The benefits of programming in a functional style are well known. In particular, algorithms that are expressed as compositions of functions operating on series/vectors/streams of data elements are much easier to understand and modify than equivalent algorithms expressed as loops. Unfortunately, many programmers hesitate to use series expressions, because they are typically implemented very inefficiently---the prime source of inefficiency being the creation of intermediate series objects. A restricted class of series expressions, obviously synchronizable series expressions, is defined which can be evaluated very efficiently. At the cost of introducing restrictions which place modest limits on the series expressions which can be written, the restrictions guarantee that the creation of intermediate series objects is never necessary. This makes it possible to automatically convert obviously synchronizable series expressions into highly efficient loops using straight forward algorithms.

The benefits of programming in a functional style are well known. In particular, algorithms that are expressed as compositions of functions operating on series/vectors/streams of data elements are much easier to understand and modify than equivalent algorithms expressed as loops. Unfortunately, many programmers hesitate to use series expressions, because they are typically implemented very inefficiently. A Common Lisp macro package (OSS) has been implemented which supports a restricted class of series expressions, obviously synchronizable series expressions, which can be evaluated very efficiently by automatically converting them into loops. Using this macro package, programmers can obtain the advantages of expressing computations as series expressions without incurring any run-time overhead.

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

It is nice to give animators artistic freedom, but having to animate every bounce, sway, and counter-balancing movement of a rider on a horse isn't freedom at all. It is painstaking labor that could easily be prevented with an effective character setup. If an animation piece is only going to have a few shots with a horse and rider, then the trouble of setting up an automated character rig is not practical, but if there are a significant amount of shots with a horse and rider galloping across the prairie, doing death defying stunts, and walking for an extended time into the sunset then there needs to be a way to automate the reactions of the rider to the horse. This thesis focuses on what parts of a horse one can analyze to know at what point a rider will lean forward, bounce up from the saddle, or in any way react to a variety of different horse movements. The automated character setup, or rig, makes animating a rider on a horse much more efficient.

This is the 15th issue of the working paper series Interdisciplinary Studies on Information Structure (ISIS) of the Sonderforschungsbereich (SFB) 632. This online version contains the Questionnaire on Focus Semantics contributed by Agata Renans, Malte Zimmermann and Markus Greif, members of Project D2 investigating information structural phenomena from a typological perspective. The present issue provides a tool for collecting and analyzing natural data with respect to relevant linguistic questions concerning focus types, focus sensitive particles, and the effects of quantificational adverbs and presupposition on focus semantics. This volume is a supplementation to the Reference manual of the Questionnaire on Information Structure, issued by Project D2 in ISIS 4 (2006).

This is the 15th issue of the working paper series Interdisciplinary Studies on Information Structure (ISIS) of the Sonderforschungsbereich (SFB) 632. This online version contains the Questionnaire on Focus Semantics contributed by Agata Renans, Malte Zimmermann and Markus Greif, members of Project D2 investigating information structural phenomena from a typological perspective. The present issue provides a tool for collecting and analyzing natural data with respect to relevant linguistic questions concerning focus types, focus sensitive particles, and the effects of quantificational adverbs and presupposition on focus semantics. This volume is a supplementation to the Reference manual of the Questionnaire on Information Structure, issued by Project D2 in ISIS 4 (2006).

Real-world perception of emotion results from the integration of multiple cues, most notably facial expression and affective prosody. The use of incongruent emotional stimuli presents an opportunity to study the interaction between sensory modalities. Thirty-seven participants were exposed to audio-visual stimuli (Robins & Schultz, 2004) including angry, fearful, happy, and neutral presentations. Eighty stimuli contain matching emotions and 240 contain incongruent emotional cues. Matching emotions elicited a significant number of correct responses for all four emotions. Sign tests indicated that for most incongruent conditions, participants demonstrated a bias towards the visual modality. Despite these findings, specific incongruent conditions did show evidence of blending. Future research should explore an evolutionary model of facial expression as a means for behavioral adaptation and the possibility of an “emotional McGurk effect” in particular combinations of emotions.

This study examines the valence and motivational direction components of affect using facial expressions of determination, anger and joy. Determination is a positive, approach-related emotion; anger is a negative, approach-related emotion; and joy is a positive, low-approach emotion. Thus, determination and anger share a motivational direction, but determination and joy share a valence. Participants created facial expressions intended to express joy, anger, fear, sadness, disgust and determination. Naive judges attempted to identify these expressions. Correct identifications of intended determination expressions were positively correlated with misidentifications of the expressions as anger, suggesting that determination is perceived as more similar to anger than to joy. This emphasizes the importance of the motivational component of emotion, as distinct from the valence of emotion.

It is nice to give animators artistic freedom, but having to animate every bounce, sway, and counter-balancing movement of a rider on a horse isn't freedom at all. It is painstaking labor that could easily be prevented with an effective character setup. If an animation piece is only going to have a few shots with a horse and rider, then the trouble of setting up an automated character rig is not practical, but if there are a significant amount of shots with a horse and rider galloping across the prairie, doing death defying stunts, and walking for an extended time into the sunset then there needs to be a way to automate the reactions of the rider to the horse. This thesis focuses on what parts of a horse one can analyze to know at what point a rider will lean forward, bounce up from the saddle, or in any way react to a variety of different horse movements. The automated character setup, or rig, makes animating a rider on a horse much more efficient.

I present and defend an account of indexicals that treats indexicals as presuppositional expressions. I argue that the distinction between presupposed and asserted content can replace the more restrictive distinction between character and content that is characteristic of Kaplanian, two-dimensional views. My account, "Presuppositional Indexicals" (PI), is simpler than a two-dimensional account because it does not posit a special layer of meaning for indexicals that cannot interact with truth-conditional content. PI also has broader scope than two-dimensional theories. It opens the door to a general theory of definite noun phrases according to which all definites have two components to their meaning: an asserted component, which contributes new information to a discourse, and a presuppositional component, which determines where asserted information will be attached in a discourse. PI does not stipulate rigidity or referentiality for indexicals as many other theories do. Indexicals do receive a special semantic treatment in PI, but their special semantics are captured entirely in terms of a strategy that indexicals exhibit for the resolution of their presuppositions. / text