1,720,955 research outputs found
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
Development of The Software as Services (SaaS) Business Model in The Satusehat Integrated Electronic Medical Record System
Full text linkDigital transformation in the healthcare sector represents a key strategy to enhance operational efficiency and improve the quality of medical services. This study presents the development of a Software as a Service (SaaS)-based Electronic Medical Record (EMR) information system, integrated with SatuSehat, a national health data platform managed by the Ministry of Health of the Republic of Indonesia. The system is designed to improve the accuracy of clinical data recording and expedite access to patient information for healthcare professionals. The development process adopted the Agile methodology, characterized by iterative and incremental stages including requirements analysis, system design, implementation, testing, and evaluation. Agile was selected for its ability to accommodate dynamic user needs and regulatory requirements through continuous feedback loops and adaptive planning. Compliance with national health regulations and data security standards, including Minister of Health Regulation No. 24 of 2022 concerning EMR implementation, guided the entire process. Evaluation of the system demonstrates enhanced efficiency in medical administrative workflows, improved accuracy of patient records, and accelerated clinical decision-making processes. The integration with SatuSehat enables interoperability at a national level, thereby supporting real-time health data exchange and long-term health monitoring systems. From a societal standpoint, the system improves data accessibility for healthcare personnel and elevates the overall quality of care delivered to patients. Economically, the SaaS-based approach reduces operational costs, promotes efficient budgeting, and contributes to the broader digital transformation of healthcare services, particularly in strengthening primary care infrastructure
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
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
Deteksi Hama Penyakit Daun Padi Dengan Menggunakan Teknik Optimasi Deep Learning Convolutional Neural Network
Full text linkBudidaya padi memegang peranan penting dalam ketahanan pangan nasional, namun sering terhambat oleh serangan penyakit daun yang berdampak signifikan terhadap penurunan produksi. Untuk menjawab tantangan tersebut, penelitian ini merancang sebuah aplikasi berbasis algoritma Convolutional Neural Network (CNN) guna mengklasifikasi penyakit daun padi secara otomatis dan akurat. Pengumpulan data dilakukan melalui observasi langsung di Gapoktan (Gabungan Kelompok Tani) Kabupaten Kuningan, wawancara dengan petani, studi literatur, serta pengembangan sistem menggunakan pendekatan Rapid Application Development (RAD) yang memungkinkan pembangunan aplikasi secara cepat dan terstruktur. Model Convolutional Neural Network (CNN) yang dibangun diuji menggunakan 480 gambar sampel dan menghasilkan akurasi tinggi sebesar 97,75%. Nilai F1-Score yang diperoleh yaitu 0,97 untuk Brown Spot, 0,921 untuk Blast, 0,871 untuk Hispa, dan 0,952 untuk daun sehat. Hasil ini menunjukkan bahwa aplikasi mampu mendeteksi penyakit secara dini, sehingga petani dapat segera mengambil tindakan preventif untuk meminimalkan kerugian hasil panen. Untuk meningkatkan performa, disarankan penerapan Model teknik optimasi yang diterapkan dalam proses model CNN (Convolutional Neural Network ) seperti perluasan dataset, variasi teknik augmentasi data set, serta evaluasi terhadap gambar dengan kompleksitas tinggi. Pengembangan ke klasifikasi penyakit lainnya juga sangat potensial. Secara keseluruhan, aplikasi ini berpeluang besar mendukung pertanian digital dan mewujudkan sistem pertanian padi yang lebih berkelanjutan dan modern.Budidaya padi memegang peranan penting dalam ketahanan pangan nasional, namun sering terhambat oleh serangan penyakit daun yang berdampak signifikan terhadap penurunan produksi. Untuk menjawab tantangan tersebut, penelitian ini merancang sebuah aplikasi berbasis algoritma Convolutional Neural Network (CNN) guna mengklasifikasi penyakit daun padi secara otomatis dan akurat. Pengumpulan data dilakukan melalui observasi langsung di Gapoktan (Gabungan Kelompok Tani) Kabupaten Kuningan, wawancara dengan petani, studi literatur, serta pengembangan sistem menggunakan pendekatan Rapid Application Development (RAD) yang memungkinkan pembangunan aplikasi secara cepat dan terstruktur. Model Convolutional Neural Network (CNN) yang dibangun diuji menggunakan 480 gambar sampel dan menghasilkan akurasi tinggi sebesar 97,75%. Nilai F1-Score yang diperoleh yaitu 0,97 untuk Brown Spot, 0,921 untuk Blast, 0,871 untuk Hispa, dan 0,952 untuk daun sehat. Hasil ini menunjukkan bahwa aplikasi mampu mendeteksi penyakit secara dini, sehingga petani dapat segera mengambil tindakan preventif untuk meminimalkan kerugian hasil panen. Untuk meningkatkan performa, disarankan penerapan Model teknik optimasi yang diterapkan dalam proses model CNN (Convolutional Neural Network ) seperti perluasan dataset, variasi teknik augmentasi data set, serta evaluasi terhadap gambar dengan kompleksitas tinggi. Pengembangan ke klasifikasi penyakit lainnya juga sangat potensial. Secara keseluruhan, aplikasi ini berpeluang besar mendukung pertanian digital dan mewujudkan sistem pertanian padi yang lebih berkelanjutan dan modern
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
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