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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
IMPLEMENTASI ALGORITMA CONVOLUTIONAL NEURAL NETWORK UNTUK MEMPREDIKSI KEMATANGAN PADA BUAH MELON
Get PDFBuah melon merupakan jenis buah-buahan yang menjadi kebutuhan pokok manusia dalam mencukupi gizi pada tubuh manusia. Khususnya di Indonesia sangat banyak di jumpai buah melon dengan jenis Sky Rocket. Kematangan buah melon menjadi suatu hal yang sangat diperhatikan dalam penentu proses saat panen. Kerana buah melon termasuk kedalam jenis buah non-klimakterik, maka buah melon harus dipanen dalam kondisi matang. Banyak para petani melakukan pemanenan buah melon secara bersamaan, yang menyebabkan tingkat kematangan buah melon berbeda. Karena pada dasarnya, setiap tanaman melon dapat menumbuhkan 4 hingga 5 buah melon, sehingga banyak perbedaan tingkat kematangan. Oleh sebab itu, dibutuhkan suatu pendekatan kususnya bidang teknologi yang mampu menyelesaikan permalahan tersebut. Salah satu pendekatan untuk pengidentifikasian menggunakan gambar dengan metode Convolutional Neural Network. dimana metode ini merupakan pengembangan dari metode Deep Learning, dalam mengidentifikasi dan mengklasifikasikan sebuah objek citra digital. Dari hasil perancangan program arsitektur CNN menggunakan bahasa python memakai library tensorflow. Dari hasil identifikasi kematangan buah melon didapatkan tingkat akurasi sebesar 99% data training, dan 99% dari data testing. Setelah peneliti melakukan uju coba menggunakan data baru sebanyak 150 gambar, didapatkan tingkat akurasi sebesar 52%. Dari berbagai percobaan yang telah peneliti lakukan, performa dari model yang telah dibuat cukup optimal dalam mengidentifikasi kematangan buah melon.
Kata Kunci :Sky Rocket, Deep Learning, Python, Citra digital, Tensorflo
Analisis dan klasifikasi status produksi bebek pedaging menggunakan Algoritma Fuzzy K_Nearest Neighbors
Get PDFABSTRAK
Keberhasilan budidaya bebek pedaging tampak dari indikator kinerja terukur seperti tingkat angka kematian, konsumsi pakan yang telah ditentukan, bobot berat akhir, dan rasio konversi pakan (FCR). Masih banyak kerugian dalam pola manajemen kandang, salah satu faktor utamanya adalah tingkat kematian yang sangat tinggi. Sehingga, berdasarkan dari hasil penelitian tentang pokok bahasan produksi bebek pedaging, peneliti mencoba menganalisis unsur-unsur produksi menggunakan berbagai teknik pengolahan data, antara lain clusification berbasis jaringan syaraf tiruan dan fuzzy classifier telah terbukti memiliki hasil yang sangat baik untuk data klasifikasi. Akan tetapi, dalam praktiknya terdapat situasi dimana sebaran data training dan testing sama tetapi berbeda. Berdasarkan analisis penelitian sebelumnya, algoritma fuzzy k-nearest neighbor diterapkan untuk mengolah data produksi bebek potong. Berdasarkan hasil pengujian metode fuzzy k-nearest neighbors dengan membandingkan jumlah dataset, nilai jarak terdekat “k”, dan derajat keanggotaan “m”. Didapatkan parameter terbaik yaitu dengan parameter nilai k=9, m=2, dan pembagian dataset training 80% dan testing 20%. Didapatkan nilai akurasi sebesar 80.07% dari hasil pengklasifikasian status produksi bebek pedaging.
مستخلص البحث
ينعكس نجاح إنتاج بط اللاحم في مؤشرات أداء قابلة للقياس، مثل معدل النفوق، واستهلاك العلف، ووزن الجسم النهائي، ونسبة تحويل العلف (FCR). لا تزال هناك العديد من العيوب في نمط إدارة الأقفاص، ومن أهمها ارتفاع معدل النفوق. لذلك، واستنادًا إلى نتائج الأبحاث المتعلقة بإنتاج بط اللاحم، حاول الباحثون تحليل عناصر الإنتاج باستخدام تقنيات معالجة بيانات متنوعة، بما في ذلك التجميع القائم على الشبكات العصبية الاصطناعية والمصنفات الضبابية، والتي أثبتت نتائجها الممتازة في تصنيف البيانات. ومع ذلك، في الممارسة العملية، هناك حالات يكون فيها توزيع بيانات التدريب والاختبار متماثلًا ولكنه مختلف. بناءً على نتائج تحليل البحث السابق، استُخدمت خوارزمية "أقرب جار ضبابي k" لمعالجة بيانات إنتاج بط اللاحم. بناءً على نتائج اختبار خوارزمية "أقرب جار ضبابي k" بمقارنة معلمات عدد مجموعات البيانات، ومعلمة أقرب مسافة "k"، ومعلمة درجة العضوية "m". تم الحصول على أفضل المعلمات باستخدام معلمات k = 9 وm = 2، وتقسيم مجموعة بيانات التدريب بنسبة 80% والاختبار بنسبة 20%. وتم الحصول على دقة 80.07% من نتائج تصنيف حالة إنتاج بط اللاحم
ABSTRACT
The efficiency of broiler duck production is apparent in measurable performance indicators such as mortality rate, feed consumption, end body weight, and feed conversion ratio (FCR). The cage management approach still has numerous drawbacks, with one of the primary issues being the exceedingly high mortality rate. Consequently, drawing from the findings of studies on broiler duck production, researchers aimed to examine production factors employing diverse data processing methods, such as clustering based on artificial neural networks and fuzzy classifiers, that have shown exceptional efficacy in classifying data. However, in practice, there are situations where the distribution of training and testing data is the same yet different. Drawing from the results of the previous research analysis, the fuzzy k-nearest neighbor algorithm was utilized to process broiler duck production data. Results from testing the fuzzy k-nearest neighbors method were analyzed by comparing the dataset quantity, the nearest distance parameter "k," and the membership degree parameter "m." The optimal parameters were achieved with k = 9, m = 2, and an 80% training dataset division alongside a 20% testing set. An accuracy rate of 80.07% was achieved from the classification results of the broiler duck production status
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
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