"Interactive use of lexical information in speech perception": Correction to Connine and Clifton.

Reports an error in "Interactive use of lexical information in speech perception" by Cynthia M. Connine and Charles Clifton (Journal of Experimental Psychology: Human Perception and Performance, 1987[May], Vol 13[2], 291-299). In the aforementioned article, Figures 1 and 2 were inadvertently transposed. The figure on p. 294 is actually Figure 2, and the figure on p. 296 is actually Figure 1. The captions are correct as they stand. (The following abstract of the original article appeared in record 1987-23984-001.) Two experiments are reported that demonstrate contextual effects on identification of speech voicing continua. Experiment 1 demonstrated the infuence of lexical knowledge on identification of ambiguous tokens from word–nonword and nonword–word continua. Reaction times for word and nonword responses showed a word advantage only for ambiguous stimulus tokens (at the category boundary); no word advantage was found for clear stimuli (at the continua endpoints). Experiment 2 demonstrated an effect of a postperceptual variable, monetary payoff, on nonword–nonword continua. Identification responses were influenced by monetary payoff, but reaction times for bias-consistent and bias-inconsistent responses did not differ at the category boundary. An advantage for bias-consistent responses was evident at the continua endpoints. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Direct volume display devices

Direct volume display devices (DVDDs), which display 3D volumes and surfaces in a volume by providing depth rather than depth cues, are discussed. The transport theory model is used to illustrate why DVDDs are best able to support fast presentation from arbitrary directions. The technology underlying various DVDDs is described. Specifically, the design and operation of the OmniView rotating-screen DVDD are examined. The air-traffic-control/air-tactics-analysis, satellite orbit mechanics, and time-critical target prosecution applications of DVDDs are also discussed     

Longitudinal elastic waves in columns due to earthquake motion

An analysis is presented of longitudinal waves in a thin elastic column. Velocity is specified at one end, and the boundary condition at the other end is expressed in terms of a range of effective impedances of an attached structure. Propagation, reflection and interference of the waves are followed by the method of characteristics. Integration of differential equations along characteristics yields the wave-induced stress, which is then applied to problems of earthquake excitation. Numerical examples are given for recorded updown ground motion of the Kobe Earthquake.     

Ultrasonic measurement of the inter-electrode gap in electrochemical machining

During the process of electrochemical machining the dependency of the inter-electrode gap with time and process parameters can be used to determine process characteristics and to define the shape of the workpiece surface relative to the tool surface. Defining process variables to map out the required gap-time function requires the use of time-consuming iterative trials. In-line monitoring of the gap would enable process control and tool to workpiece transfer characteristics to be achieved (for ideal conditions) without the requirement to generate such parameter maps. This work explores the use of ultrasound applied as a passive, non-intrusive, in-line gap measurement system for ECM. The accuracy of this technique was confirmed through correspondence between the generated gap-time and current time data and theoretical models applicable to ideal conditions. Gap measurements are also used to demonstrate and quantify the degree of departure from ideal behaviour for an In718/chloride system as the electrolyte flow rate is reduced from 16 to 4 l min⁻¹. The monitoring of the gap size has also been shown to be effective when determining shape convergence under ideal conditions, for the example case of a 2D sinusoidal profile.     

Infants' predictive reaching for moving objects in the dark.

Infants were presented with a moving object under 2 lighting conditions to investigate the role of vision in early reaching. The motion of the target object also allowed for an analysis of the infants' ability to use a predictive style of reaching. Infants were tested twice, at 5 and 7.5 months of age, with a moving object in the light and the same object painted with luminescent paint in the dark. Infants successfully contacted the glowing object on about half of their attempts at both ages, although 7.5 month-olds reached more often. Infants also took into account the motion of the target object by aiming their reaches ahead of the object and by reaching with their contralateral hand. These results suggest that proprioceptive feedback and sight of the target allow for successful reaching with limited visual information, even in relatively complex reaching tasks. The infants' success also demonstrates their ability to adapt their movements and reaching strategy to the speed and trajectory of the target object in order to reach predictively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Thematic roles in sentence parsing.

Two eyetracking experiments examined the interaction among syntactic parsing preferences, thematically based comprehension preferences, and plausibility in the early stages of reading a sentence. Results from 64 adults support the pattern of results reported by L. Stowe (1989) when looking at the disambiguating region of a sentence. However, the results for earlier regions suggest that the postverbal noun phrase was initially taken as direct object of an ergative verb even when the subject was inanimate. It appears that the inanimacy of the subject may not have guided the initial syntactic analysis, but rather facilitated the revision of an initial misanalysis. (French abstract) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Speed-up fractal image compression with a fuzzy classifier

This paper presents a fractal image compression scheme incorporated with a fuzzy classifier that is optimized by a genetic algorithm. The fractal image compression scheme requires to find matching range blocks to domain blocks from all the possible division of an image into subblocks. With suitable classification of the subblocks by a fuzzy classifier we can reduce the search time for this matching process so as to speedup the encoding process in the scheme. Implementation results show that by introducing three image classes and using fuzzy classifier optimized by a genetic algorithm the encoding process can be speedup by about 40% of an unclassified encoding system.     

Physicochemical Methods for Prediction of Functional Information for Proteins

Structural genomics initiatives are determining thousands of new protein structures. Many of these structures are of unknown function, and computational methods for the rapid determination of functional information from protein structure are needed. We present details of how functional information is obtained from the structure using THEMATICS (Theoretical Microscopic Titration Curves). THEMATICS is a computational procedure that gives information about chemical reactivity, based on solution of the Poisson-Boltzmann equations for the electrical potential function. We show how anomalies in predicted titration curves are established. We show further that when residues with anomalous predicted titration curves form a cluster in physical space, these residues tend to be very highly conserved across species and such clusters are reliable predictors of the active site. Results are given for ten enzymes; detailed results are shown for the enzymes triosephosphate isomerase (from chicken), 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (from E. coli), and papain (from papaya).     

TopCat: data mining for topic identification in a text corpus

TopCat (topic categories) is a technique for identifying topics that recur in articles in a text corpus. Natural language processing techniques are used to identify key entities in individual articles, allowing us to represent an article as a set of items. This allows us to view the problem in a database/data mining context: Identifying related groups of items. We present a novel method for identifying related items based on traditional data mining techniques. Frequent itemsets are generated from the groups of items, followed by clusters formed with a hypergraph partitioning scheme. We present an evaluation against a manually categorized ground truth news corpus; it shows this technique is effective in identifying topics in collections of news articles.     

Combating discrimination using Bayesian networks

Discrimination in decision making is prohibited on many attributes (religion, gender, etc…), but often present in historical decisions. Use of such discriminatory historical decision making as training data can perpetuate discrimination, even if the protected attributes are not directly present in the data. This work focuses on discovering discrimination in instances and preventing discrimination in classification. First, we propose a discrimination discovery method based on modeling the probability distribution of a class using Bayesian networks. This measures the effect of a protected attribute (e.g., gender) in a subset of the dataset using the estimated probability distribution (via a Bayesian network). Second, we propose a classification method that corrects for the discovered discrimination without using protected attributes in the decision process. We evaluate the discrimination discovery and discrimination prevention approaches on two different datasets. The empirical results show that a substantial amount of discrimination identified in instances is prevented in future decisions.