1,721,311 research outputs found
Bohannon, M. Leo, 1961 April 3
No full textDear Denny: Thanks for the copy of the St. Louis Story Retold. I had no idea you were still in Omaha. I thought that you, like most of the young fellows, had long since migrated to other lands. However I did know well of your interest in the community and I know you must be making a very worthwhile contribution to human relations in Omaha. Father John Markoe also sent me a copy of the St. Louis Story Retold so I have two copies. I am happy that I am remembered by my old friends. Best personal regards to you. Sincerely yours, Leo Bohanon M. Leo Bohanon, Executive Director
Carr, L M (Leo Mannix), VX48402
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/376092Surname: CARR
Given Name(s) or Initials: L M (LEO MANNIX)
Military Service Number or Last Known Location: VX48402
Missing, Wounded and Prisoner of War Enquiry Card Index Number: 42439188655
Item: [2016.0049.08400] "Carr, L M (Leo Mannix), VX48402
Cain, L M (Leo Moss), NX71926
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/375387Surname: CAIN
Given Name(s) or Initials: L M (LEO MOSS)
Military Service Number or Last Known Location: NX71926
Missing, Wounded and Prisoner of War Enquiry Card Index Number: 41679188088
Item: [2016.0049.07695] "Cain, L M (Leo Moss), NX71926
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Capitalizing on self-supervision and pre-trained models in computer vision
No full textThis thesis addresses the overarching challenge of advancing computer vision tasks under the constraints of limited labeled data and the imperative to capitalize on pre-existing knowledge encoded in pre-trained models. By exploring three distinct computer vision tasks - classification, regression, and segmentation - this work presents diverse frameworks aimed at transcending the conventional boundaries imposed by data scarcity and task-specific methodologies. The first focus lies on Unsupervised Domain Adaptation (UDA) in visual recognition, a critical endeavor in bridging disparate visual domains for robust real-world performance. Existing approaches in UDA typically necessitate manual adaptation to specific backbone architectures, hindering adaptability over time as methods become outdated with evolving architectures. To circumvent this limitation, this thesis proposes a novel approach termed Adversarial Branch Architecture Search for UDA (ABAS). ABAS addresses the lack of target labels by employing a data-driven ensemble approach for model selection and explores auxiliary adversarial branches to drive domain alignment. Extensive validation on standard visual recognition datasets demonstrates ABAS's efficacy in enhancing modern UDA techniques, robustly yielding superior performances across diverse domains. In the realm of regression tasks, the thesis delves into collaborative human pose forecasting, an understudied domain with the potential for improved performance through exploiting the correlated motion patterns of interacting individuals. By revisiting prevalent single-person practices and tailoring them to the collaborative setting, significant advancements are achieved. Notably, the integration of frequency input representations, space-time separable interaction encodings, and fully-learnable interaction adjacencies into a Graph Convolutional Network (GCN) framework showcases promising results. Furthermore, a novel initialization procedure for spatial interaction parameters enhances both performance and stability, culminating in a substantial performance boost over state-of-the-art methods on benchmark datasets. Lastly, the thesis tackles semantic segmentation in autonomous driving scenarios, leveraging the unique capabilities of event cameras for low-latency operation in challenging lighting conditions. We introduce OVOSE, the first open-vocabulary semantic segmentation approach explicitly tailored for event-based data. OVOSE leverages knowledge distillation from pre-trained image-based models and synthetic event data to enhance segmentation performance. Additionally, we propose a novel dissimilarity network to recalibrate mask loss, mitigating the effects of sub-optimal reconstructions and enabling precise fine-tuning of the segmentation model. Through this novel approach, OVOSE demonstrates superior performance in dynamic environments, outperforming existing conventional image-based models and state-of-the-art methods in unsupervised domain adaptation for event-based semantic segmentation. In summary, this thesis presents a holistic approach to computer vision tasks, unifying disparate methodologies under the common goal of leveraging pre-trained models and limited labels to achieve superior performance across diverse domains. By addressing specific challenges within classification, regression, and segmentation tasks, the proposed frameworks contributes towards advancing the frontier of computer vision in real-world applications
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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