12,525 research outputs found
Author Identification from Song Lyrics
No full textMachine Learning (ML) tools have been used extensively in a wide variety of domains
recently. Due the enormous amount of data being produced, machine learning techniques
are being heavily used to make sense of data & derive meaningful results. Using machine
learning tools, we can turn the data into knowledge.
Music is one of the truest forms of art. Bangladesh has a great history of music with a
great tradition of song writing over centuries. Authorship attribution is the way of
identifying the author from a linguistic corpus.
This paper demonstrates a guideline to identify the author of a Bengali song from the
lyrics of that song using machine learning. This research work presents the first work on
machine learning approach for author attribution from the lyrics of a song. Here six
methods of machine learning are used for the author identification and high accuracies
have been achieved from these methods. It is observed that Naïve Bayes method provides
higher accuracy in comparison with the other methods
Song
No full textAuthor attribution from Rudolph, 240. Printed on yellow paper with black ink. Set to the tune of "Happy land of Canaan". First line "You Rebels come along and listen to my song"
sj-docx-1-trr-10.1177_03611981221134628 – Supplemental material for Head-Up Display Graphic Warning to Support Collision Avoidance: Effect of Graphic Animation and Border on Driving Behavior and Eye Movement Pattern
No full textSupplemental material, sj-docx-1-trr-10.1177_03611981221134628 for Head-Up Display Graphic Warning to Support Collision Avoidance: Effect of Graphic Animation and Border on Driving Behavior and Eye Movement Pattern by Yuwei Wang, Jiaqing Song, Xiaojiang An, Shu Ma, Hongting Li, Duming Wang and Zhen Yang in Transportation Research Record</p
The Singer or the Song? Developments in Performers' Rights from the Perspective of a Cultural Economist
No full textOver the last century, performers gradually acquired statutory protection of their economic and moral
rights. These rights are not copyright in the legal sense but neighboring rights and until recently, they
were mainly remuneration rights that are collectively administered. With the WPPT (WIPO
Performers and Phonograms Treaty), performers now have individual exclusive rights for digital
performances; this leads to the question: what has motivated this change – is it a change in the
perception of the value of performer or a change brought about by the changing technology of copying or,
indeed, a change that reflects different economic costs and benefits? The paper discusses the role of
copyright law as an incentive to performers and asks if the economic role of the performer is so different
from that of the author. The conclusion is that a complex interaction of the legal regulations, economic
conditions and institutional arrangements for administering these new rights will determine the outcome
Design and Analysis of a Rolling Joint Based on Tension Amplification
No full textOwing to structural rigidity and inherent quality issues in traditional industrial manipulators, attaining essential safety in man-machine cooperation proves challenging. In this study, we emulate the human arm tendon drive principle, positioning the motor, reducer, and other high-quality components behind and driving them with cables. To address the stiffness issue in low-mass manipulators, we design the structure of a bilateral conjugate gear rolling joint using a pulley tension amplification mechanism. Analyzing the designed rolling joint, we unveil the kinematic relationship between cable length and joint angle. Simultaneously, we derive expressions for the stiffness and strength of the rolling joint, laying a theoretical foundation for subsequent joint optimization. We have also analyzed the overall pulley system and derived the tension transfer. Conducting kinematics simulation with the Adams simulation software, we unveil the impact of the number of turns on the joint angle. The observed motion results align with the theoretically derived outcomes
sj-docx-2-tan-10.1177_17562864231154976 – Supplemental material for Short-term outcome prediction for myasthenia gravis: an explainable machine learning model
No full textSupplemental material, sj-docx-2-tan-10.1177_17562864231154976 for Short-term outcome prediction for myasthenia gravis: an explainable machine learning model by Huahua Zhong, Zhe Ruan, Chong Yan, Zhiguo Lv, Xueying Zheng, Li-Ying Goh, Jianying Xi, Jie Song, Lijun Luo, Lan Chu, Song Tan, Chao Zhang, Bitao Bu, Yuwei Da, Ruisheng Duan, Huan Yang, Sushan Luo, Ting Chang and Chongbo Zhao in Therapeutic Advances in Neurological Disorders</p
sj-docx-1-tan-10.1177_17562864231154976 – Supplemental material for Short-term outcome prediction for myasthenia gravis: an explainable machine learning model
No full textSupplemental material, sj-docx-1-tan-10.1177_17562864231154976 for Short-term outcome prediction for myasthenia gravis: an explainable machine learning model by Huahua Zhong, Zhe Ruan, Chong Yan, Zhiguo Lv, Xueying Zheng, Li-Ying Goh, Jianying Xi, Jie Song, Lijun Luo, Lan Chu, Song Tan, Chao Zhang, Bitao Bu, Yuwei Da, Ruisheng Duan, Huan Yang, Sushan Luo, Ting Chang and Chongbo Zhao in Therapeutic Advances in Neurological Disorders</p
Freemasons\u27 Song
No full textSong concerning pride in Freemasonryhttps://egrove.olemiss.edu/kgbsides_uk/1560/thumbnail.jp
Northumberland Election Song
No full textA song for a political candidate.https://egrove.olemiss.edu/kgbsides_uk/1899/thumbnail.jp
Song of Haymakers
No full textA song about working in the hayfields during summer.https://egrove.olemiss.edu/kgbsides_uk/1628/thumbnail.jp
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