632 research outputs found
Lesbian Radio, August 15 2012
No full textHost Deb Gallagher talks again with Leela Sinha, author of You’re Not Too Much: Intensive Lies in an Expansive World, about the fundamentals of good communication.https://digitalcommons.usm.maine.edu/wmpg_lesbianradio/1002/thumbnail.jp
Lesbian Radio, June 20 2012
No full textHost Deb Gallagher talks with Leela Sinha, author of You’re Not Too Much: Intensive Lies in an Expansive World, about the fundamentals of good communication.https://digitalcommons.usm.maine.edu/wmpg_lesbianradio/1001/thumbnail.jp
Face Recognition Time Reduction Based on Partitioned Faces without Compromising Accuracy and a Review of state-of-the-art Face Recognition Approaches
No full textHerbalist Deb Soule, author of The Roots of Healing: A Woman\u27s Book of Herbs,
No full textHerbalist Deb Soule, author of The Roots of Healing: A Woman\u27s Book of Herbs, founded Avena Botanicals of Rockland ten years ago. Avena Botanicals, perhaps the largest herbal apothecary in the Northeast, grows or gathers around 60 percent of the raw plant materials used in producing herbal extracts, oils, salves and teas. The Shaker Community of Sabbath Day Lake has an herbal tradition that is 200 years old, and the herb department is the Shakers\u27 largest industry. Pol Hermes of Dayton, Gail Edwards of Athens and Betty Chase of Falmouth are other Mainers who use herbs. Details
Increasing fuel resilience to survive Cascadia
No full textprepared by Oregon Seismic Safety Policy Advisory Commission, Working Group on CEI Hub Mitigation Strategies ; production writer: Laura Hall ; production assistant: Deb Schueller.Title from PDF cover (viewed on January 15, 2020)."OSSPAC Publication Number 19-01."This archived document is maintained by the State Library of Oregon as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Includes bibliographical references (pages 31-32).Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Graduate medical education in 2030 (Podcast)
No full textIn the June issue of the Journal of Graduate Medical Education, an editorial explores what graduate medical education will look like in 2030. In this episode, JGME deputy editor, Deb Simpson, speaks with physician, educator, and author, James Woolliscroft, about the future of graduate medical education, especially in the wake of the COVID-19 pandemic. They discuss the roles of the DIO, program director, and faculty as well as the impact of technology on the medical education system
Graduate medical education in 2030 (Podcast)
No full textIn the June issue of the Journal of Graduate Medical Education, an editorial explores what graduate medical education will look like in 2030. In this episode, JGME deputy editor, Deb Simpson, speaks with physician, educator, and author, James Woolliscroft, about the future of graduate medical education, especially in the wake of the COVID-19 pandemic. They discuss the roles of the DIO, program director, and faculty as well as the impact of technology on the medical education system
Deep Learning and Data Balancing Approaches in Mining Hospital Surveillance Data
No full textA number of classifier models on hospital surveillance data to classify admitted patients according to their critical conditions with an emphasis to deep learning paradigms, namely convolutional neural network, were used in this research. Three class labels were used to distinguish the criticality of the admitted 25,261 patients. The authors have set forth two distinct approaches to address the unbalance nature of data. They used multilayer perceptron (MLP), convolutional neural network (CNN), and multinomial logistic regression classifications and finally compared the performance of our models with the models developed by Firoze, Hasan and Rahman (2013). After comparison, the authors show that one of the models, including convolutional neural network based on deep learning, surpasses most models in terms of classification performance in contingent with training times and epochs. The trade-off is computational power for which—to achieve optimal accuracy—multiple CUDA cores are necessary. The authors achieved stable improvement of classification for their model using CNN. </jats:p
An algorithmic approach to estimate cognitive aesthetics of images relative to ground truth of human psychology through a large user study
No full textThis research introduces a learning model that estimates the cognitive perception of aesthetics. Taking psychology into account, this bridges the gap between human and machine. The goal is to build a machine-learning model that can estimate beauty in images perceived by human eyes. We have summand our research [Firoze, A., Osman, T., Psyche, S. S., & Rahman, R. M. (2018). Scoring photographic rule of thirds in a large MIRFLICKR dataset: A showdown between machine perception and human perception of image aesthetics. Asian Conference on Intelligent Information and Database Systems (pp. 466–475), Springer; Osman, T., Psyche, S. S., Deb, T., Firoze, A., & Rahman, R. M. (2018). Differential color harmony: A robust approach for extracting Harmonic Color features and perceive aesthetics in a large dataset. International Conference on Big Data and Cloud Computing, Springer] together with the idea of humans’ personal preferences and achieved higher than state of the art performances. An extensive user study (374 participants) has been conducted to support claims. Several photographical compositional metrics have been used. Colour gradient, rule of thirds and human subject’s psychology has been picked as features. The consideration of user’s perspective or psychology is one of the key contributions of this research
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