We report four experiments investigating the effects of repeated and transposed letters in orthographic processing. Orthographically related primes were formed by removing one letter from the target word, by transposing two adjacent letters, or by replacing two adjacent letters with different letters. Robust masked priming in a lexical decision task was found for primes formed by removing a single letter (e.g., mircle-MIRACLE), and this was not influenced by whether or not the prime contained a letter repetition (e.g., balace vs. balnce as a prime for BALANCE). Target words containing a repeated letter tended to be harder to respond to than words without a letter repetition, but the nonwords formed by removing a repeated letter (e.g., BALNCE) were no harder to reject than nonwords formed by removing a non-repeated letter (e.g., MIRCLE, BALACE). Significant transposition priming effects were found for 7-letter words (e.g., sevrice-SERVICE), and these priming effects did not vary as a function of the position of the transposition (initial, final, or inner letter pair). Priming effects disappeared when primes were formed by replacing the two transposed letters with different letters (e.g., sedlice-SERVICE), and fiveletter words only showed priming effects with inner letter transpositions (e.g., Correspondence should be addressed to Jonathan Grainger, Laboratoire de Psychologie

Abstract-Our goal is to link spatial and temporal properties of letter recognition to reading speed for text viewed centrally or in peripheral vision. We propose that the size of the visual span- the number of letters recognizable in a glance- imposes a fundamental limit on reading speed. and that shrinkage of the visual span in peripheral vision accounts for slower peripheral reading. In Experiment 1, we estimated the size of the visual span in the lower visual field by measuring RSVP (rapid serial visual presentation) reading times as a function of word length. The size of the visual span decreased from at least 10 letters in central vision to 1.7 letters at 15° eccentricity, in good agreement with the corresponding reduction of reading speed measured by Chung et al. (1998). In Exp. 2, we measured letter recognition for trigrams (random strings of three letters) as a function of their position on horizontal lines passing through fixation (central vision) or displaced downward into the lower visual field (5, 10 and 20°). We also varied trigram presentation time. We used these data to construct visual-span profiles of letter accuracy versus letter position. These profiles were used as input to a parameter-free model whose output was RSVP reading speed. A version of this model containing a simple lexical-matching rule accounted for RSVP reading speed in central vision. Failure of this version of the model in peripheral vision indicated that people rely more on lexical inference to support peripheral reading. We conclude that spatiotemporal characteristics of the visual span limit RSVP reading speed in central vision, and that shrinkage of the visual span results in slower reading in peripheral vision.

An asymmetrical optimal viewing position (OVP) effect in isolated word recognition has been well documented, such that recognition speed and accuracy are highest when the point of fixation within the word is slightly to the left of center. However, there remains disagreement as to the source of the asymmetry in the OVP effect. One leading explanation is that perceptual acuity in isolated word recognition is asymmetric, falling off more rapidly to the left than to the right. An alternative explanation is that of lexical constraint: perceptual acuity may be symmetric, but that the distributional statistics of the lexicon are such that the letters near the beginning of a word are on average of greater value in discriminating word identity than the letters near the end. On both these accounts, a left-of-center fixation point optimizes the efficient accrual of

This document consists of the 1999 version of the ISO C Standard with the edits from TC1 and TC2 applied to it (plus a few typos corrections). Writing coding guidelines is a very common activity. Whether these guidelines provide any benefit other than satisfying the itch that caused their author to write them is debatable. My own itch scratchings are based on having made a living, since 1991, selling tools that provide information to developers about possible problems in C source code. The prime motivating factor for these coding guidelines subsections is money (other coding guideline documents often use technical considerations to label particular coding constructs or practices as good or bad). The specific monetary aspect of software of interest to me is reducing the cost of source code ownership. Given that most of this cost is the salary of the people employed to work on it, the performance characteristics of human information processing is the prime consideration. Software developer interaction with source code occurs over a variety of timescales. My own interests and professional experience primarily deals with interactions whose timescale are measured in seconds. For this reason these coding guidelines discuss issues that are of importance over this timescale. While interactions that occur over longer timescales (e.g., interpersonal interaction) are important, they are not the primary focus of these coding guideline subsections. The study of human information processing, within the timescale of interest, largely falls within the field of cognitive psychology and an attempt has been made to underpin the discussion with the results of studies performed by researchers in this field. The study of software engineering has yet to outgrow the mathematical roots from wh...

It has been known for a long time that visual task, such as reading, counting and searching, greatly influences eye movement patterns. Perhaps the best known demonstration of this is the celebrated study of Yarbus showing that different eye movement trajectories emerge depending on the visual task that the viewers are given. The objective of this paper is to develop an inverse Yarbus process whereby we can infer the visual task by observing the measurements of a viewer’s eye movements while executing the visual task. The method we are proposing is to use Hidden Markov Models (HMMs) to create a probabilistic framework to infer the viewer’s task from eye movements. 1

It has been known for a long time that visual task, such as reading, counting and searching, greatly influences eye movement patterns. Perhaps the best known demonstration of this is the celebrated study of Yarbus showing that different eye movement trajectories emerge depending on the visual task that the viewers are given. The objective of this paper is to develop an inverse Yarbus process whereby we can infer the visual task by observing the measurements of a viewer’s eye movements while executing the visual task. The method we are proposing is to use Hidden Markov Models (HMMs) to create a probabilistic framework to infer the viewer’s task from eye movements. 1