Fertilization of case frame dictionary for robust Japanese case analysis

This paper proposes a method of fertilizing a Japanese case frame dictionary to handle com-plicated expressions: double nominative sen-tences, non-gapping relation of relative clauses, and case change. Our method is divided into two stages. In the first stage, we parse a large corpus and construct a Japanese case frame dic-tionary automatically from the parse results. In the second stage, we apply case analysis to the large corpus utilizing the constructed case frame dictionary, and upgrade the case frame dictio-nary by incorporating newly acquired informa-tion.

Automatic Acquisition of Lexical-Functional Grammar Resources from a Japanese Dependency Corpus

PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200

Improving Japanese Zero Pronoun Resolution by Global Word Sense Disambiguation

This paper proposes unsupervised word sense disambiguation based on automatically constructed case frames and its incorporation into our zero pronoun resolution system. The word sense disambiguation is applied to verbs and nouns. We consider that case frames define verb senses and semantic features in a thesaurus define noun senses, respectively, and perform sense disambiguation by selecting them based on case analysis. In addition, according to the one sense per discourse heuristic, the word sense disambiguation results are cached and applied globally to the subsequent words. We integrated this global word sense disambiguation into our zero pronoun resolution system, and conducted experiments of zero pronoun resolution on two different domain corpora. Both of the experimental results indicated the effectiveness of our approach.

The Lexical Grid: Lexical Resources in Language Infrastructures

Language Resources are recognized as a central and strategic for the development of any Human Language Technology system and application product. they play a critical role as horizontal technology and have been recognized in many occasions as a priority also by national and spra-national funding a number of initiatives (such as EAGLES, ISLE, ELRA) to establish some sort of coordination of LR activities, and a number of large LR creation projects, both in the written and in the speech areas

Metabolic Rift or Metabolic Shift? Dialectics, Nature, and the World-Historical Method

Abstract In the flowering of Red-Green Thought over the past two decades, metabolic rift thinking is surely one of its most colorful varieties. The metabolic rift has captured the imagination of critical environmental scholars, becoming a shorthand for capitalism’s troubled relations in the web of life. This article pursues an entwined critique and reconstruction: of metabolic rift thinking and the possibilities for a post-Cartesian perspective on historical change, the world-ecology conversation. Far from dismissing metabolic rift thinking, my intention is to affirm its dialectical core. At stake is not merely the mode of explanation within environmental sociology. The impasse of metabolic rift thinking is suggestive of wider problems across the environmental social sciences, now confronted by a double challenge. One of course is the widespread—and reasonable—sense of urgency to evolve modes of thought appropriate to an era of deepening biospheric instability. The second is the widely recognized—but inadequately internalized—understanding that humans are part of nature

Copyright, Commodification, and Culture: Locating the Public Domain

The relationship between increased commodification and the public domain in copyright law is the subject of considerable controversy, both political and theoretical. The paper argues that beliefs about what legal definition the public domain requires depend crucially on implicit preconceptions about what a public domain is. When considered in broader historical context, the term public domain has a specific set of denotative and connotative meanings that constitute the artistic, intellectual, and informational public domain as a geographically separate place, portions of which are presumptively eligible for privatization. This idea meshes well with the current push toward commodification in copyright. The paper then tests this metaphorical construct of the public domain against descriptive and theoretical accounts of the ways that forms of artistic expression develop, and argues that the metaphor in fact describes the public aspects of artistic, intellectual, and informational culture rather badly. Attention to the social parameters of creative practice suggests that the common in culture is not a separate place, but a distributed property of social space. The legally constituted common should both mirror and express this disaggregation. The paper offers a different organizing metaphor for the relationship between the public and the proprietary that matches the theory and practice of creativity more accurately: The common in culture is the cultural landscape within which creative practice takes place. This in turn suggests a need to recalibrate the doctrines that determine the scope of a copyright owner\u27s rights during the copyright term, particularly those that establish the right to control the preparation and exploitation of copies and derivative works

Weed Recognition in Agriculture: A Mask R-CNN Approach

Recent interdisciplinary collaboration on deep learning has led to a growing interest in its application in the agriculture domain. Weed control and management are some of the crucial tasks in agriculture to maintain high crop productivity. The inception phase of weed control and management is to successfully recognize the weed plants, followed by providing a suitable management plan. Due to the complexities in agriculture images, such as similar colour and texture, we need to incorporate a deep neural network that uses pixel-wise grouping for identifying the plant species. In this thesis, we analysed the performance of one of the most popular deep neural networks aimed to solve the instance segmentation (pixel-wise analysis) problems: Mask R-CNN, for weed plant recognition (detection and classification) using field images and aerial images. We have used Mask R-CNN to recognize the crop plants and weed plants using the Crop/Weed Field Image Dataset (CWFID) for the field image study. However, the CWFID\u27s limitations are that it identifies all weed plants as a single class and all of the crop plants are from a single organic carrot field. We have created a synthetic dataset with 80 weed plant species to tackle this problem and tested it with Mask R-CNN to expand our study. Throughout this thesis, we predominantly focused on detecting one specific invasive weed type called Persicaria Perfoliata or Mile-A-Minute (MAM) for our aerial image study. In general, supervised model outcomes are slow to aerial images, primarily due to large image size and scarcity of well-annotated datasets, making it relatively harder to recognize the species from higher altitudes. We propose a three-level (leaves, trees, forest) hierarchy to recognize the species using Unmanned Aerial Vehicles(UAVs) to address this issue. To create a dataset that resembles weed clusters similar to MAM, we have used a localized style transfer technique to transfer the style from the available MAM images to a portion of the aerial images\u27 content using VGG-19 architecture. We have also generated another dataset at a relatively low altitude and tested it with Mask R-CNN and reached ~92% AP50 using these low-altitude resized images

Genome Editing and the Jurisprudence of Scientific Empiricism

Humankind has reached, in tow by the hand of a scientific breakthrough called CRISPR, the Rubicon of precise genetic manipulation first envisioned over fifty years ago. Despite CRISPR\u27s renown in science and its power to transform the world, it remains virtually unaddressed in legal scholarship. In the absence of on-point law, the scientific community has attempted to reach some consensus to preempt antagonistic regulation and prescribe subjective standards of use under the guise of a priori scientific empiricism. Significant and complex legal issues concerning this technology are emerging, and the void in legal scholarship is no longer tolerable. This Article shrinks the scholarly gap, and it is the first to introduce CRISPR to legal literature. By providing a resource for jurists, scholars, and practitioners, it challenges conventional notions concerning the false dichotomy frequently associated with mutually exclusive normative roles for science and law. The Article makes two independent contributions. First, it lays a robust and comprehensive epistemic foundation of genome editing suitable for legal audiences. This element is descriptive, but essential because a detailed and coherent understanding of the nuts and bolts of the science is requisite for a discussion of law and policy. Second, it advocates for a jurisprudence of scientific empiricism, namely, a normative legal framework that consolidates empiricism and technological--e.g., genome editing--applications into a uniform doctrinal structure unencumbered by common substantive impediments to constructive debate. These impediments consist of impractical and often sensationalist claims about issues raised by technological advances and are collectively characterized as deceptive simplicity. The proposed paradigm, which lays a blueprint for the legal community to combat the deleterious effects of scientific illiteracy, flows from the Supreme Court\u27s recent decision in Association for Molecular Pathology v. Myriad Genetics and is broadly adaptable to addressing questions of science in law. Applying this framework, the Article reconsiders Buck v. Belland argues that, contrary to long-held views, Buck is not a direct product of false science, but of unbridled deceptive simplicity. Lastly, the Article sets the stage for a series of forthcoming works that will analyze genome editing from regulatory, constitutional, international, egalitarian, ethical, and policy standpoints, which highlight pivotal synergistic roles for law, science, and public policy in the development of this remarkable nascent biotechnology

Can humain association norm evaluate latent semantic analysis?

This paper presents the comparison of word association norm created by a psycholinguistic experiment to association lists generated by algorithms operating on text corpora. We compare lists generated by Church and Hanks algorithm and lists generated by LSA algorithm. An argument is presented on how those automatically generated lists reflect real semantic relations