Unsupervised detection and localization of structural textures using projection profiles

Cataloged from PDF version of article.The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images. First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes.(C)2010 Elsevier Ltd. All rights reserved

Automatic detection and segmentation of orchards using very high-resolution imagery

Cataloged from PDF version of article.Spectral information alone is often not sufficient to distinguish certain terrain classes such as permanent crops like orchards, vineyards, and olive groves from other types of vegetation. However, instances of these classes possess distinctive spatial structures that can be observable in detail in very high spatial resolution images. This paper proposes a novel unsupervised algorithm for the detection and segmentation of orchards. The detection step uses a texture model that is based on the idea that textures are made up of primitives (trees) appearing in a near-regular repetitive arrangement (planting patterns). The algorithm starts with the enhancement of potential tree locations by using multi-granularity isotropic filters. Then, the regularity of the planting patterns is quantified using projection profiles of the filter responses at multiple orientations. The result is a regularity score at each pixel for each granularity and orientation. Finally, the segmentation step iteratively merges neighboring pixels and regions belonging to similar planting patterns according to the similarities of their regularity scores and obtains the boundaries of individual orchards along with estimates of their granularities and orientations. Extensive experiments using Ikonos and QuickBird imagery as well as images taken from Google Earth show that the proposed algorithm provides good localization of the target objects even when no sharp boundaries exist in the image data. © 2012 IEEE

Unsupervised detection and localization of structural textures using projection profiles

The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images. First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes. © 2010 Elsevier Ltd. All rights reserved

Determinants of Sovereign Bond Yield Spreads in the EMU. An Optimal Currency Area Perspective

In the light of the recent financial crisis, we take a panel cointegration approach that allows for structural breaks to the analysis of the determinants of sovereign bond yield spreads in nine economies of the European Monetary Union. While we find evidence for a level break in the cointegrating relationship, we do not find empirical support for a regime shift and hence for a change in the pricing of the determinants of sovereign spreads. Moreover, results show that (i) fiscal imbalances (namely expected government debt-to-GDP differentials) are the main long-run drivers of sovereign spreads; (ii) liquidity risks and cumulated inflation differentials have non-negligible weights; but (iii) all conclusions are ultimately connected to whether or not the sample of countries is composed of members of an Optimal Currency Area (OCA). In particular, we establish (i) that results are overall driven by those countries not passing the OCA test; and (ii) that investors closely monitor and severely punish the deterioration of expected debt positions of those economies exhibiting significant gaps in competitiveness

Catalysis by Dehydroepiandrosterone Sulfotransferase

ABSTRACT: Cholestero

Semantic argument frequency-based Multi-Document Summarization

Semantic Role Labeling (SRL) aims to identify the constituents of a sentence, together with their roles with respect to the sentence predicates. In this paper, we introduce and assess the idea of using SRL on generic Multi-Document Summarization (MDS). We score sentences according to their inclusion of frequent semantic phrases and form the summary using the top-scored sentences. We compare this method with a term-based sentence scoring approach to investigate the effects of using semantic units instead of single words for sentence scoring. We also integrate our scoring metric as an auxiliary feature to a cutting edge summarizer with the intention of examining its effects on the performance. The experiments using datasets from the Document Understanding Conference (DUC) 2004 show that the SRL-based summarization outperforms the term-based approach as well as most of the DUC participants. © 2009 IEEE

Cardamine Occulta: A New Weed and Alien Plant Species in Banana Production Greenhouses in Türkiye

Banana is a cash crop in Mediterranean Region of Türkiye, which is grown mainly in greenhouses and open fields. In weed flora surveys carried out in 2021 and 2022, an Eastern Asian plant, Cardamine occulta Hornem. (Brassicaceae), was determined first time in 60% of banana greenhouses in Türkiye. The species had been recorded in Europe in the second half of the 20th century, and then spread especially in urban areas of many European countries and Mediterranean Basin, which implies many habitats in Türkiye under the threat of C. occulta . The main diagnostic morphological features and an identification key are presented in comparison with those for allied C. flexuosa With. and C. hirsuta L. An eradication program is suggested because it is not scattered but limited with banana greenhouses in Türkiye

Developing research skills in medical students online using an active research study

Background: Developing research skills and scholarship are key components of medical education. The COVID-19 pandemic necessitated that all teaching be delivered online. We introduced an approach to small group teaching in the academic year 2020–2021 online which involved students in an active (ongoing) research study to develop their research skills. Methods: We acquired student feedback to evaluate their perspectives quantitatively on development of research and scholarship skills, teaching content and format, and tutor performance using this teaching approach. In addition, we captured free text responses from both students and tutors on the positives and negatives of our course, and their suggested improvements. We also compared summative assessment marks for the online/active research course (2020–2021) with those obtained from previous (2017–2019) and subsequent (2021–2023) teaching sessions. Results: Students were largely positive about most aspects of the online course utilising an active research study (n = 13). Students agreed that they were able to acquire research skills, particularly related to data analysis, transferable skills, and giving scientific presentations. A one-way ANOVA revealed no significant difference for assessment marks across all five teaching years (two years prior and two years following the online/active research course), indicating that the course achieved the learning outcomes. Students enjoyed the convenience of online teaching and the availability of course resources, but least liked the lack of in-person interaction and laboratory training. Tutors enjoyed the collaborative aspects of online teaching, but least liked the lack of face-to-face interactions with students. Conclusions: Our study demonstrates that delivering online teaching which involves students in active research engages and motivates them to develop their research and scholarship skills. We recommend that educators consider incorporating a current research study in their undergraduate courses as this can enhance the student learning experience as well as the research project itself