4,130 research outputs found
Computer Vision and Image Processing in Structural Health Monitoring: Overview of Recent Applications
No full textStructural deterioration is a primary long-term concern resulting from material wear and tear, events, solicitations, and disasters that can progressively compromise the integrity of a cement- based structure until it suddenly collapses, becoming a potential and latent danger to the public. For many years, manual visual inspection has been the only viable structural health monitoring (SHM) solution. Technological advances have led to the development of sensors and devices suitable for the early detection of changes in structures and materials using automated or semi-automated approaches. Recently, solutions based on computer vision, imaging, and video signal analysis have gained momentum in SHM due to increased processing and storage performance, the ability to easily monitor inaccessible areas (e.g., through drones and robots), and recent progress in artificial intelligence fueling automated recognition and classification processes. This paper summarizes the most recent studies (2018–2022) that have proposed solutions for the SHM of infrastructures based on optical devices, computer vision, and image processing approaches. The preliminary analysis revealed an initial subdivision into two macro-categories: studies that implemented vision systems and studies that accessed image datasets. Each study was then analyzed in more detail to present a qualitative description related to the target structures, type of monitoring, instrumentation and data source, methodological approach, and main results, thus providing a more comprehensive overview of the recent applications in SHM and facilitating comparisons between the studies
Claudia Rankine: An Evening with Claudia Rankine
No full textAn initiative of the National Endowment for the Arts in partnership with Arts Midwest, the NEA Big Read broadens our understanding of our world, our communities, and ourselves through the joy of sharing a good book. For NEA Big Read: Hampton Roads, that book is Citizen: An American Lyric.
NEA Big Read: Hampton Roads, the President\u27s Lecture Series, and the President\u27s Task Force on Inclusive Excellence invite you to a powerful evening with Claudia Rankine, the book\u27s author, hosted by Tim Seibles, Poet Laureate for the Commonwealth of Virginia, and opening with readings by local youth poets.
Claudia Rankine has written five collections of poetry, including Citizen: An American Lyric, which was selected for the National Endowment for the Arts\u27 Big Read, and two plays. She also has participated in several video collaborations and edited anthologies including The Racial Imaginary: Writers on Race in the Life of the Mind.
Rankine has received fellowships from the MacArthur and Guggenheim foundations. Citizen won several honors, including the National Book Critics Circle Award for Poetry, the PEN Open Book Award and the NAACP Image Award. Citizen also was the only poetry book to be a New York Times nonfiction bestseller. She is the Frederick Iseman Professor of Poetry at Yale University and chancellor of the Academy of American Poets
Portrait of Claudia Lynn Pittman.
No full textHandwritten inscription: Claudia Lynn Pittman, 20 yrs old, Hattiesburg.https://egrove.olemiss.edu/joephoto_c/1129/thumbnail.jp
Homonoia - Concorda - Sammanasya
No full textAnalysis of the divine figures of Homónoia in the Greek pantheon, Concordia in the Roman pantheon, and Sammanasya in the Vedic pantheon. Claudia Santi is the author of Homónoia; Andrzej Gillmeister is the author of Concordia; Antonio Salvati is the author of Sammanasya. As regards Homónoia, the origin of this personified abstraction seems to be traced back to the political debate of Athens in the last 5th century. Maybe it was created by Antiphon as opposed to stásis, both in the meaning of ‘psychic conflict’ and ‘internal political dissensions, civil war’
Claudia Emerson, 31st Annual ODU Literary Festival
No full textClaudia Emerson was awarded the 2006 Pulitzer Prize in Poetry for her book Late Wife: Poems (LSU Press, 2005). She is also the author of the poetry collections Pharaoh, Pharaoh, and Pinion: An Elegy; all volumes are published in Dave Smith’s Southern Messenger Poets series. Her poems have appeared in Poetry, Southern Review, Shenandoah, TriQuarterly, New England Review and other journals. Emerson is the recipient of a Witter Bynner Fellowship from the Library of Congress and fellowships from the National Endowment for the Arts and the Virginia Commission for the Arts. She is an associate professor of English at the University of Mary Washington in Fredericksburg, Va
Electrodermal Activity in the Evaluation of Engagement for Telemedicine Applications
No full textElectrodermal Activity (EDA) is a broadly-investigated physiological signal, whose behaviour is connected to nervous system arousal. Such system, indeed, influences the properties of the skin, producing a measurable electrical signal. Among the possible applications of such measurements, several studies have correlated the signal behaviour to engagement during mental and physical tasks, and the subjects' response to specific multimodal stimuli. Also due to the possibility of performing remote assessment and rehabilitation, telemedicine applications are gaining ground in the healthcare system. However, acceptance and engagement, hence continuity of usage, still remain significant obstacles. Therefore, it would be highly beneficial to verify, through objective measures, if these solutions are actually providing a sufficient stimulation to properly engage subjects while playing. This study investigates the possibility of employing EDA in the automatic recognition of different levels of user engagement, while playing a motor-cognitive exergame specifically designed for this purpose. Preliminary results, obtained on a cohort of 25 healthy subjects, seem to confirm that features extracted from EDA analysis are significant and able to train supervised classifiers, achieving high accuracy and precision in the engagement recognition problem
Enhancing Model Generalizability In Parkinson's Disease Automatic Assessment: A Semi-Supervised Approach Across Independent Experiments
No full textMachine learning in Parkinson's disease assessment uses data from clinically-coded movements, such as finger tapping, to objectively measure motor impairment. Video-based models showed promise in several experiments, but the lack of a unified test benchmark hinders proving generalizability. Additionally, new telemedicine systems may easily collect large amounts of unsupervised data, while obtaining ground truth labels for supervised learning remains time-consuming and requires specialized clinicians. This study explores semi-supervised learning to enhance the generalizability of a Light Gradient Boosting model for video-based finger tapping staging, while reducing its need for supervised data labelling. Specifically, this work employs the Self-training schema in two trials using openly-available finger tapping datasets from three independent experiments. This method significantly improves model performance across various metrics, achieving notable accuracy gains (e.g., from 87.62% to 92.05%) when tested on unseen data from a different experiment. Semi-supervision proves valuable when limited labelled data (less than 10%) from the test distribution are available during training
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