1,720,968 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
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
Perbandingan Metode EfficientNetB3 dan MobileNetV2 Untuk Identifikasi Jenis Buah-buahan Menggunakan Fitur Daun: Metode EfficientNetB3 dan MobileNetv2
No full textToday's technology is growing rapidly in various fields. One of the benefits of technological developments are helping human to work in various fields, for instance, in the field of plantations, development for the quality of fruits and even in the field of education. One of them is identifying the types of fruits that are needed by citizen even children. They can easily distinguish the types of fruits by looking at the shape of the leaves, so that it can help to increase their knowledge about fruits. For ordinary people, it must be quite difficult to know what kind of fruit on its leaf. Therefore, this study proposes a Convolution Neural Network proposal by comparing the architecture of EfficientNet-B3 and MobileNet-V2 by setting several parameters to get the best accuracy value in detecting fruit types using leaf features. EfficientNet-B3 and MobileNet-V2 are pre-trained models from CNN that tell a fairly large dataset, namely ImageNet. The results obtained from this study are applied several parameters such as the use of epoch, optimizer Adam, optimizer Adamax, optimizer sgd, bathsize. For EfficientNet-B3 epoch 20 optimizer sgd produces an accuracy of 0.2370 or 23%, while EfficientNet-B3 epoch 50 optimizer Adamax produces an accuracy of 0.3051 or 30%. In addition, research on the MobileNet-V2 epoch 20 optimizer Adam resulted in an accuracy of 0.9914 or 99%, while the MobileNet-V2 epoch 50 optimizer Adamax resulted in an accuracy of 0.9860 or 98%.
Keywords: Leaf, Convolution Neural Network, EfficientNet-B3, MobileNet-V2Teknologi pada zaman sekarang semakin berkembang dengan pesat dalam berbagai bidang. Manfaat dari perkembangan teknologi ini tentu saja dapat membantu pekerjaan manusia di berbagai bidang. Misalkan dalam bidang perkebunan, pengembangan untuk kualitas pada buah-buahan bahkan sampai pada bidang pendidikan. Salah satunya adalah pengidentifikasian jenis buah-buahan dibutuhkan agar masyarakat umum khususnya anak-anak dapat membedakan jenis buah-buahan dengan cara melihat bentuk daun, sehingga dapat bermanfaat untuk menambah wawasan mengenai buah-buahan. Untuk orang awam pasti cukup sulit dalam mengetahui jenis buah apa dari daun tersebut. Oleh karena itu penelitian ini mengusulkan algoritma Convolution Neural Network dengan membandingkan arsitektur EfficientNet-B3 dan MobileNet-V2 dengan cara mengatur beberapa parameter pada setiap model untuk mendapatkan nilai akurasi terbaik dalam mendeteksi jenis buah-buahan menggunakan fitur daun. EfficientNet-B3 dan MobileNet-V2 merupakan model Pre-trained dari CNN yang telaj dilatih pada suatu dataset yang cukup besar yaitu ImageNet. Hasil yang dihasilkan dari penelitian ini dengan menerapkan beberapa parameter seperti penggunaan epoch, optimizer Adam, optimizer Adamax, optimizer sgd, bathsize. Untuk EfficientNet-B3 epoch 20 optimizer sgd menghasilkan akurasi 0,2370 atau 23%, sedangkan EfficientNet-B3 epoch 50 optimizer Adamax menghasilkan akurasi 0,3051 atau 30%. Selain itu penelitian pada model MobileNet-V2 epoch 20 optimizer Adam menghasilkan akurasi 0,9914 atau 99%, sedangkan MobileNet-V2 epoch 50 optimizer Adamax menghasilkan akurasi 0,9860 atau 98%.
Kata kunci: Daun, Convolution Neural Network, EfficientNet-B3, MobileNet-V
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
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
Voting classifier in pain points identification
Get PDFA successful app understands and addresses the needs of its users. Pain points-specific difficulties and frustrations that users experience while using an application-are crucial for understanding user expectations and improving user experience. Google Play Store reviews can be a valuable source for identifying these pain points, but this raw data requires processing to be useful for developers. This study develops a model to automatically classify reviews as either containing pain points or not. We chose the voting classifier as our primary algorithm because of its proven ability to produce models with high accuracy through combining the strengths of multiple classifiers. After evaluating 5 different classifier methods, our research shows that the optimal model combines XGradient boosting, multinomial naïve Bayes, and logistic regression-with each contributing unique strengths in text classification. This combination achieves 90% accuracy and a 90% F1-Score, outperforming previous studies that used neural networks (which achieved 80% accuracy). The model successfully identifies user frustrations from app reviews, providing developers with actionable insights to improve their applications.
IDENTIFIKASI PERFORMA ALGORITMA BLAKE3 UNTUK VALIDASI DATA
Full text linkThis study aims to test the ability and performance of the BLAKE3 algorithm in determining data integrity. The test will conduct a series of trials using the checksum method to obtain the hash value of a data using the BLAKE3 algorithm. The parameters tested are computation time, power consumption, CPU thread, and data size. This test shows that the BLAKE3 algorithm is able to validate data. With this test, the use of the BLAKE3 algorithm has optimal parameters that can be set in order to get the fastest and most efficient results of computing time and power consumption.  
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