1,142 research outputs found
Geologic map of the Dufur area, Wasco County, Oregon
No full textReport -- Plate 1 -- Plate 2 -- Plate 3.Jason D. McClaughry, Heather H. Herinckx, Clark A. Niewendorp, Carlie J.M. Azzopardi, and Joshua A. Hackett.Title from PDF cover (viewed on May 19, 2021).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.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Michel Azzopardi, Vingt ans dans un tunnel, le cinéma ouest-allemand de 1946 à 1986, 1987
No full textHugues Philippe d'. Michel Azzopardi, Vingt ans dans un tunnel, le cinéma ouest-allemand de 1946 à 1986, 1987. In: 1895, revue d'histoire du cinéma, n°3, 1987. p. 27
Coauthor prediction for junior researchers
No full textResearch collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag
Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models
No full textThe remarkable abilities of the primate visual cortex have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 -> V4 -> TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. A S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms
Using the quantum probability ranking principle to rank interdependent documents
No full textA known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements
Hierarchical auxetic mechanical metamaterials
No full textThis work has been funded through the Malta Council for Science and Technology through
the R&I-2011-024 Project (Smart Stents) and R&I-2012-061 (SMESH).Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.peer-reviewe
Geologic map of the Athena 7.5′ quadrangle, Umatilla County, Oregon
No full textPlate 1 -- Plate 2.by Jason D. McClaughry and Carlie J.M. Azzopardi; cartography by Jon J. Franczyk and geodatabase by Carlie J.M. Azzopardi.Relief shown by contours and hill shading.Includes detailed geologic map, bedrock geologic map, location maps, time rock chart, geologic cross section, text, and references.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.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Maternità
No full textĠabra ta’ poeżiji u proża li tinkludi: O tempora! O mores! ta’ Wallace Gulia – Naf b’kollox ta’ Ivo Muscat-Azzopardi – Lit-tabib Ġużè Galea, M. B. E., M. D., D. P. H., ta’ Vincent Ungaro – Il-għolliq ta’ A. Buttigieg – Lill-Kav. Dr. Ġużè Galea, M. B. E., M. D., D. P. H. ta’ Karmenu Mallia – “Vestru” ta’ J. E. Busuttil – Maternità ta’ Ġużè Chetcuti.N/
Trainable COSFIRE filters for vessel delineation with application to retinal images
No full textRetinal imaging provides a non-invasive opportunity for the diagnosis of several medical pathologies. The automatic segmentation of the vessel tree is an important pre-processing step which facilitates subsequent automatic processes that contribute to such diagnosis. We introduce a novel method for the automatic segmentation of vessel trees in retinal fundus images. We propose a filter that selectively responds to vessels and that we call B-COSFIRE with B standing for bar which is an abstraction for a vessel. It is based on the existing COSFIRE (Combination Of Shifted Filter Responses) approach. A B-COSFIRE filter achieves orientation selectivity by computing the weighted geometric mean of the output of a pool of Difference-of-Gaussians filters, whose supports are aligned in a collinear manner. It achieves rotation invariance efficiently by simple shifting operations. The proposed filter is versatile as its selectivity is determined from any given vessel-like prototype pattern in an automatic configuration process. We configure two B-COSFIRE filters, namely symmetric and asymmetric, that are selective for bars and bar-endings, respectively. We achieve vessel segmentation by summing up the responses of the two rotation-invariant B-COSFIRE filters followed by thresholding. The results that we achieve on three publicly available data sets (DRIVE: Se = 0.7655, Sp = 0.9704; STARE: Se = 0.7716, Sp = 0.9701; CHASE_DB1: Se = 0.7585, Sp = 0.9587) are higher than many of the state-of-the-art methods. The proposed segmentation approach is also very efficient with a time complexity that is significantly lower than existing methods.peer-reviewe
- …
