149 research outputs found
Implications of vehicle automation for accessibility and social inclusion of people on low income, people with physical and sensory disabilities, and older people
No full textGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Logistic
Case Study of Physiotherapy Treatment of a Patient with the Diagnosis Shoulder Luxation
No full textTitle: Case Study of Physiotherapy Treatment of a Patient with the Diagnosis Shoulder Luxation Název: Kazuistika fyzioterapeutické péče o pacienta s diagnózou luxace ramenního kloubu Author: Emmanouil Kassakis This bachelor thesis is divided into two parts, the general part and the special part. In the general part, it is included all the theoretical information about my patient's diagnosis. Specifically, the theoretical part is composed by the basic anatomy of the shoulder joint including muscles, joint, ligaments and bones. Then the biomechanical and kinesiological field. Furthermore, it is explained in details how the shoulder luxation injury is it possible to happen. Secondly, the special part which is the most important part of the bachelor thesis, it is composed by the whole information, examinations, therapy sessions and results of my patient. It is explained in details and in pictures of the patient during her therapy sessions as well. There were performed to the patient about 7 therapies sessions. Starting from Wednesday 5 February 2014 and ending on Friday 14 February 2014. Each therapy session is explained in details including the procedure and the results as well. Key words: shoulder, shoulder luxation, conservative treatment, shoulder girdle, range of motion, exercise. Powered by TCPDF..
Case study of Physical Therapy approach of patient with Anterior. Cruciate Ligament rupture after traumatic injury in skiing
No full textTitle: Physical Therapy program in a patient with total rupture of Anterior Cruciate Ligament and partial rupture of Medial Collateral Ligament of the right knee joint after ski accident. Název bakalářské práce: Author: Emmanouil Tsichlakis The current Bachelor Thesis is divided into two parts, theoritical and practical one. In the theoritical part an overview of the general anatomy of the knee joint and the biomechanics of the knee ligaments are presented. Also the mechanisms of the injury of Anterior Cruciate Ligament, the clinical examination that follows, the symptomes that correspond in this injury and the conservative therapeutic approach are discused. The second part contains a detailed description of the case study of the patient, the examination tests and the rehabilitation program I perforfed to the patient and also the evaluation of the results of the therapy. Key worlds: Physical Therapy, knee joint, Anterior Cruciate Ligament, rupture, conservative, skiing Dates of practice: 16/1/2012 - 1/2/2012 Location of practice: Ústřední vojenská nemocnice Praha 1200/1, 162 00 Praha
Handbook for quality in cultural Web sites: improving quality for citizens
No full textprinted and online versions, co-author with Giancarlo Buzzanca, David Dawson, Chiara De Vecchis, Mario Di Domenicantonio, Sara Di Giorgio, Isabelle Dujacquier, Fedora Filippi, Franca Garzotto, Maria Teresa Natale, Maria Pia Guermandi, Cary Karp, Emmanouil Karatzas, Sofia Karagiorgoudi, Oleg Missikoff, Maurizio Vittoria, Andrea Vituzz
Day lit density
No full textThesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2015.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Title as it appears in MIT Commencement Exercises program, June 5, 2015: Daylit Density : a simulation-based framework for performance-aware zoning and real estate development. Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 85-86).Population growth and related space constraints have led to a planning paradigm that promotes living and working in high-density urban areas. Increasing urban density, however, leads to a conflict between space-use efficiency and access to daylight. To manage this conflict and to ensure sufficient solar access, cities have traditionally relied on zoning guidelines that propose simple, two-dimensional geometric evaluation techniques. This practice seems antiquated in times when computer aided design tools enable architects to test designs before construction. Recent advances in building performance simulation software allow us to compute annual climate-based daylight performance metrics of urban environments accurately, in high spatial resolution and in a timely manner. Given that zoning requirements as well as massing design decisions at the urban planning level may make or break the long-term daylighting potential of a whole neighborhood, the adoption of these tools by zoning boards and planners seems particularly relevant. This manuscript therefore presents a simulation-based framework for formulating more nuanced prescriptive zoning rules, along with a performance-based approach for developers and planners interested in exploring innovative urban massing solutions. The framework is used to evaluate the daylighting performance of common and innovative urban block typologies in New York City. The performance of the investigated massing designs varies; in some cases the designs significantly outperform existing strategies, supporting urban densities that are twice as high as current zoning maxima. Findings are illustrated using a case study and compiled into a set of recommendations for zoning boards, planners and real estate developers towards more sustainable management of solar access at the urban scale.by Emmanouil Saratsis.S.M
SMART mobility via prediction, optimization and personalization
No full textIn this chapter, we present a methodological approach for Smart Mobility that integrates three key features: prediction, optimization, and personalization. They are integrated in such a way that when a travel menu is offered, predicted conditions are considered in the attributes of alternatives and optimized system-level policies are maintained. Similarly, user-level estimations and updates are used by prediction and optimization methods at the system-level in order to represent the population with most up-to-date behavioral estimates. Furthermore, a simulation-based evaluation methodology enables to validate the performance of prediction, optimization, and personalization before Smart Mobility is implemented in real-life. Two case studies are presented based on the proposed methodologies together with platforms that facilitate their application. Potential benefits of the proposed methodologies are evaluated which can be classified into user-level and system-level benefits. User-level benefits include consumer surplus, waiting times, etc., and system-level is concerned with congestion, throughput, system-wide travel time, etc. As there is normally a tradeoff between the individual decision-making and system-wide decision-making, Smart Mobility bridges them together with appropriate methodologies on each end. For example, for our Flexible Mobility on Demand case study, we observe 10%–20% reduction in volume-to-capacity ratio as a system-level benefit. Moreover, we see that the tradeoff between consumer surplus and operator profit can be managed with an appropriate objective function.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic
Correction: Allogeneic hematopoietic cell transplantation in patients with myeloid/lymphoid neoplasm with FGFR1-rearrangement: a study of the Chronic Malignancies Working Party of EBMT (Bone Marrow Transplantation, (2022), 57, 3, (416-422), 10.1038/s41409-021-01553-x)
No full textTwo members from that institution collaborated in our study but we did not choose the preferred one for the final version of the manuscript. The suggested coauthor is Dr Emmanouil Nikolousis (manos. [email protected]) in place of Shankara Paneesha (shankara. [email protected]). Both of them have agreed on this change. The original article has been corrected © The Author(s), under exclusive licence to Springer Nature Limited 2022
FSD-FS
No full textFSD-FS is a publicly-available database of human labelled sound events for few-shot learning. It spans across 143 classes obtained from the AudioSet Ontology and contains 43805 raw audio files collected from the FSD50K. FSD-FS is curated at the Centre for Digital Music, Queen Mary University of London.
Citation
If you use the FSD-FS dataset, please cite our paper and FSD50K.
@article{liang2022learning,
title={Learning from Taxonomy: Multi-label Few-Shot Classification for Everyday Sound Recognition},
author={Liang, Jinhua and Phan, Huy and Benetos, Emmanouil},
journal={arXiv preprint arXiv:2212.08952},
year={2022}
}
@ARTICLE{9645159, author={Fonseca, Eduardo and Favory, Xavier and Pons, Jordi and Font, Frederic and Serra, Xavier}, journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing}, title={FSD50K: An Open Dataset of Human-Labeled Sound Events}, year={2022}, volume={30}, number={}, pages={829-852}, doi={10.1109/TASLP.2021.3133208}}
About FSD-FS
FSD-FS is an open database for multi-label few-shot audio classification containing 143 classes drawn from the FSD50K. It also inherits the AudioSet Ontology. FSD-FS follows the ratio 7:2:1 to split classes into base, validation, and evaluation sets, so there are 98 classes in the base set, 30 classes in the validation set, and 15 classes in the evaluation set (More details can be found in our paper).
LICENSE
FSD-FS are released in Creative Commons (CC) licenses. Same as FSD50K, each clip has its own license as defined by the clip uploader in Freesound, some of them requiring attribution to their original authors and some forbidding further commercial reuse. For more details, ones can refer to the link.
FILES
FSD-FS are organised in the structure:
root
|
└─── dev_base
|
└─── dev_val
|
└─── eval
REFERENCES AND LINKS
[1] Gemmeke, Jort F., et al. "Audio set: An ontology and human-labeled dataset for audio events." 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2017. [paper] [link]
[2] Fonseca, Eduardo, et al. "Fsd50k: an open dataset of human-labeled sound events." IEEE/ACM Transactions on Audio, Speech, and Language Processing 30 (2021): 829-852. [paper] [code
MuChoMusic dataset
No full textMuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models
MuChoMusic is a benchmark designed to evaluate music understanding in multimodal language models focused on audio. It includes 1,187 multiple-choice questions validated by human annotators, based on 644 music tracks from two publicly available music datasets. These questions cover a wide variety of genres and assess knowledge and reasoning across several musical concepts and their cultural and functional contexts. The benchmark provides a holistic evaluation of five open-source models, revealing challenges such as over-reliance on the language modality and highlighting the need for better multimodal integration.
Note on Audio Files
This dataset comes without audio files. The audio files can be downloaded from two datasets: SongDescriberDataset (SDD) and MusicCaps. Please see the code repository for more information on how to download the audio.
Citation
If you use this dataset, please cite our paper:
@inproceedings{weck2024muchomusic,
title={MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models},
author={Weck, Benno and Manco, Ilaria and Benetos, Emmanouil and Quinton, Elio and Fazekas, György and Bogdanov, Dmitry},
booktitle = {Proceedings of the 25th International Society for Music Information Retrieval Conference (ISMIR)},
year={2024}
}
Weck B, Manco I, Benetos E, Quinton E, Fazekas G, Bogdanov D. MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models. In: Kaneshiro B, Mysore G, Nieto O, Donahue C, Huang CZA, Lee JH, McFee B, McCallum M, editors. Proceedings of the 25th International Society for Music Information Retrieval Conference (ISMIR2024); 2024 November 10-14; San Francisco, USA
Error Correction for Wave Modelling
No full textInstallation and maintenance strategies regarding offshore wind farm operations involve extensive logistics, since the main focus is the right temporal and spatial placement of personnel and equipment, while taking into account forecasted meteorological and hydrodynamic conditions. In order for these operations to be successful weather windows characterized by certain permissive wave, wind and current conditions is of enormous importance, whereas unforeseen events result in high cost and risk in terms of safety.For that purpose, Deltares created Meteo Dashboard, an integrated software system that collects, stores, computes and presents measured and forecasted meteorological and hydrodynamic data for decision making of maintenance or installation activities in an offshore wind farm. The wind speed, as well as the air and water temperatures, result from a meteorological model and serve as an input for the numerical modelling (e.g. SWAN or Delft3D) of waves, water levels and current related parameters. To account for the inherited uncertainty, several error modelling techniques, such as Artificial Neural Networks (ANN), Copulas, Stochastic Interpolation (SI), ARMA models, and Linear Regression (REG), already run operational on Meteo Dashboard and can be implemented in order for the numerical model forecasts to be corrected. A number of the aforementioned techniques require training using historical or present time data, while others can be incorporated forthwith.In this research, a fully automated ARIMA model and different kinds of Bayesian Network (BN) models are incorporated in order to enhance the accuracy of the significant wave height (Hs) predictions even further. Both techniques are implemented using packages provided by the free software environment of R, namely the bnlearn and forecast. The implemented BN models differ in terms of training and structure, and provide overall the most satisfying accuracy in comparison to the rest of the error correction techniques, when tested with data retrieved from stations deployed in the Irish Sea (adjacent to the Gwynt-y-Mor and Rhyl Flats offshore wind farms) corresponding to the whole year of 2017 (from January 2017 – to January 2018).Supplementary, it is also shown that the BN models illustrate even more advantages when compared to the rest of the error correction techniques, since they provide information about the incorporated variables dependence relationship through their structures, while producing estimates for the underlying uncertainty of the phenomenon, by means of 95% confidence intervals extracted by the significant wave height (Hs) conditional distribution.Finally, all error correction models are tested in operational (online) mode, with real-time data from the aforementioned locations, with the newly implemented BN models producing results of enhanced accuracy, even in the absence of measurement
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