473 research outputs found

    Fall 2023 Supplement to Brauneis & Schechter, Copyright: A Contemporary Approach

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    This Fall 2023 Supplement is the product of our effort to capture important developments in copyright law since the publication of the second edition of Copyright: A Contemporary Approach. It includes three Supreme Court decisions as principal cases: the fair use cases of Google LLC v. Oracle America, Inc. (p. 23) and Andy Warhol Foundation v. Goldsmith (p. 41) and the 2020 decision about copyright protection for state statutes, Georgia v. Public.Resources.Org (p. 74).. (Because there are now so many Supreme Court fair use cases to cover, this supplement also includes a note on Harper & Row, Publishers v. Nation Enterprises (pp. 13-14), as an option to replace its treatment as a principal case in the second edition of the casebook. The supplement also includes notes on many other cases, and a few new features that we thought would enhance study of U.S. copyright law. It includes new material on copyright and artificial intelligence, both on the issue of AI authorship, (see the new notes on page 7-9), and the issue of infringement and fair use in training generative AI models (see the new feature on p. 21). Because the Copyright Claims Board (“CCB”) opened up its doors for business in June 2022, we have included a new section at the end of Chapter 6 on the CASE Act and CCB proceedings (p. 67). We have also completely revised Chapter 12.E., on digital audio transmission rights, and Chapter 12.F., on rights in pre-1972 sound recordings. The new Chapter 12.E. in this supplement, “Digital Streaming of Music After the Musical Works Modernization Act” (p. 101), now consists of a general introduction to copyright and the streaming of music, covering both rights in sound recordings and rights in musical works, and all of the relevant exclusive rights

    Data analysis with merge trees

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    Today’s data are increasingly complex and classical statistical techniques need growingly more refined mathematical tools to be able to model and investigate them. Paradigmatic situations are represented by data which need to be considered up to some kind of trans- formation and all those circumstances in which the analyst finds himself in the need of defining a general concept of shape. Topological Data Analysis (TDA) is a field which is fundamentally contributing to such challenges by extracting topological information from data with a plethora of interpretable and computationally accessible pipelines. We con- tribute to this field by developing a series of novel tools, techniques and applications to work with a particular topological summary called merge tree. To analyze sets of merge trees we introduce a novel metric structure along with an algorithm to compute it, define a framework to compare different functions defined on merge trees and investigate the metric space obtained with the aforementioned metric. Different geometric and topolog- ical properties of the space of merge trees are established, with the aim of obtaining a deeper understanding of such trees. To showcase the effectiveness of the proposed metric, we develop an application in the field of Functional Data Analysis, working with functions up to homeomorphic reparametrization, and in the field of radiomics, where each patient is represented via a clustering dendrogram

    Machine Learning Algorithm for the Scansion of Old Saxon Poetry

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    Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input verses

    Being Friendly is Difficult. Psycholinguistic Experiments on Agentivity in Copular Constructions

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    Agentivity in copular constructions such as Sophia is being friendly, compared to its non-agentive counterpart Sophia is friendly, is a phenomenon that has received some attention in the theoretical debate but has not been widely investigated in psycholinguistics. The implications of Sophia’s voluntary control over her deliberate actions, which arise in the former sentence, seem to stem from the interplay between the subject, the verb, and the adjective. Truthfully, there is not much more to the sentence itself. In comparison, Sophia is friendly can be interpreted both as a state and as an event. Neither the predicate nor the verb in isolation can explain how agentivity comes about. Furthermore, the restrictions on the utterance’s agent are vague and flexible. Two theoretical accounts explain the agentivity effect by means of either underspecification or coercion. According to the Underspecification Account, the copula is semantically undetermined and adapts to the requirements of its lexical context as they arise. The adjectival predicate dictates the availability of the agentive interpretation. The Coercion Account postulates that the copula is lexically stative. The state interpretation of the copula-predicate combination is constructed compositionally, but the agentive reading is the result of reinterpreting the utterance as an activity. Underspecification and coercion are reflected in differing ways during processing. The former is effortless, whereas the latter elicits an increase in processing effort and a decrease in naturalness or sensicality. In a series of offline and online experiments on German copular sentences, the predictions of the Underspecification Account and the Coercion Account are put to a test. The results point to the stative nature of the copula, in line with the Coercion Account’s hypothesis. The availability of an adjective’s agentive interpretations appears to hinge on the specific circumstances. However, some degree of uncertainty remains in relation to the subtle nature of agentive coercion effects

    National Conference on ‘Renewable Energy, Smart Grid and Telecommunication-2023

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    Theme of the Conference: “The challenges and opportunities of integrating renewable energy into the grid” The National Conference on Renewable Energy, Smart Grid, and Telecommunication - 2023 is a platform for industry experts, researchers, and policymakers to come together and explore the latest advancements and challenges in the fields of renewable energy, smart grids, and telecommunication. Conference Highlights: In-depth discussions on renewable energy technologies and innovations. Smart grid integration for a sustainable future. The role of telecommunication in advancing renewable energy solutions. Networking opportunities with industry leaders and experts. Presentation of cutting-edge research papers and case studies. Conference topics: Renewable Energy Technologies and Innovations Smart Grid Development and Implementation Telecommunication for Energy Systems Energy Storage and Grid Balancing Policy, Regulation, and Market Dynamics Environmental and Social Impacts of Renewable Energy Energy Transition and Future Outlook Integration of renewable energy into the grid Microgrids and decentralized energy systems Grid cybersecurity and data analytics IoT and sensor technologies for energy monitoring Data management and analytics in energy sector Battery storage technologies and applicationshttps://www.interscience.in/conf_proc_volumes/1087/thumbnail.jp

    Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?

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    Convolutional networks and vision transformers have different forms of pairwise interactions, pooling across layers and pooling at the end of the network. Does the latter really need to be different? As a by-product of pooling, vision transformers provide spatial attention for free, but this is most often of low quality unless self-supervised, which is not well studied. Is supervision really the problem? In this work, we develop a generic pooling framework and then we formulate a number of existing methods as instantiations. By discussing the properties of each group of methods, we derive SimPool, a simple attention-based pooling mechanism as a replacement of the default one for both convolutional and transformer encoders. We find that, whether supervised or self-supervised, this improves performance on pre-training and downstream tasks and provides attention maps delineating object boundaries in all cases. One could thus call SimPool universal. To our knowledge, we are the first to obtain attention maps in supervised transformers of at least as good quality as self-supervised, without explicit losses or modifying the architecture. Code at: https://github.com/billpsomas/simpool.Comment: ICCV 2023. Code and models: https://github.com/billpsomas/simpoo

    Haste: The slow politics of climate urgency

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    What does it mean politically to construct climate change as a matter of urgency? We are certainly running out of time to stop climate change. But perhaps this particular understanding of urgency could be at the heart of the problem. When in haste, we make more mistakes, we overlook things, we get tunnel vision. Here we make the case for a ‘slow politics of urgency’. Rather than rushing and speeding up, the sustainable future is arguably better served by us challenging the dominant framings through which we understand time and change in society. Transformation to meet the climate challenge requires multiple temporalities of change, speeding up certain types of change processes but also slowing things down. While recognizing the need for certain types of urgency in climate politics, Haste directs attention to the different and alternative temporalities at play in climate and sustainability politics. It addresses several key issues on climate urgency: How do we accommodate concerns that are undermined by the politics of urgency, such as participation and justice? How do we act upon the urgency of the climate challenge without reproducing the problems that speeding up of social processes has brought? What do the slow politics of urgency look like in practice? Divided into 23 short and accessible chapters, written by both established and emerging scholars from different disciplines, Haste tackles a major problem in contemporary climate change research and offers creative perspectives on pathways out of the climate emergency

    Topological feature selection for time series data

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    We use tools from applied topology for feature selection on vector-valued time series data. We employ persistent homology and sliding window embeddings to quantify the coordinated dynamics of time series. We describe an algorithm for gradient descent to assign scores, or weights, to the variables of the time series based on their contribution to the dynamics as quantified by persistent homology; the result is a convex combination of a subset of the variables. In this setting, we prove persistence vineyards are piecewise linear and we give a simple formula for the derivatives of the vines. We demonstrate our method of topological feature selection with synthetic data and C. elegans neuronal data.Comment: 15 page

    Imagining machine vision: Four visual registers from the Chinese AI industry

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    Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the national AI market, and technologies like face recognition, object tracking and automated driving play a central role in surveillance systems and social governance projects relying on the large-scale collection and processing of sensor data. Like other novel articulations of technology and society, machine vision is defined, developed and explained by different actors through the work of imagination. In this article, we draw on the concept of sociotechnical imaginaries to understand how Chinese companies represent machine vision. Through a qualitative multimodal analysis of the corporate websites of leading industry players, we identify a cohesive sociotechnical imaginary of machine vision, and explain how four distinct visual registers contribute to its articulation. These four registers, which we call computational abstraction, human–machine coordination, smooth everyday, and dashboard realism, allow Chinese tech companies to articulate their global ambitions and competitiveness through narrow and opaque representations of machine vision technologies.publishedVersio
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