1,720,981 research outputs found
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
Introduction and preliminary results of a calibration for full-frame hyperspectral cameras to monitor agricultural crops with UAVs
No full textHyperspectral remote sensing helps to acquire information about the status of agricultural crops to allow optimized management
practices in the context of precision agriculture. Due to technological innovations small and lightweight hyperspectral sensors
have become available which may be carried by unmanned aerial vehicles (UAVs). In this paper we give a brief overview over
existing hyperspectral sensors for UAVs. We focus on a new type of full-frame sensors which capture hyperspectral information
in two dimensional image frames. We then develop a calibration procedure for these sensors and identify challenges in remote
sensing of vegetation. The calibration is evaluate by in-field data acquired during a flight campaign. The spectral calibration
shows good results with less than three percent difference in reflection for 110 of the 125 bands (458 to 886 nm)
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
Addressing Grand Challenges in Earth Observation Science: The Earth Observation Data Centre for Water Resources Monitoring
No full textEarth observation is entering a new era where the increasing availability of free and open global satellite data sets combined with the computing power offered by modern information technologies opens up the possibility to process high-resolution data sets at global scale and short repeat intervals in a fully automatic fashion. This will not only boost the availability of higher level earth observation data in purely quantitative terms, but can also be expected to trigger a step change in the quality and usability of earth observation data. However, the technical, scientific, and organisational challenges that need to be overcome to arrive at this point are significant. First of all, Petabyte-scale data centres are needed for storing and processing complete satellite data records. Second, innovative processing chains that allow fully automatic processing of the satellite data from the raw sensor records to higher-level geophysical products need to be developed. Last but not least, new models of cooperation between public and private actors need to be found in order to live up to the first two challenges. This paper offers a discussion of how the Earth Observation Data Centre for Water Resources Monitoring (EODC) - a catalyser for an open and international cooperation of public and private organisations - will address these three grand challenges with the aim to foster the use of earth observation for monitoring of global water resources
Process – Based Image Analysis For Agricultural Mapping Using Medium Resolution Satellite Data
No full textTez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2011Günümüzde teknoloji pek çok alanda insanoğlunun günlük hayatta kullandığı işleri daha sistematik, doğruluklu, hızlı ve minimum insan etkileşimi ile otomatikleştirmek üzere gelişmektedir. Bilgi teknolojilerinin birçok alanında olduğu gibi geo-enformasyon alanında da daha hızlı ve hassas bilgiye ihtiyaç artmaktadır. Bugün, uzaktan algılama alanındaki görüntü analizlerinde proses tabanlı sistemler hala uzman etkileşimi gerektirmesine rağmen, gelecekte çok daha fazla işlem adımının tam otomatik olarak gerçekleştirilebileceği akıllı sistemler yer alacaktır. Bu tezin hazırlanmasındaki ana motivasyon uzaktan algılama uygulamalarındaki otomasyon olup, görüntü analizi için proses-bazlı bir prosedür tasarlanmıştır. Tez kapsamında, tarımsal faaliyetlerin periyodik nükseden yapısı nedeni ile proses bazlı tasarım için uygun olduğu düşünülerek, tarımsal haritalama amaçlı görüntü işleme prosesi hazırlanmıştır. Hazırlanan proses çok-zamanlı görüntü setini girdi olarak kullanmakta ve otomatik aşamalı sistem ile sınıflandırılmış görüntü çıktısı sağlamaktadır. Optik ve radar olmak üzere iki ayrı veriseti için iki ayrı proses yazılmıştır. Uydu veri setleri olarak 2007 yılına ait 5 adet SPOT 4 ve 1997 yılına ait 6 adet JERS görüntüsü kullanılmıştır. Çalışma alanı olarak Türkgeldi Tarım İşletmesi seçilmiştir. Çalışmada Türkgeldi Tarım İşletmesi’nden alınan ürün haritaları yardımcı veri olarak kullanılmıştır. Proseste görüntü analizi yöntemi olarak nesne-tabanlı sınıflandırma yöntemi seçilmiştir. Bu yöntemde sınıfların hem spektral özellikler hem de şekil, doku, komşuluk gibi diğer özellikler ile tanımlanması avantajı sağlanmaktadır. Çok-zamanlı verisetleri üzerinde ilk adım olarak segmentasyon işlemi yapılmıştır. Sınıf tanımları yapılarak her parametre için sınıf aidiyet kriteri ve sınıflar için dağılım fonksiyonları belirlenmiştir. Gerektiğinde sınıf tanımlayıcı parametreler mantık operatörleri ile birleştirilmiştir. İkinci adım olarak oluşturulan görüntü nesnelerine fuzzy teorisine dayalı olarak yapılan sınıflandırma işlemi ile üyelik değerleri atanmıştır. Sınıflandırma gerektiği kadar seviyede gerçekleştirilmiştir. Sınıflar hiyerarşik bir ağ yapısı altında birbirleri ile alt-üst sınıf ilişkisi içerisindedirler. Uygulamada proses çalıştırılarak aşamalı olarak sınıflandırma işlemlerini tamamlamakta ve sonuç çıktıya ulaşmaktadır. Çalışmanın değerlendirilmesi amacı ile nesne-tabanlı görüntü sınıflandırma işleminin doğruluk analizi yapılmıştır. Her iki veriseti için ayrı ayrı olmak üzere segmentasyon ve sınıflandırma işlemlerinde karşılaşılan sorunlar ve çözüm yaklaşımları değerlendirilerek otomasyon açısından hazırlanan prosesin başarısı değerlendirilmiştir.Technology, today, is in progress to automate various kinds of work conducted by people to get more accurate products in more systematic and faster ways with less effort. As in many fields of information technologies, the need for timely and accurate geo-spatial information is steadily increasing. Although expert interaction and feedback is needed today, in the future, more of the steps will be done automatically by intelligent systems. The main motivation of this thesis was the automation in remote sensing applications, and a design of a process-based image analyzing procedure was performed. In context of this thesis, a process tree was developed for agricultural mapping based on the thought that the agricultural activities are suitable for process based systems since they recur on a periodic cycle. The process tree written is using multi-temporal image dataset as an input, and then giving the classified output image by using an incremental automated system. Two different procedures were developed and executed for optical and radar image datasets separately. The datasets are composed of 5 images of SPOT 4 data acquired on 2007 and 6 images of JERS data acquired on 1997. The study area was selected as Turkgeldi State Production Farm. The crop maps taken from Türkgeldi State Production Farm were used as ancillary data. Object-based image analysis was used through the process. This method provides the advantage of using class descriptions maintained by considering object properties such as shape, texture and neighborhood relations as well as spectral properties. As a first step, segmentation was applied on multi-temporal data. After the determination of the criteria for each parameter and the expression of related distribution functions, classes were defined. Logical terms were used to combine class descriptions where needed. As the second step, membership values were assigned to the image objects for each possible class based on fuzzy theory. Classification was executed on multi-levels. The hierarchical structure enables a parent-child relation between classes. The final classification output was produced by taking the advantage of a hierarchical structure. The results were interpreted in perspectives of evaluating both the process-based remote sensing applications and the efficiency of object-based image analysis. As the process runs, the classification process is realized incrementally and outputs the final result. To evaluate the success of the application, the accuracy assessment of the object-based image classification was performed. The problems of segmentation and classification operations, and the solution approaches were evaluated for both process trees of optical and radar datasets to assess the success of the process in scope of automation.DoktoraPh
Forest fire susceptibility assessment with machine learning methods in north-east Turkiye
No full textISSN:1682-1750ISSN:2194-9034ISSN:1682-1777ISSN:2194-9034ISSN:1682-177
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