anschließend untersuchen wir in einem nutzerzentrierten Designprozess geeignete Feedbackmechanismen, die zur kognitiven Assistenz beitragen. Wir prĂ€sentieren Designanforderungen, welche zeigen wie Schnittstellen eine kognitive Augmentierung durch die Messung kognitiver Arbeitslast erreichen können. Anschließend untersuchen wir verschiedene physiologische MessmodalitĂ€ten, welche Bewertungen der kognitiven Arbeitsbelastung in Realzeit ermöglichen. ZunĂ€chst validieren wir empirisch, dass das menschliche Gehirn auf kognitive Arbeitslast reagiert. Es zeigt sich, dass die Ableitung der kognitiven Arbeitsbelastung ĂŒber Elektroenzephalographie eine geeignete Methode ist, um den kognitiven Anspruch neuartiger Assistenzsysteme zu evaluieren. Anschließend verwenden wir Eye-Tracking, um VerĂ€nderungen in den Augenbewegungen und dem Durchmesser der Pupille unter verschiedenen IntensitĂ€ten kognitiver Arbeitslast zu bewerten. Das Anwenden von maschinellem Lernen fĂŒhrt zu zuverlĂ€ssigen Echtzeit-Bewertungen kognitiver Arbeitsbelastung. Auf der Grundlage der bisherigen Forschungsarbeiten stellen wir Anwendungen vor, welche die Kognition im hĂ€uslichen und beruflichen Umfeld unterstĂŒtzen. Die physiologischen Messungen stellen fest, wann eine kognitive Augmentierung sich als gĂŒnstig erweist. In einer Feldstudie setzen wir ein Assistenzsystem ein, um die erhobenen Designanforderungen zur Reduktion kognitiver Arbeitslast zu validieren. Unsere Ergebnisse zeigen, dass die Arbeitsbelastung durch den Einsatz von Assistenzsystemen reduziert wird. Im Anschluss untersuchen wir, wie kognitive Arbeitsbelastung visualisiert werden kann. Wir stellen eine Implementierung einer Biofeedback-Visualisierung vor, die das NutzerverstĂ€ndnis zum Verlauf und zur Entstehung von kognitiver Arbeitslast unterstĂŒtzt. Eine abschließende Studie zeigt, wie Messungen kognitiver Arbeitslast zur Vorhersage der aktuellen Leseeffizienz benutzt werden können. Wir schließen hierbei mit einer Reihe von Applikationen ab, welche sich kognitive Arbeitslast als Eingabe zunutze machen. Die vorliegende wissenschaftliche Arbeit befasst sich mit dem Design von Assistenzsystemen, welche die kognitive Arbeitslast der Nutzer implizit erfasst und diese bei der DurchfĂŒhrung alltĂ€glicher Aufgaben unterstĂŒtzt. Dabei werden physiologische Daten erfasst, um RĂŒckschlĂŒsse in Realzeit auf die derzeitige kognitive Arbeitsbelastung zu erlauben. Anschließend werden diese Daten analysiert, um dem Nutzer strategisch zu assistieren. Das Ziel dieser Arbeit ist die Erweiterung neuartiger und bestehender kontextbewusster Benutzerschnittstellen um den Faktor kognitive Arbeitslast. Daher werden in dieser Arbeit arbeitslastbewusste Systeme und arbeitslastbewusste Benutzerschnittstellen als eine zusĂ€tzliche Dimension innerhalb des Paradigmas kontextbewusster Systeme prĂ€sentiert. Wir stellen acht Forschungsstudien vor, um die Designanforderungen und die Implementierung von kognitiv arbeitslastbewussten Systemen zu untersuchen. Schließlich stellen wir unsere Vision von zukĂŒnftigen kognitiven arbeitslastbewussten Systemen und Benutzerschnittstellen vor. Durch die knappe VerfĂŒgbarkeit öffentlich zugĂ€nglicher DatensĂ€tze, Referenzimplementierungen, und Methoden, waren Kontextbewusste Systeme in der Auswertung kognitiver Arbeitslast bezĂŒglich der Nutzerinteraktion limitiert. ErgĂ€nzt durch die in dieser Arbeit gesammelten DatensĂ€tze erwarten wir, dass diese Arbeit den Weg fĂŒr methodische und technische Werkzeuge ebnet, welche kognitive Arbeitslast als Faktor in das Kontextbewusstsein von Computersystemen integriert

    VertiFarm2024 - Book of Abstracts

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    Vertical farming, growing plants on multiple layers or upright surfaces, in enclosed climate controlled chambers and supplemented with artificial lighting technologies, is reshaping current agriculture. This revolutionary way of food production may substantially impact our knowledge on plant biology and physiology, cultivation systems and resource use. Beyond the hype toward this new sector, a clear need for successful cooperation between industry and research is pivotal to ensure feasibility and sustainability of the technology. The International Workshop on Vertical Farming (abbreviated as VertiFarm from its 1st edition, in 2019, followed by a 2nd event in 2023) is a recurring workshop within the portfolio of scientific dissemination and communication events of the International Society for Horticultural Sciences (ISHS), the World's leading independent organization of horticulturists with a network of over 70,000 individuals, universities, governments, institutions, libraries and commercial companies. At VertiFarm, experts from diversified World regions and with cross-disciplinary backgrounds encounter entrepreneurs, policy makers and investors to exchange on priorities and challenges of the sector. Its mission is to shed light on innovation technologies and pave the way for the future evolution of the sector. The content of the 3rd International Workshop on Vertical Farming (#VertiFarm2024) are condensed in the following pages, where an effort was made to summarize the many diverse (though all significant) steps research and industry are advancing toward a viable vertical farming sector, ranging from the single technologies to the whole food system approach. Thematic sessions, business panels, workshop, technical visits and a dense agenda of social and networking events constitute the solid framework of the workshop series, as clearly visible in the agenda of this VertiFarm2024 edition. We sincerely hope you will enjoy the workshop and look forward to meet and exchange with you in the coming days
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