1,455 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
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Towards a Global System of Innovation: the Role of Donors in Immunisation for International Development
This research examines what role donors play with respect to innovation in immunisation for international development. It uses as its conceptual framework the global innovation system (GIS) model to examine the principal donors within the sector. Because the empirical data is in-depth, contextualised, and qualitative, the research design adopted is that of a multiple case-study of donor organisations, using triangulated, mixed-methods qualitative data collection. The examined cases are UNICEF, the Bill and Melinda Gates Foundation, and Gavi, the Vaccine Alliance.
Knowledge gaps in the existing literature related to how these donors engage actors and institutions across different spatial levels for innovation; to how donors’ manifold power relations affect this; and to how donor structure and capabilities determine their particular roles in innovation.
The research finds strong evidence of an emerging GIS in immunisation for international development. This consists of a global sub-system and a set of sub-systems at the national level, each representing a country receiving development assistance in immunisation. Donors perform four principal roles within this GIS. Firstly, they provide, maintain and extend structural elements of the GIS, especially its networks and linkages between sub-systems. Secondly, donors generate and utilise resources of financial investment, market access and innovation legitimacy for the valuation of innovation. Thirdly, donors coordinate to ensure complementarity in the activities they and other actors provide, which enables effective distributed agency across the GIS. Fourthly, donors navigate the rules, norms and presumptions of the GIS on behalf of partnerships of actors, variously complying, co-opting or contesting them.
The relationship is shown between each of these principal roles and the system’s spatial levels, inter-actor power relations and donors’ structure and capabilities. This offers new, detailed understanding to close significantly the previously-identified knowledge gaps
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Policy options for food system transformation in Africa and the role of science, technology and innovation
As recognized by the Science, Technology and Innovation Strategy for Africa – 2024 (STISA-2024), science, technology and innovation (STI) offer many opportunities for addressing the main constraints to embracing transformation in Africa, while important lessons can be learned from successful interventions, including policy and institutional innovations, from those African countries that have already made significant progress towards food system transformation. This chapter identifies opportunities for African countries and the region to take proactive steps to harness the potential of the food and agriculture sector so as to ensure future food and nutrition security by applying STI solutions and by drawing on transformational policy and institutional innovations across the continent. Potential game-changing solutions and innovations for food system transformation serving people and ecology apply to (a) raising production efficiency and restoring and sustainably managing degraded resources; (b) finding innovation in the storage, processing and packaging of foods; (c) improving human nutrition and health; (d) addressing equity and vulnerability at the community and ecosystem levels; and (e) establishing preparedness and accountability systems. To be effective in these areas will require institutional coordination; clear, food safety and health-conscious regulatory environments; greater and timely access to information; and transparent monitoring and accountability systems
Systemic Circular Economy Solutions for Fiber Reinforced Composites
This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials
SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
We introduce SwiftSage, a novel agent framework inspired by the dual-process
theory of human cognition, designed to excel in action planning for complex
interactive reasoning tasks. SwiftSage integrates the strengths of behavior
cloning and prompting large language models (LLMs) to enhance task completion
performance. The framework comprises two primary modules: the Swift module,
representing fast and intuitive thinking, and the Sage module, emulating
deliberate thought processes. The Swift module is a small encoder-decoder LM
fine-tuned on the oracle agent's action trajectories, while the Sage module
employs LLMs such as GPT-4 for subgoal planning and grounding. We develop a
heuristic method to harmoniously integrate the two modules, resulting in a more
efficient and robust problem-solving process. In 30 tasks from the ScienceWorld
benchmark, SwiftSage significantly outperforms other methods such as SayCan,
ReAct, and Reflexion, demonstrating its effectiveness in solving complex
real-world tasks.Comment: Project website: https://yuchenlin.xyz/swiftsage
Automatic Generation of Personalized Recommendations in eCoaching
Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio
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Shaping and expressing politics: a comparative study of national parliament buildings within the European Union
Book chapter. No abstract available
Responsive Building Envelope for Grid-Interactive Efficient Buildings – Thermal Performance and Control
The building sector accounts for 30% of total energy consumption worldwide. Responsive building envelopes (or RBEs) are one of the approaches to achieving net-zero energy and grid-interactive efficient buildings. However, research and development of RBEs are still in the early stages of technologies, simulation, control, and design. The control strategies in prior studies did not fully explore the potential of RBEs or they obtained good performance with high design and deployment costs. A low-cost strategy that does not require knowledge of complex systems is needed, while no studies have investigated online implementations of model-free control approaches for RBEs. To address these challenges, this dissertation describes a multidisciplinary study of the modeling, control, and design of RBEs, to understand mechanisms governing their dynamic properties and synthesis rules of multiple technologies through simulation analyses. Widely applicable mathematical models are developed that can be easily extended for multiple RBE types with validation. Computational frameworks (or co-simulation testbeds) that flexibly integrate multiple control methods and building simulation models are established with higher computation efficiency than that using commercial software during offline training. To overcome the limitations of the control strategies (e.g., rule-based control and MPC) in prior research, a novel easy-to-implement yet flexible ‘demand-based’ control strategy, and model-free online control strategies using deep reinforced learning are proposed for RBEs composed of active insulation systems (AISs). Both the physics-derived and model-free control strategies fully leverage the advantages of AISs and provide higher energy savings and thermal comfort improvement over traditional temperature-based control methods in prior research and demand-based control. The case studies of RBEs that integrate AISs and high thermal mass or self-adaptive/active modules (e.g., evaporative cooling techniques and dynamic glazing/shading) demonstrate the superior performance of AISs in regulating thermal energy transfer to offset AC demands during the synergy. Moreover, the controller design and training implications are elaborated. The applicability assessment of promising RBE configurations is presented along with design implications based on building energy analyses in multiple scenarios. The design and control implications represent an interactive and holistic way to operate RBEs allowing energy and thermal comfort performances to be tuned for maximum efficiency
Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives
Collectiveness is an important property of many systems--both natural and
artificial. By exploiting a large number of individuals, it is often possible
to produce effects that go far beyond the capabilities of the smartest
individuals, or even to produce intelligent collective behaviour out of
not-so-intelligent individuals. Indeed, collective intelligence, namely the
capability of a group to act collectively in a seemingly intelligent way, is
increasingly often a design goal of engineered computational systems--motivated
by recent techno-scientific trends like the Internet of Things, swarm robotics,
and crowd computing, just to name a few. For several years, the collective
intelligence observed in natural and artificial systems has served as a source
of inspiration for engineering ideas, models, and mechanisms. Today, artificial
and computational collective intelligence are recognised research topics,
spanning various techniques, kinds of target systems, and application domains.
However, there is still a lot of fragmentation in the research panorama of the
topic within computer science, and the verticality of most communities and
contributions makes it difficult to extract the core underlying ideas and
frames of reference. The challenge is to identify, place in a common structure,
and ultimately connect the different areas and methods addressing intelligent
collectives. To address this gap, this paper considers a set of broad scoping
questions providing a map of collective intelligence research, mostly by the
point of view of computer scientists and engineers. Accordingly, it covers
preliminary notions, fundamental concepts, and the main research perspectives,
identifying opportunities and challenges for researchers on artificial and
computational collective intelligence engineering.Comment: This is the author's final version of the article, accepted for
publication in the Artificial Life journal. Data: 34 pages, 2 figure
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