Wearable robots are an emerging form of technology that allow organizations to combine the strength, precision, and performance of machines with the flexibility, intelligence, and problem-solving abilities of human wearers. Active exoskeletons are a type of wearable robot that gives wearers the ability to effortlessly lift up to 200 lbs., as well as perform other types of physically demanding tasks that would be too strenuous for most humans. Synchronization between exoskeleton suits and wearers is one of the most challenging requirements (...) to operate these technologies effectively. In this conceptual paper, we extend interpersonal adaption theory (IAT) to the exoskeleton context and explicate (a) the antecedents that are most likely to shape synchrony in human-exoskeleton interactions, (b) automatic and strategic synchrony as adaptive behaviors in human-exoskeleton interactions, and (c) outcome variables that are especially important in these processes. Lastly, we offer a discussion of key methodological challenges for measuring synchrony in human-exoskeleton interactions and offer a future research agenda for this important area. (shrink)

Originally published in 1972, Should Trees Have Standing? was a rallying point for the then burgeoning environmental movement, launching a worldwide debate on the basic nature of legal rights that reached the U.S. Supreme Court. Now, in the 35th anniversary edition of this remarkably influential book, Christopher D. Stone updates his original thesis and explores the impact his ideas have had on the courts, the academy, and society as a whole. At the heart of the book is an eminently (...) sensible, legally sound, and compelling argument that the environment should be granted legal rights. For the new edition, Stone explores a variety of recent cases and current events--and related topics such as climate change and protecting the oceans--providing a thoughtful survey of the past and an insightful glimpse at the future of the environmental movement. This enduring work continues to serve as the definitive statement as to why trees, oceans, animals, and the environment as a whole should be bestowed with legal rights, so that the voiceless elements in nature are protected for future generations. (shrink)

This paper presents the first use of a computational model of natural logic—a system of logical inference which operates over natural language—for textual inference. Most current approaches to the PAS- CAL RTE textual inference task achieve robustness by sacrificing semantic precision; while broadly effective, they are easily confounded by ubiquitous inferences involving monotonicity. At the other extreme, systems which rely on first-order logic and theorem proving are precise, but excessively brittle. This work aims at a middle way. Our system finds (...) a low-cost edit sequence which transforms the premise into the hypothesis; learns to classify entailment relations across atomic edits; and composes atomic entailments into a top-level entailment judgment. We provide the first reported results for any system on the FraCaS test suite. We also evaluate on RTE3 data, and show that hybridizing an existing RTE system with our natural logic system yields significant performance gains. (shrink)

I wish to present a codi cation of syntactic approaches to dealing with ergative languages and argue for the correctness of one particular approach, which I will call the Inverse Grammatical Relations hypothesis.1 I presume familiarity with the term `ergativity', but, brie y, many languages have ergative case marking, such as Burushaski in (1), in contrast to the accusative case marking of Latin in (2). More generally, if we follow Dixon (1979) and use A to mark the agent-like argument of (...) a transitive verb, O to mark the patient-like argument of a transitive verb, and S to mark the single argument of an intransitive verb, then we can call ergative any subsystem of a language that groups S and O in contrast to A, as shown in (3). (shrink)

In this book, Christopher D. Rodkey asks how the brain worships and responds by engaging ideas from neurological science, philosophy, ritual theory, and religious education. The Synaptic Gospel will prove to be a useful theoretical tool for pastors, religious educators, youth ministers, church music professionals, and seminary students.

Linking constructions involving dሇ (DE) are ubiquitous in Chinese, and can be translated into English in many different ways. This is a major source of machine translation error, even when syntaxsensitive translation models are used. This paper explores how getting more information about the syntactic, semantic, and discourse context of uses of dሇ (DE) can facilitate producing an appropriate English translation strategy. We describe a finergrained classification of dሇ (DE) constructions in Chinese NPs, construct a corpus of annotated examples, and (...) then train a log-linear classifier, which contains linguistically inspired features. We use the DE classifier to preprocess MT data by explicitly labeling dሇ (DE) constructions, as well as reordering phrases, and show that our approach provides significant BLEU point gains on MT02 (+1.24), MT03 (+0.88) and MT05 (+1.49) on a phrasedbased system. The improvement persists when a hierarchical reordering model is applied. (shrink)

Increasingly, voices in the growing neurodiversity movement are alleging that individuals who are neurologically divergent, such as those with conditions related to bipolar disorder, autism, schizophrenia, and depression, must struggle for their civil rights. This movement therefore raises questions of interest to scholars in the humanities and social sciences, as well as to concerned members of the general public. These questions have to do with such matters as the accessibility of knowledge about mental health; autonomy and community within the realm (...) of the mentally ill; and accommodation in civil society and its institutions. The contributors to Ethics and Neurodiversity explore these questions, and the traditional philosophical questions related to them. The authors pay special attention to the need to examine the policies and practices of institutions, such as higher education, social support, and healthcare. (shrink)

Skyrms has pointed out differences between the results of rational choice theory and evolutionary game theory. This commentary argues that there is a great deal of agreement on the Nash Bargaining Solution, which maximizes the product of player payoffs, in both rational-choice-based and evolution-based theories of equilibrium selection. While evolutionary game theory has the potential to explain how we arrive at the behavioural rules that govern what we do, realistic models will require calibration through laboratory experiments. Indeed, experimental evidence strongly (...) supports the Nash Bargaining Solution. (shrink)

1 Boolean retrieval 1 2 The term vocabulary and postings lists 19 3 Dictionaries and tolerant retrieval 49 4 Index construction 67 5 Index compression 85 6 Scoring, term weighting and the vector space model 109 7 Computing scores in a complete search system 135 8 Evaluation in information retrieval 151 9 Relevance feedback and query expansion 177 10 XML retrieval 195 11 Probabilistic information retrieval 219 12 Language models for information retrieval 237 13 Text classification and Naive Bayes 253 (...) 14 Vector space classification 289 15 Support vector machines and machine learning on documents 319 16 Flat clustering 349 17 Hierarchical clustering 377 18 Matrix decompositions and latent semantic indexing 403 19 Web search basics 421 20 Web crawling and indexes 443 21 Link analysis 461.. (shrink)

This book argues that the othering and criminalization of Black people in times of crisis is part of the religious meaning of America that fuels the problem of mass incarceration. The author develops a religious interpretation of the significance of these images to America’s political economy the produces the very problems we punish as a society.

We have only limited awareness of the system by which we control our actions and this limited awareness does not seem to be concerned with the control of action. Awareness of choosing one action rather than another comes after the choice has been made, while awareness of initiating an action occurs before the movement has begun. These temporal differences bind together in consciousness the intention to act and the consequences of the action. This creates our sense of agency. Activity in (...) the anterior cingulate cortex and medial prefrontal cortex is associated with awareness of our own actions and also occurs when we think about the actions of others. I propose that the mechanism underlying awareness of how our own intentions lead to actions can also be used to represent the intentions that underlie the actions of others. This common system enables us to communicate mental states and thereby share our experiences. (shrink)

Christopher Frith is a research professor at the Functional Imaging Laboratory of the Wellcome Department of Imaging Neuroscience at University College, London. He explores, experimentally, using the techniques of functional brain imaging, the relationship between human consciousness and the brain. His research focuses on questions pertaining to perception, attention, control of action, free will, and awareness of our own mental states and those of others. As the following discussion makes clear, Frith investigates brain systems involved in the choice of (...) one action over another and in the understanding of other people. Such investigations are aimed at understanding brain basis of autism and schizophrenia. In his widely cited study of schizophrenia, The Cognitive Neuropsychology of Schizophrenia , Frith argues that many of the positive symptoms of schizophrenia, such as delusions of control, auditory hallucinations, and thought insertion, involve problems of self-monitoring. Patients, in effect, lose track of their own intentions and mistakenly attribute agency for their own actions to someone else. Frith employs models of motor control, involving comparator mechanisms and efference copy, not only to explain delusions that involve movement, but also to develop a neurocognitive explanation of delusional cognition. (shrink)

Environmental ethics has reached a certain level of maturity; further significant advances require reexamining its status within the larger realm of moral philosophy. It could aim to extend to nonhumans one of the familiar sets of principles subject to appropriate modifications; or it could seek to break away and put forward its own paradigm or paradigms. Selecting the proper course requires as the most immediate mission exploring the formal requirements of an ethical system. In general, are there constraints against bringing (...) our moral relations with different sorts of things under different mIes of govemance? In particular, how much independence can an environmental ethic (or ethics) aim to have? (shrink)

I examine what would be necessary to move part-of-speech tagging performance from its current level of about 97.3% token accuracy (56% sentence accuracy) to close to 100% accuracy. I suggest that it must still be possible to greatly increase tagging performance and examine some useful improvements that have recently been made to the Stanford Part-of-Speech Tagger. However, an error analysis of some of the remaining errors suggests that there is limited further mileage to be had either from better machine learning (...) or better features in a discriminative sequence classifier. The prospects for further gains from semisupervised learning also seem quite limited. Rather, I suggest and begin to demonstrate that the largest opportunity for further progress comes from improving the taxonomic basis of the linguistic resources from which taggers are trained. That is, from improved descriptive linguistics. However, I conclude by suggesting that there are also limits to this process. The status of some words may not be able to be adequately captured by assigning them to one of a small number of categories. While conventions can be used in such cases to improve tagging consistency, they lack a strong linguistic basis. (shrink)

Discriminative feature-based methods are widely used in natural language processing, but sentence parsing is still dominated by generative methods. While prior feature-based dynamic programming parsers have restricted training and evaluation to artificially short sentences, we present the first general, featurerich discriminative parser, based on a conditional random field model, which has been successfully scaled to the full WSJ parsing data. Our efficiency is primarily due to the use of stochastic optimization techniques, as well as parallelization and chart prefiltering. On WSJ15, (...) we attain a state-of-the-art F-score of 90.9%, a 14% relative reduction in error over previous models, while being two orders of magnitude faster. On sentences of length 40, our system achieves an F-score of 89.0%, a 36% relative reduction in error over a generative baseline. (shrink)

Antti Revonsuo has given us an engaging and deliberately provocative paper discussing the value of brain imaging in the search for the neural basis of consciousness. In some places, however, his enthusiasm for the controversial nature of the topic has led him to overstate or misdirect his case.

We propose a model of natural language inference which identifies valid inferences by their lexical and syntactic features, without full semantic interpretation. We extend past work in natural logic, which has focused on semantic containment and monotonicity, by incorporating both semantic exclusion and implicativity. Our model decomposes an inference problem into a sequence of atomic edits linking premise to hypothesis; predicts a lexical semantic relation for each edit; propagates these relations upward through a semantic composition tree according to properties of (...) intermediate nodes; and joins the resulting semantic relations across the edit sequence. A computational implementation of the model achieves 70% accuracy and 89% precision on the FraCaS test suite. Moreover, including this model as a component in an existing system yields significant performance gains on the Recognizing Textual Entailment challenge. (shrink)

This volume reaches beyond the controversy surrounding the teaching and learning of evolution in the United States, specifically in regard to the culture, politics, and beliefs found in the Southeast. The editors argue that despite a deep history of conflict in the region surrounding evolution, there is a wealth of evolution research taking place—from biodiversity in species to cultural evolution and human development. In fact, scientists, educators, and researchers from around the United States have found their niche in the South, (...) where biodiversity is high, culture runs deep, and the pace is just a little bit slower. (shrink)

This paper proposes a new architecture for textual inference in which finding a good alignment is separated from evaluating entailment. Current approaches to semantic inference in question answering and textual entailment have approximated the entailment problem as that of computing the best alignment of the hypothesis to the text, using a locally decomposable matching score. While this formulation is adequate for representing local (word-level) phenomena such as synonymy, it is incapable of representing global interactions, such as that between verb negation (...) and the addition/removal of qualifiers, which are often critical for determining entailment. We propose a pipelined approach where alignment is followed by a classification step, in which we extract features representing high-level characteristics of the entailment problem, and give the resulting feature vector to a statistical classifier trained on development data. (shrink)

The alignment problem—establishing links between corresponding phrases in two related sentences—is as important in natural language inference (NLI) as it is in machine translation (MT). But the tools and techniques of MT alignment do not readily transfer to NLI, where one cannot assume semantic equivalence, and for which large volumes of bitext are lacking. We present a new NLI aligner, the MANLI system, designed to address these challenges. It uses a phrase-based alignment representation, exploits external lexical resources, and capitalizes on (...) a new set of supervised training data. We compare the performance of MANLI to existing NLI and MT aligners on an NLI alignment task over the well-known Recognizing Textual Entailment data. We show that MANLI significantly outperforms existing aligners, achieving gains of 6.2% in F1 over a representative NLI aligner and 10.5% over GIZA++. (shrink)

adjacent phrases, but they typically lack the ability to perform the kind of long-distance reorderings possible with syntax-based systems. In this paper, we present a novel hierarchical phrase reordering model aimed at improving non-local reorderings, which seamlessly integrates with a standard phrase-based system with little loss of computational efficiency. We show that this model can successfully handle the key examples often used to motivate syntax-based systems, such as the rotation of a prepositional phrase around a noun phrase. We contrast our (...) model with reordering models commonly used in phrase-based systems, and show that our approach provides statistically significant BLEU point gains for two language pairs: Chinese-English (+0.53 on MT05 and +0.71 on MT08) and Arabic-English (+0.55 on MT05). (shrink)

A desirable quality of a coreference resolution system is the ability to handle transitivity constraints, such that even if it places high likelihood on a particular mention being coreferent with each of two other mentions, it will also consider the likelihood of those two mentions being coreferent when making a final assignment. This is exactly the kind of constraint that integer linear programming (ILP) is ideal for, but, surprisingly, previous work applying ILP to coreference resolution has not encoded this type (...) of constraint. We train a coreference classifier over pairs of mentions, and show how to encode this type of constraint on top of the probabilities output from our pairwise classifier to extract the most probable legal entity assignments. We present results on two commonly used datasets which show that enforcement of transitive closure consistently improves performance, including improvements of up to 3.6% using the b3 scorer, and up to 16.5% using cluster f-measure. (shrink)

Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the sparseness of counts of such dependencies, smoothing and the ability to use multiple sources of knowledge are important challenges. For example, if the probability P(N |V ) of noun N being the subject of verb V is high, and V takes similar objects to V , and V is synonymous to V , then (...) we want to conclude that P(N |V ) should also be reasonably high—even when those words did not cooccur in the training data. (shrink)

This report details experimental results of using stochastic disambiguation models for parsing sentences from the Redwoods treebank (Oepen et al., 2002). The goals of this paper are two-fold: (i) to report accuracy results on the more highly ambiguous latest version of the treebank, as compared to already published results achieved by the same stochastic models on a previous version of the corpus, and (ii) to present some newly developed models using features from the HPSG signs, as well as the MRS (...) dependency graphs. (shrink)

Abstract:Ninety years ago, John Dewey’s discussion of “the religious”—as distinct from traditional “religion”—opened new ways of thinking about the connection between spirituality and everyday forms of human action. But in what ways does our contemporary religious landscape invite us to reimagine and reconstruct Deweyan approaches to religion? This essay addresses this question by focusing on how the community of El Paso, Texas came together to respond to one of the worst racially motivated mass shootings in recent history. This community’s use (...) of spirituality, art, and institutional religion all corroborate key Deweyan insights and invite us to stretch them further. (shrink)

The correct locus (or loci) of binding theory has been a matter of much discussion. Theories can be seen as varying along at least two dimensions. The rst is whether binding theory is con gurationally determined (that is, the theory exploits the geometry of a phrase marker, appealing to such purely structural notions as c-command and government) or whether the theory depends rather on examining the relations between items selected by a predicate (where by selection I am intending to cover (...) everything from semantic dependencies to syntactic subcategorization). The second is the level of grammar on which binding is de ned. Attempting to roughly equate levels across di erent theories, suggestions have included the semantics/lexical conceptual structure (Jackendo 1992), thematic structure (Jackendo 1972, Wilkins 1988), argument structure/D-structure/initial grammatical relations (Manning 1994, Belletti and Rizzi 1988, Perlmutter 1984), surface syntax/grammatical relations, logical form, linear order, pragmatics (Levinson 1991), and discourse (Iida 1992). The data is su ciently varied and complex that many theories end up as mixtures, variously employing a combination of elements along both dimensions (for instance, Chomsky (1986) relies purely on con gurational notions for the relationship between an anaphor and its antecedent, but uses concepts from selection in the de nition of the binding domain of an anaphor). LFG has always rejected a con gurational account of binding. For instancError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMape, Simpson (1991) argues that a con gurational theory of binding in Warlpiri cannot be maintained, among other reasons because nite clauses lack a VP.. (shrink)

This paper shows that a simple two-stage approach to handle non-local dependencies in Named Entity Recognition (NER) can outperform existing approaches that handle non-local dependencies, while being much more computationally efficient. NER systems typically use sequence models for tractable inference, but this makes them unable to capture the long distance structure present in text. We use a Conbel.

This paper examines feature selection for log linear models over rich constraint-based grammar (HPSG) representations by building decision trees over features in corresponding probabilistic context free grammars (PCFGs). We show that single decision trees do not make optimal use of the available information; constructed ensembles of decision trees based on different feature subspaces show signifi- cant performance gains (14% parse selection error reduction). We compare the performance of the learned PCFG grammars and log linear models over the same features.

We present a system for deciding whether a given sentence can be inferred from text. Each sentence is represented as a directed graph (extracted from a dependency parser) in which the nodes represent words or phrases, and the links represent syntactic and semantic relationships. We develop a learned graph matching model to approximate entailment by the amount of the sentence’s semantic content which is contained in the text. We present results on the Recognizing Textual Entailment dataset (Dagan et al., 2005), (...) and show that our approach outperforms Bag- Of-Words and TF-IDF models. (shrink)

Many named entities contain other named entities inside them. Despite this fact, the field of named entity recognition has almost entirely ignored nested named entity recognition, but due to technological, rather than ideological reasons. In this paper, we present a new technique for recognizing nested named entities, by using a discriminative constituency parser. To train the model, we transform each sentence into a tree, with constituents for each named entity (and no other syntactic structure). We present results on both newspaper (...) and biomedical corpora which contain nested named entities. In three out of four sets of experiments, our model outperforms a standard semi-CRF on the more traditional top-level entities. At the same time, we improve the overall F-score by up to 30% over the flat model, which is unable to recover any nested entities. (shrink)

This paper examines the Stanford typed dependencies representation, which was designed to provide a straightforward description of grammatical relations for any user who could benefit from automatic text understanding. For such purposes, we argue that dependency schemes must follow a simple design and provide semantically contentful information, as well as offer an automatic procedure to extract the relations. We consider the underlying design principles of the Stanford scheme from this perspective, and compare it to the GR and PARC representations. Finally, (...) we address the question of the suitability of the Stanford scheme for parser evaluation. (shrink)

This article reconstructs Hegel’s account of nature’s autonomy and argues for its significance for his understanding of human autonomy and the relation between nature and spirit. It argues that Hegel treats the actualization of nature’s autonomy—epitomized by the phenomena of animal voice and birdsong—as a vital component of the actualization of free human spirit. Drawing on this analysis, the article then offers an ecological gloss on Hegel’s interest in the progressive actualization of freedom in the modern world. It concludes by (...) sketching a Hegelian account of what it might mean to listen to nature’s voices. (shrink)