1,720,957 research outputs found
Improving Automatic Essay Scoring for Indonesian Language using Simpler Model and Richer Feature
Get PDFAutomatic essay scoring is a machine learning task where we create a model that can automatically assess student essay answers. Automated essay scoring will be instrumental when the answer assessment process is on a large scale so that manual correction by humans can cause several problems. In 2019, the Ukara dataset was released for automatic essay scoring in the Indonesian language. The best model that has been published using the dataset produces an F1-score of 0.821 using pre-trained fastText sentence embedding and the stacking model between the neural network and XGBoost. In this study, we propose to use a simpler classifier model using a single hidden layer neural network but using a richer feature, namely BERT sentence embedding. Pre-trained model BERT sentence embedding extracts more information from sentences but has a smaller file size than fastText pre-trained model. The best model we propose manages to get a higher F1-score than the previous models on the Ukara dataset, which is 0.829
Classroom Attendance Based on Smiling Face Patterns and Nearby Wifi with Deep Learning
No full textStudents' attendance in class is often mandatory in education and becomes a benchmark for assessing students. Sometimes there are still fraudulent practices by students to achieve minimum attendance. From the administrative perspective, a paper-based presence system is potentially wasteful and extends the administrative stage because it requires manual recapitulation. This study aims to design a class attendance application based on facial pattern recognition, smile, and closest Wi-Fi. The method used in this research is a deep learning approach with CNN based architecture, FaceNet, to recognize faces. In addition to facial images, the system will also validate the attendance with location and time data. Location data is obtained from matching SSID from the database, and time data is taken when the user sends attendance data through API. This attendance system consists of three applications: web, mobile, and services installed on a mini-computer, which are integrated to sending attendance data to the academic system automatically. As confirmation, students are required to smile selfies to strengthen the validity of their presence. The testing model's accuracy results are 92.6%, while for live testing accuracy the model obtained 66.7%.
Kehadiran mahasiswa dalam suatu pembelajaran di kelas seringkali menjadi syarat wajib dalam dunia pendidikan, dan menjadi tolak ukur dalam menilai mahasiswa. Terkadang masih dijumpai praktik curang oleh mahasiswa dalam presensi agar mencapai kehadiran minimal. Dari sisi administrasi, presensi berbasis kertas berpotensi pemborosan dan juga memperpanjang tahapan administrasi karena membutuhkan rekapitulasi manual. Penelitian ini bertujuan untuk merancang bangun aplikasi presensi kelas berbasis pengenalan pola wajah, senyum, dan Wi-Fi terdekat. Metode yang digunakan dalam penelitian ini adalah pendekatan Deep Learning dengan arsitektur CNN FaceNet untuk mengenali wajah. Selain gambar wajah, sistem juga akan memvalidasi presensi dengan kesesuaian lokasi dan waktu. Data lokasi diperoleh dari pencocokan SSID dengan database, dan data waktu diambil saat mahasiswa mengirimkan data kehadiran melalui API. Sistem presensi ini terdiri dari tiga aplikasi yaitu web, mobile, dan service yang dipasang di komputer mini, yang saling terintegrasi untuk mengirimkan data presensi ke sistem akademik secara otomatis. Sebagai konfirmasi, siswa diwajibkan selfie tersenyum untuk memperkuat validitas kehadiran. Sistem terintegrasi ini masih dalam bentuk purwarupa. Hasil akurasi dari testing model sebesar 92,6% sedangkan untuk testing live akurasi sebesar 66,7%. Nilai testing live lebih kecil dan cukup jauh dari testing model dapat diartikan hasil training model terlalu overfitting
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
Quran Memorization Technologies and Methods: Literature Review
No full textThe application of the Qur\u27an for the memorizers in adding and maintaining their memorization continues to grow in number. No less than 200 digital Qur\u27an applications are available on mobile application providers. In addition, publications on the topic of the digital Qur\u27an in the last ten years have also increased. Through these applications and publications, it is an opportunity to find patterns and knowledge about current topics and features. Through this knowledge, it is hoped that it can be a recommendation for a better form of digital Al-Qur\u27an application system, especially providing features that affect increasing the ease and quality of memorizing the Qur\u27an. This paper aims to explore the application of the Qur\u27an specifically for memorizing and papers on the topic to provide these recommendations. The method used to get the paper using PRISMA. While the applications being reviewed are taken from the AppStore. As a result, 31 papers were reviewed and 12 main applications regarding the Qur\u27an for memorization were obtained. Through the answers to each research question, it can be used by subsequent researchers as well as by system developers in developing Al-Qur\u27an products for better memorization of tense
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
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