12,702 research outputs found
Author Identification from Song Lyrics
Machine 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
Author 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"
The Singer or the Song? Developments in Performers' Rights from the Perspective of a Cultural Economist
Over 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
Diminishing returns among lamina fresh and dry mass, surface area, and petiole fresh mass among nine Lauraceae species
Premise
The phenomenon called “diminishing returns” refers to a scaling relationship between lamina mass (M) vs. lamina area (A) in many species, i.e., M ∝ Aα>1, where α is the scaling exponent exceeding unity. Prior studies have focused on the scaling relationships between lamina dry mass (DM) and A, or between fresh mass (FM) and A. However, the scaling between petiole mass and M and A has seldom been investigated. Here, we examine the scaling relationships among FM, DM, A, and petiole fresh mass (PFM).
Methods
For each of 3268 leaves from nine Lauraceae species, FM, DM, A, and PFM were measured, and their scaling relationships were fitted using reduced major axis regression protocols. The bootstrap percentile method was used to test the significance of the difference in α-values between any two species.
Results
The phenomenon of diminishing returns was verified between FM vs. A and DM vs. A. The FM vs. A scaling relationship was statistically more robust than the DM vs. A scaling relationship based on bivariate regression r2-values. Diminishing returns were also observed for the PFM vs. FM and PFM vs. A scaling relationships. The PFM vs. FM scaling relationship was statistically more robust than the PFM vs. A scaling relationship.
Conclusions
“Diminishing returns” was confirmed among the FM, DM, A, and PFM scaling relationships. The data collectively indicate that the petiole scales mechanically more strongly with lamina mass than with area, suggesting that static (self) loading takes precedence over dynamic (wind) loading
Fig. 2 in Diterpenoid alkaloids from Delphinium forrestii var. viride and their anti-inflammation activity
Fig. 2. Key HMBC correlations of compounds 1–6.Published as part of Song, Zhuorui, Gao, Chengfeng, Jiang, Qinghua, Xu, Jinyu, Xiong, Liangliang, Liu, Kexin, Sun, Dejuan, Li, Hua & Chen, Lixia, 2021, Diterpenoid alkaloids from Delphinium forrestii var. viride and their anti-inflammation activity, pp. 1-11 in Phytochemistry (112971) 192 on page 5, DOI: 10.1016/j.phytochem.2021.112971, http://zenodo.org/record/825802
Freemasons\u27 Song
Song concerning pride in Freemasonryhttps://egrove.olemiss.edu/kgbsides_uk/1560/thumbnail.jp
Northumberland Election Song
A song for a political candidate.https://egrove.olemiss.edu/kgbsides_uk/1899/thumbnail.jp
Song of Haymakers
A song about working in the hayfields during summer.https://egrove.olemiss.edu/kgbsides_uk/1628/thumbnail.jp
Appendix to Esther's Song
Notes - 'Esther's Song' with descriptive entries on friends, associates, and family members (125 pages)Appendi
A General Model for Describing the Ovate Leaf Shape
Many plant species produce ovate leaves, but there is no general parametric model for describing this shape. Here, we used two empirical nonlinear equations, the beta and Lobry–Rosso–Flandrois (LRF) equations, and their modified forms (referred to as the Mbeta and MLRF equations for convenience), to generate bilaterally symmetrical curves along the x-axis to form ovate leaf shapes. In order to evaluate which of these four equations best describes the ovate leaf shape, we used 14 leaves from 7 Neocinnamomum species (Lauraceae) and 72 leaves from Chimonanthus praecox (Calycanthaceae). Using the AIC and adjusted root mean square error to compare the fitted results, the modified equations fitted the leaf shapes better than the unmodified equations. However, the MLRF equation provided the best overall fit. As the parameters of the MLRF equation represent leaf length, maximum leaf width, and the distance from leaf apex to the point associated with the maximum leaf width along the leaf length axis, these findings are potentially valuable for studying the influence of environmental factors on leaf shape, differences in leaf shape among closely related plant species with ovate leaf shapes, and the extent to which leaves are bilaterally symmetrical. This is the first work in which temperature-dependent developmental equations to describe the ovate leaf shape have been employed, as previous studies lacked similar leaf shape models. In addition, prior work seldom attempted to describe real ovate leaf shapes. Our work bridges the gap between theoretical leaf shape models and empirical leaf shape indices that cannot predict leaf shape profiles
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