1,720,953 research outputs found
Post-disaster structural damage assessment based on semantic segmentation using remote sensing images
No full textDoğal afetler sonrası yapıların çatı, cephe ve bina içi hasar görüntüleri üzerinden hasar bilgisini çıkarmak için hava görüntüleri ve bina içi görüntülerin entegrasyonundan faydalanmak, uzaktan algılama ile hasar tespitinde en etkili ve güvenilir yöntem olacaktır. Bina içi hasar tespitinde yapıların taşıyıcı elemanları üzerinden inceleme yapılmakta olup, bina dışından yapılacak incelemede cephe ve çatı incelenebilmektedir. Bu tezin birinci çalışmasında, betonarme yapıların deprem sonrası hasar tespiti ve çatlak segmentasyonu amacıyla geleneksel makine öğrenimi yöntemlerinin sınırlamalarını aşmak üzere geliştirilen derin öğrenme tabanlı segmentasyon yaklaşımları ele alınmıştır. Beton yüzeylerindeki çatlakların piksel düzeyinde tespiti amacıyla önerilen DeepLabV3+ tabanlı semantik segmentasyon mimarisi kapsamında, kodlayıcı blokta kullanılan farklı ön eğitimli omurga mimarilerinin performansları karşılaştırmalı olarak analiz edilmiştir. Söz konusu mimarilerin, düşük ve yüksek seviyeli özellik çıkarımı üzerindeki etkinliklerini değerlendirmek üzere DeepCrack ve CrackForest adlı açık erişimli veri setleri kullanılmıştır. Gerçekleştirilen deneysel çalışmalar sonucunda, MobileNetV2 mimarisinin hem parametre verimliliği hem de segmentasyon doğruluğu açısından diğer omurga yapılarından üstün performans sergilediği tespit edilmiştir. İkinci çalışma, doğal afetler sonrası yapı hasar tespiti amacıyla geliştirilen derin öğrenme tabanlı semantik segmentasyon modellerinin doğruluk, genelleme kabiliyeti ve hesaplama verimliliği açısından kapsamlı bir analizi sunulmuştur. Çalışma kapsamında, özgün hazırlanan Kahramanmaraş depremi veri seti ile birlikte Joplin Kasırgası ve xBD'ye ait yüksek çözünürlüklü drone ve uydu görüntülerinden oluşan veri kümeleri kullanılarak bina yıkım derecelerinin tespiti hedeflenmiştir. DeepLabV3+ segmentasyon mimarisi farklı omurga (backbone) ağları ile yapılandırılarak değerlendirilmiştir. Ayrıca, bina bazlı sınıflandırma için Joplin Kasırgasına ait afet öncesi görüntülerden çıkarılan poligon sınırları ile segmentasyon çıktıları birleştirilerek, bina düzeyinde hasar durumu belirlenmiştir. Deneysel sonuçlar, ResNet50 ve Xception mimarilerinin genel segmentasyon doğruluğu açısından en başarılı modeller olduğunu, buna karşılık MobileNetV2'nin daha az hesaplama maliyetiyle özellikle hızlı ve hafif uygulamalarda avantaj sağladığını göstermektedir. Öte yandan, sınıf dengesizliği ve karmaşık enkaz yapısı nedeniyle tüm modellerin yıkılmış binaların tespitinde zorluk yaşadığı, bu durumdan en çok etkilenen modellerin daha düşük katman derinliğine sahip yapılar olduğu gözlemlenmiştir. Bu çalışma, afet sonrası hızlı ve doğru hasar değerlendirmesi için derin öğrenme tabanlı bir çerçeve sunmaktadır.In the aftermath of natural disasters, integrating aerial imagery with interior building images is considered one of the most effective and reliable methods for remote sensing-based damage assessment, as it enables the extraction of structural damage information from roof, façade and interior views. While interior damage analysis focuses on inspecting structural elements, exterior assessments are typically limited to roofs and façades. The first part of this dissertation addresses deep learning-based semantic segmentation approaches developed to overcome the limitations of conventional machine learning techniques in post-earthquake damage detection and crack segmentation in reinforced concrete structures. Specifically, a DeepLabV3+ based semantic segmentation architecture was proposed for pixel-level detection of surface cracks in concrete. Within this framework, the performance of various pre-trained backbone architectures was comparatively analyzed in the encoder block. To evaluate the effectiveness of low and high-level feature extraction capabilities of these architectures, publicly available datasets, namely DeepCrack and CrackForest, were employed. experimental results demonstrated that the MobileNetV2 model outperformed the others in terms of both parameter efficiency and segmentation accuracy. The second part of this study presents a comprehensive analysis of deep learning-based semantic segmentation models for post-disaster structural damage assessment in terms of accuracy, generalization ability and computational efficiency. Using the custom-built Kahramanmaraş Earthquake dataset, along with high-resolution drone and satellite imagery from the Joplin Tornado and xBD datasets, the objective was to detect building-level damage grades. The DeepLabV3+ segmentation architecture was evaluated using various backbone networks. For building-level classification, segmentation outputs were merged with polygon boundaries extracted from pre-disaster imagery to determine the structural damage status of individual buildings. experimental findings revealed that ResNet50 and Xception provided the highest segmentation accuracy overall, whereas MobileNetV2 offered advantages in computational efficiency, making it preferable for lightweight and rapid applications. On the other hand, due to class imbalance and the complexity of debris patterns, all models exhibited difficulty in accurately detecting fully collapsed buildings an issue most prominent in architectures with shallower depth. This study proposes a deep learning-based framework for rapid and accurate post-disaster damage assessment
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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