1,355,001 research outputs found

    DIMO 1.0.1.0 manual

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    DIMO 1.0.1.0 is a plant dispersal model. It simulates plant dispersal in time, given (abiotic) suitability and species-specific characteristics. DIMO comprises three main processes: seed dispersal, seed-bank degradation and germination. The Manual for DIMO 1.0.1.0 consists of instructions on how to install the program, prepare the input data, run the model and uninstall the program

    Our sorrows

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    Title: Тъгите ни (Our sorrows) Originally published: Almanac Южни цветове, 1907, pp. 62–111. Language: Bulgarian The excerpts used are from the anthology: Stoyan Iliev ed., Блуждаеща естетика. Българските символисти за символизма, (Sofia: Издателство на БАН, 1992), pp. 158–161. About the author Dimo Kyorchev [1884, Veliko Tarnovo – 1928, Paris]: philosopher, essayist and politician. His father Petar Kyorchev was a teacher and former collaborator of Vasil Levski, the leader of the movement for..

    Our sorrows

    No full text
    Title: Тъгите ни (Our sorrows) Originally published: Almanac Южни цветове, 1907, pp. 62–111. Language: Bulgarian The excerpts used are from the anthology: Stoyan Iliev ed., Блуждаеща естетика. Българските символисти за символизма, (Sofia: Издателство на БАН, 1992), pp. 158–161. About the author Dimo Kyorchev [1884, Veliko Tarnovo – 1928, Paris]: philosopher, essayist and politician. His father Petar Kyorchev was a teacher and former collaborator of Vasil Levski, the leader of the movement for..

    Force control and EMG-based adaptive assistance for enhanced human-exoskeleton interaction

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    The increasing diffusion of exoskeletons in industrial, domestic, and medical environments highlights their potential to reduce work-related musculoskeletal disorders, support rehabilitation, and improve the mobility of people with disabilities. Unfortunately, control technologies capable of ensuring a reliable physical human-exoskeleton interaction and providing optimal assistance based on the load lifted by the user are still missing. This thesis investigates advanced control strategies that address key limitations of existing approaches by acting at both the low-level and high-level layers of exoskeleton control architectures. The first part of the thesis focuses on low-level force control. First, a force control benchmarking framework is developed to highlight well-known critical challenges in force control and to evaluate force control algorithms by taking into account diverse interacting environments. Next, a high-performance friction compensation solution for benchmarking applications is proposed to guarantee non-biased benchmarking results. Since the latter solution cannot be exploited outside the benchmarking scenario and given the importance of accurate friction compensation for reliable human-exoskeleton interaction, this thesis proposes a novel force control architecture that includes a model-reference friction observer. Since passivity is a fundamental requirement for interaction control, the conditions under which the proposed observer preserves passivity at the environment, control, and friction ports were investigated. This implies that the proposed architecture can perform passive friction compensation for any friction dynamics and can be combined with any passive force controller while guaranteeing a stable interaction with any passive environment. Experimental validation shows that the proposed approach outperforms existing friction compensation solutions in force control applications. The second part of the thesis focuses on high-level Electromyography (EMG)-based control strategies for Adaptive Gravity Compensation (AGC). To introduce the reader, a brief overview of Myoelectric Control Strategies (MCSs) is presented, showing that MCSs found in the literature are generally composed of three distinct functional modules: a decoder to extract the movement intention from EMG signals, a controller to accomplish the desired motion through a command given to the actuators, and a shaper to connect them. Subsequently, two EMG-based AGC approaches are proposed. Differently from existing AGC solutions, the proposed approaches (1) do not require knowledge of the anthropomorphic properties of the human arm and (2) recognize the importance of accounting for the human-exoskeleton dynamics within the adaptation law to improve payload estimation performance in dynamic conditions. The feasibility of the proposed approaches is experimentally validated on a 1-degree-of-freedom upper-limb exoskeleton

    Një medalion argjendi nga Apolonia (Belerofonti - vrasësi i përbindëshave) / A Silver Medallion from Apollonia (Bellerophontes: the Slayer of Monsters)

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    Dimo Vangjel. Një medalion argjendi nga Apolonia (Belerofonti - vrasësi i përbindëshave) / A Silver Medallion from Apollonia (Bellerophontes: the Slayer of Monsters). In: Iliria, vol. 36, 2012. pp. 249-252

    Environment Aware Friction Observer with Applications to Force Control Benchmarking

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    The benchmarking of force control algorithms has been significantly investigated in recent years. High-fidelity experimental benchmarking outcomes may require high-end electronics and mechanical systems not to compromise the algorithm’s evaluation. However, affordability may be highly desired to spread benchmarking tools within the research community. Mechanical inaccuracies due to affordability can lead to undesired friction effects which in this paper are tackled by exploiting a novel friction compensation technique based on an environment-aware friction observer (EA-FOB). Friction compensation capabilities of the proposed EA-FOB are assessed through simulation and experimental comparisons with a widely used static friction model: Coulomb friction combined with viscous friction. Moreover, a comprehensive stability comparison with state-of-the-art disturbance observers (DOBs) is conducted. Results show higher stability margins for the EA-FOB with respect to traditional DOBs. The research is carried on within the Forecast project, which aims to provide tools and metrics to benchmark force control algorithms relying on low-cost electronics and affordable hardware

    DiMO: Differentiable Model Optimization

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    I am interested in automated methods for model selection - architecture selection, hyperparameter selection and optimizer selection. To this end, I am developing DiMO (Differentiable Model Optimization): a novel technique for 1) model optimization (i.e. model selection for a fixed dataset by improving the selected architecture, hyperparameters and custom optimizers) and 2) meta-learning (i.e. automatic selection of model architectures for new tasks not observed during training). The main idea of DiMO is to develop a framework (flexible for both meta-learning and model optimization) that models the entire machine learning pipeline and minimize that objective directly with minimal hacks and tricks. The hope is that by optimizing the objective directly - with minimal modifications - performance of constructed models can be optimal and the search efficient, due to it's differentiable formulation.Open Restriction set for Item 116758 on 2020-12-14T20:08:23Z with date by [email protected] by Brando Miranda ([email protected]) on 2020-12-14T20:12:43Z No. of bitstreams: 1 DiMO_research_Statement.pdf: 116939 bytes, checksum: cf4fd7e9bbf25c375a5d2c5ac96f3d67 (MD5)Made available in DSpace on 2020-12-14T20:12:43Z (GMT). No. of bitstreams: 1 DiMO_research_Statement.pdf: 116939 bytes, checksum: cf4fd7e9bbf25c375a5d2c5ac96f3d67 (MD5) Previous issue date: 2020-03-01Ope

    The Reflective Entrepreneur

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    In a world where entrepreneurial success often seems deceptively accessible, it is not always clear what makes a person entrepreneurial. In this book, Dimo Dimov offers a reflective insight into the entrepreneurial journey, striking up a conversation about entrepreneurship in order to challenge and untangle existing preconceptions. A discussion of challenges and tensions such as idea versus opportunity, genius versus lunatic, and skill versus luck forms the foundation of the book, while the second part offers actions and considerations which can help the reader to seek opportunities in a fractious environment. The final part of the text focuses on the collective spirit in entrepreneurship, arising from the interplay between participation and outcomes. The author brings a succinct diversity to the field, making this book essential reading for undergraduate and postgraduate students on entrepreneurship courses, as well as scholars, researchers, and practitioners looking for a new perspective on entrepreneurship

    The Reflective Entrepreneur

    No full text
    In a world where entrepreneurial success often seems deceptively accessible, it is not always clear what makes a person entrepreneurial. In this book, Dimo Dimov offers a reflective insight into the entrepreneurial journey, striking up a conversation about entrepreneurship in order to challenge and untangle existing preconceptions. A discussion of challenges and tensions such as idea versus opportunity, genius versus lunatic, and skill versus luck forms the foundation of the book, while the second part offers actions and considerations which can help the reader to seek opportunities in a fractious environment. The final part of the text focuses on the collective spirit in entrepreneurship, arising from the interplay between participation and outcomes. The author brings a succinct diversity to the field, making this book essential reading for undergraduate and postgraduate students on entrepreneurship courses, as well as scholars, researchers, and practitioners looking for a new perspective on entrepreneurship
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