Information Preserving Processing of Noisy Handwritten Document Images

Many pre-processing techniques that normalize artifacts and clean noise induce anomalies due to discretization of the document image. Important information that could be used at later stages may be lost. A proposed composite-model framework takes into account pre-printed information, user-added data, and digitization characteristics. Its benefits are demonstrated by experiments with statistically significant results. Separating pre-printed ruling lines from user-added handwriting shows how ruling lines impact people\u27s handwriting and how they can be exploited for identifying writers. Ruling line detection based on multi-line linear regression reduces the mean error of counting them from 0.10 to 0.03, 6.70 to 0.06, and 0.13 to 0.02, com- pared to an HMM-based approach on three standard test datasets, thereby reducing human correction time by 50%, 83%, and 72% on average. On 61 page images from 16 rule-form templates, the precision and recall of form cell recognition are increased by 2.7% and 3.7%, compared to a cross-matrix approach. Compensating for and exploiting ruling lines during feature extraction rather than pre-processing raises the writer identification accuracy from 61.2% to 67.7% on a 61-writer noisy Arabic dataset. Similarly, counteracting page-wise skew by subtracting it or transforming contours in a continuous coordinate system during feature extraction improves the writer identification accuracy. An implementation study of contour-hinge features reveals that utilizing the full probabilistic probability distribution function matrix improves the writer identification accuracy from 74.9% to 79.5%

Under Construction (Identities, Communities and Visual Overkill)

Most of modern identities emerge from mediated interactions in public and virtual spaces. There are no acknowledged authorities to watch over organizational identities and grant them legitimacy. These identities are renegotiated in real and virtual communities, often carry a permanent label 'under construction' and can be violently contested in public space. Garrulous behaviour stimulated by interactive media and by the forthcoming Evernet allows for a gradual build-up of individual and social response to the visual overkill in media-regulated societies. Voicing the images over, we mobilize for action, dismantle institutional structures and generally speaking mix gate-keeping with data-dating, thus contributing to the overall change of world's cultural climate - one of bricks, clicks and flicks. Benetton's Toscani campaign and Napster's ordeal are cases in point.corporate identity;cultural climate;flicks;virtual community;visual overkill

Where the inchoate seeks form: Autobiographical curriculum inquiry in women\u27s rowing

In 1976, four years after the Title IX act was passed by the Federal Government, a group of female rowers at Yale University attempted to reveal the university\u27s discriminatory practices toward their team. On March 3, 1976, team captain, Chris Ernst, secured an appointment with the assistant athletic director Joni Barnett. Members of the Yale Women\u27s Crew filed silently into the athletic director\u27s office wearing sweats that said Yale Women\u27s Crew, then stripped to the waist, revealing the words Title IX written on their bare chests and backs. Chris Ernst read a 300-word statement (New York Times, 3/4/76) while a New York Times reporter took notes. Using archival data and the 1999 film, A Hero For Daisy , by Mary Mazzio which documents the Title IX protest at Yale University, I explore the rhetorical moves these women used when the conventional modes of address failed them. I identify and analyze the rhetorical tactics they used in order to contest the dominant ideologies about female athletes and to make a claim about the ways the university was discriminating against them by exploiting their bodies (Ernst in Mazzio, 1999). Through this study, I draw on feminist studies, philosophy, composition studies and curriculum theory to pursue a set of concerns related to my work as an educator. What lessons does an exploration of the rhetorical tactics used by the women in this event offer educators committed to educational equity? How can we return subjectivity to curriculum studies, to research in education and to history? In particular, I am concerned with situations where issues of injustice go unrecognized and unaddressed because of the way that oppression is embedded into the available language and forms. I explore the ways historical and present power structures maintain narratives that preclude a genuine public discussion that might advance the cause of justice (Kastely, 1997). This dissertation is not an argument in the rational empiricist tradition; the trajectory of the work may not be clearly linear, nor clearly located in a disciplinary or theoretical territory. Like the rower, this research takes a path that is defined, but not definite

Payment in Credit: Copyright Law and Subcultural Creativity

Copyright lawyers talk and write a lot about the uncertainties of fair use and the deterrent effects of a clearance culture on publishers, teachers, filmmakers, and the like, but know less about the choices people make about copyright on a daily basis, especially when they are not working. Here, Tushnet examines one subcultural group that engages in a variety of practices, from pure copying and distribution of others\u27 works to creation of new stories, art, and audiovisual works: the media-fan community. Among other things, she discusses some differences between fair use and fan practices, focused around attribution as an alternative to veto rights over uses of copyrighted works

Post-Yugoslav Film and Literature Production: an Alternative to Mainstream Political and Cultural Discourse

Drawing upon studies which emphasized and conceptualized the existence of political and cultural alternatives to the emerging nationalistic cultures in ex-Yugoslav societies, this study aims at following those anti-nationalist artistic records in newly formed post-Yugoslav states. By offering an overview to the contemporary artistic production, namely literature and film, an exploration focuses on several concrete cultural concepts, which should then function as tools for displaying the difference/ opposition between the mainstream culture and its alternative authors and artifacts. The question of an exile, as existentially altered position, which also reframes the issue of one’s belonging, then question of the Other, crucial for establishing one’s identity, and finally a notion of memory which is a space for reconsideration of both private and official histories, problems of responsibility and guilt, are encompassing the way these post- Yugoslav film and literature authors articulate their own artistic and political views. Process of violent disintegration is a constitutive argument of this research, for it necessitates understanding of three post-Yugoslav states which were at war (Croatia, Bosnia and Herzegovina and Serbia) as a single cultural/political space. By inevitably touching upon Yugoslav cultural heritage this writing also seeks to distinguish novel identities and concepts which have been emerging after the dissolution

Under Construction (Identities, Communities and Visual Overkill)

Most of modern identities emerge from mediated interactions in public and virtual spaces. There are no acknowledged authorities to watch over organizational identities and grant them legitimacy. These identities are renegotiated in real and virtual communities, often carry a permanent label 'under construction' and can be violently contested in public space. Garrulous behaviour stimulated by interactive media and by the forthcoming Evernet allows for a gradual build-up of individual and social response to the visual overkill in media-regulated societies. Voicing the images over, we mobilize for action, dismantle institutional structures and generally speaking mix gate-keeping with data-dating, thus contributing to the overall change of world's cultural climate - one of bricks, clicks and flicks. Benetton's Toscani campaign and Napster's ordeal are cases in point

Deep Learning With Sentiment Inference For Discourse-Oriented Opinion Analysis

Opinions are omnipresent in written and spoken text ranging from editorials, reviews, blogs, guides, and informal conversations to written and broadcast news. However, past research in NLP has mainly addressed explicit opinion expressions, ignoring implicit opinions. As a result, research in opinion analysis has plateaued at a somewhat superficial level, providing methods that only recognize what is explicitly said and do not understand what is implied. In this dissertation, we develop machine learning models for two tasks that presumably support propagation of sentiment in discourse, beyond one sentence. The first task we address is opinion role labeling, i.e.\ the task of detecting who expressed a given attitude toward what or who. The second task is abstract anaphora resolution, i.e.\ the task of finding a (typically) non-nominal antecedent of pronouns and noun phrases that refer to abstract objects like facts, events, actions, or situations in the preceding discourse. We propose a neural model for labeling of opinion holders and targets and circumvent the problems that arise from the limited labeled data. In particular, we extend the baseline model with different multi-task learning frameworks. We obtain clear performance improvements using semantic role labeling as the auxiliary task. We conduct a thorough analysis to demonstrate how multi-task learning helps, what has been solved for the task, and what is next. We show that future developments should improve the ability of the models to capture long-range dependencies and consider other auxiliary tasks such as dependency parsing or recognizing textual entailment. We emphasize that future improvements can be measured more reliably if opinion expressions with missing roles are curated and if the evaluation considers all mentions in opinion role coreference chains as well as discontinuous roles. To the best of our knowledge, we propose the first abstract anaphora resolution model that handles the unrestricted phenomenon in a realistic setting. We cast abstract anaphora resolution as the task of learning attributes of the relation that holds between the sentence with the abstract anaphor and its antecedent. We propose a Mention-Ranking siamese-LSTM model (MR-LSTM) for learning what characterizes the mentioned relation in a data-driven fashion. The current resources for abstract anaphora resolution are quite limited. However, we can train our models without conventional data for abstract anaphora resolution. In particular, we can train our models on many instances of antecedent-anaphoric sentence pairs. Such pairs can be automatically extracted from parsed corpora by searching for a common construction which consists of a verb with an embedded sentence (complement or adverbial), applying a simple transformation that replaces the embedded sentence with an abstract anaphor, and using the cut-off embedded sentence as the antecedent. We refer to the extracted data as silver data. We evaluate our MR-LSTM models in a realistic task setup in which models need to rank embedded sentences and verb phrases from the sentence with the anaphor as well as a few preceding sentences. We report the first benchmark results on an abstract anaphora subset of the ARRAU corpus \citep{uryupina_et_al_2016} which presents a greater challenge due to a mixture of nominal and pronominal anaphors as well as a greater range of confounders. We also use two additional evaluation datasets: a subset of the CoNLL-12 shared task dataset \citep{pradhan_et_al_2012} and a subset of the ASN corpus \citep{kolhatkar_et_al_2013_crowdsourcing}. We show that our MR-LSTM models outperform the baselines in all evaluation datasets, except for events in the CoNLL-12 dataset. We conclude that training on the small-scale gold data works well if we encounter the same type of anaphors at the evaluation time. However, the gold training data contains only six shell nouns and events and thus resolution of anaphors in the ARRAU corpus that covers a variety of anaphor types benefits from the silver data. Our MR-LSTM models for resolution of abstract anaphors outperform the prior work for shell noun resolution \citep{kolhatkar_et_al_2013} in their restricted task setup. Finally, we try to get the best out of the gold and silver training data by mixing them. Moreover, we speculate that we could improve the training on a mixture if we: (i) handle artifacts in the silver data with adversarial training and (ii) use multi-task learning to enable our models to make ranking decisions dependent on the type of anaphor. These proposals give us mixed results and hence a robust mixed training strategy remains a challenge

The Rhetoric of Symmetry

References to the concept of symmetry have appeared in judicial opinions, advocacy efforts, and scholarly commentary throughout American legal history. But for every legal writer who invokes the concept as a logical or moral ideal, there is another who dismisses it as a formalistic distraction or an arid illusion. What is more, although legal writers virtually always use the term “symmetry” as if its meaning were self-evident, in fact they have used the same term to refer to a variety of distinct concepts, each with its own ambiguities