1,238 research outputs found
Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics
It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM “Schwingungen in rotierenden Maschinen”. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name “European Conference on Rotordynamics”. This new international profile has also been
emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations
Tradition and Innovation in Construction Project Management
This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings
2023 GREAT Day Program
SUNY Geneseo’s Seventeenth Annual GREAT Day. Geneseo Recognizing Excellence, Achievement & Talent Day is a college-wide symposium celebrating the creative and scholarly endeavors of our students. http://www.geneseo.edu/great_dayhttps://knightscholar.geneseo.edu/program-2007/1017/thumbnail.jp
Proceedings of the 8th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2023)
This volume gathers the papers presented at the Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCASE2023), Tampere, Finland, during 21–22 September 2023
Evaluation of automated organ segmentation for total-body PET-CT
The ability to diagnose rapidly and accurately and treat patients is substantially facilitated by medical images. Radiologists' visual assessment of medical images is crucial to their study. Segmenting images for diagnostic purposes is a crucial step in the medical imaging process. The purpose of medical image segmentation is to locate and isolate ‘Regions of Interest’ (ROI) within a medical image. Several medical uses rely on this procedure, including diagnosis, patient management, and medical study. Medical image segmentation has applications beyond just diagnosis and treatment planning. Quantitative information from medical images can be extracted by image segmentation and employed in the research of new diagnostic and treatment procedures. In addition, image segmentation is a critical procedure in several programs for image processing, including image fusion and registration. In order to construct a single, high-resolution, high-contrast image of an item or organ from several images, a process called "image registration" is used. A more complete picture of the patient's anatomy can be obtained through image fusion, which entails integrating numerous images from different modalities such as computed tomography (CT) and Magnetic resonance imaging (MRI). Once images are obtained using imaging technologies, they go through post-processing procedures before being analyzed. One of the primary and essential steps in post-processing is image segmentation, which involves dividing the images into parts and utilizing only the relevant sections for analysis. This project explores various imaging technologies and tools that can be utilized for image segmentation. Many open-source imaging tools are available for segmenting medical images across various applications. The objective of this study is to use the Jaccard index to evaluate the degree of similarity between the segmentations produced by various medical image visualization and analysis programs
Monitoring fatigue and drowsiness in motor vehicle occupants using electrocardiogram and heart rate - A systematic review
Introdução: A fadiga é um estado complexo que pode resultar em diminuição da vigilância, frequentemente acompanhada de sonolência. A fadiga durante a condução contribui significativamente para acidentes de trânsito em todo o mundo, destacando-se a necessidade de técnicas de monitorização eficazes. Existem várias tecnologias para aumentar a segurança do condutor e reduzir os riscos de acidentes, como sistemas de deteção de fadiga que podem alertar os condutores à medida que a sonolência se instala. Em particular, a análise dos padrões de frequência cardíaca pode oferecer informações valiosas sobre a condição fisiológica e o nível de vigilância do condutor, permitindo-lhe compreender os seus níveis de fadiga. Esta revisão tem como objetivo estabelecer o estado atual das estratégias de monitorização para ocupantes de veículos, com foco específico na avaliação da fadiga pela frequência cardíaca e variabilidade da frequência cardíaca.
Métodos: Realizamos uma pesquisa sistemática da literatura nas bases de dados Web of Science, SCOPUS e Pubmed, utilizando os termos veículo, condutor, monitoração fisiológica, fadiga, sono, eletrocardiograma, frequência cardíaca e variabilidade da frequência cardíaca. Examinamos artigos publicados entre 1 de janeiro de 2018 e 31 de janeiro de 2023.
Resultados: Um total de 371 artigos foram identificados, dos quais 71 foram incluídos neste estudo. Entre os artigos incluídos, 57 utilizam o eletrocardiograma (ECG) como sinal adquirido para medir a frequência cardíaca, sendo que a maioria das leituras de ECG foi obtida através de sensores de contacto (n=41), seguidos por sensores vestíveis não invasivos (n=11). Relativamente à validação, 23 artigos não mencionam qualquer tipo de validação, enquanto a maioria se baseia em avaliações subjetivas de fadiga relatadas pelos próprios participantes (n=27) e avaliações feitas por observadores com base em vídeos (n=11). Dos artigos incluídos, apenas 14 englobam um sistema de estimativa de fadiga e sonolência. Alguns relatam um desempenho satisfatórios, no entanto, o tamanho reduzido da amostra limita a abrangência de quaisquer conclusões.
Conclusão: Esta revisão destaca o potencial da análise da frequência cardíaca e da instrumentação não invasiva para a monitorização contínua do estado do condutor e deteção de sonolência. Uma das principais questões é a falta de métodos suficientes de validação e estimativa para a fadiga, o que contribui para a insuficiência dos métodos na criação de sistemas de alarme proativos. Esta área apresenta grandes perspetivas, mas ainda está longe de ser implementada de forma fiável.Background: Fatigue is a complex state that can result in decreased alertness, often accompanied by drowsiness. Driving fatigue has become a significant contributor to traffic accidents globally, highlighting the need for effective monitoring techniques. Various technologies exist to enhance driver safety and minimize accident risks, such as fatigue detection systems that can alert drivers as drowsiness sets in. In particular, measuring heart rate patterns may offer valuable insights into the occupant's physiological condition and level of alertness, and may allow them to understand their fatigue levels. This review aims to establish the current state of the art of monitoring strategies for vehicle occupants, specifically focusing on fatigue assessed by heart rate and heart rate variability.
Methods: We performed a systematic literature search in the databases of Web Of Science, SCOPUS and Pubmed, using the terms vehicle, driver, physiologic monitoring, fatigue, sleep, electrocardiogram, heart rate and heart rate variability. We examine articles published between 1st of january 2018 and 31st of January 2023.
Results: A total of 371 papers were identified from which 71 articles were included in this study. Among the included papers, 57 utilized electrocardiogram (ECG) as the acquired signal for heart rate (HR) measures, with most ECG readings obtained through contact sensors (n=41), followed by non-intrusive wearable sensors (n=11). Regarding validation, 23 papers do not report validation, while the majority rely on subjective self-reported fatigue ratings (n=27) and video-based observer ratings(n=11). From the included papers, only 14 comprise a fatigue and drowsiness estimation system. Some report acceptable performances, but reduced sample size limits the reach of any conclusions.
Conclusions: This review highlights the potential of HR analysis and non-intrusive instrumentation for continuous monitoring of driver's status and detecting sleepiness. One major issue is the lack of sufficient validation and estimation methods for fatigue, contributing to the insufficiency of methods in providing proactive alarm systems. This area shows great promise but is still far from being reliably implemented
Eddy current defect response analysis using sum of Gaussian methods
This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics
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