Stereo and motion parallax cues in human 3D vision: can they vanish without a trace?

In an immersive virtual reality environment, subjects fail to notice when a scene expands or contracts around them, despite correct and consistent information from binocular stereopsis and motion parallax, resulting in gross failures of size constancy (A. Glennerster, L. Tcheang, S. J. Gilson, A. W. Fitzgibbon, & A. J. Parker, 2006). We determined whether the integration of stereopsis/motion parallax cues with texture-based cues could be modified through feedback. Subjects compared the size of two objects, each visible when the room was of a different size. As the subject walked, the room expanded or contracted, although subjects failed to notice any change. Subjects were given feedback about the accuracy of their size judgments, where the “correct” size setting was defined either by texture-based cues or (in a separate experiment) by stereo/motion parallax cues. Because of feedback, observers were able to adjust responses such that fewer errors were made. For texture-based feedback, the pattern of responses was consistent with observers weighting texture cues more heavily. However, for stereo/motion parallax feedback, performance in many conditions became worse such that, paradoxically, biases moved away from the point reinforced by the feedback. This can be explained by assuming that subjects remap the relationship between stereo/motion parallax cues and perceived size or that they develop strategies to change their criterion for a size match on different trials. In either case, subjects appear not to have direct access to stereo/motion parallax cues.

Time patterns in UK demand for alcohol and tobacco: an application of the EM algorithm

Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

Use of a novel Hill-climbing genetic algorithm in protein folding simulations

We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

Rovibrational energy levels of hydrogen peroxide, studied by MULTIMODE with a reaction path Hamiltonian

Recently. Carter and Handy [J. Chem. Phys. 113 (2000) 987] have introduced the theory of the reaction path Hamiltonian (RPH) [J. Chem. Phys. 72 (1980) 99] into the variational scheme MULTIMODE, for the calculation of the J = 0 vibrational levels of polyatomic molecules, which have a single large-amplitude motion. In this theory the reaction path coordinate s becomes the fourth dimension of the moment-of-inertia tensor, and must be treated separately from the remaining 3N - 7 normal coordinates in the MULTIMODE program. In the modified program, complete integration is performed over s, and the M-mode MULTIMODE coupling approximation for the evaluation of the matrix elements applies only to the 3N - 7 normal coordinates. In this paper the new algorithm is extended to the calculation of rotational-vibration energy levels (i.e. J > 0) with the RPH, following from our analogous implementation for rigid molecules [Theoret. Chem. Acc. 100 (1998) 191]. The full theory is given, and all extra terms have been included to give the exact kinetic energy operator. In order to validate the new code, we report studies on hydrogen peroxide (H2O2), where the reaction path is equivalent to torsional motion. H2O2 has previously been studied variationally using a valence coordinate Hamiltonian; complete agreement for calculated rovibrational levels is obtained between the previous results and those from the new code, using the identical potential surface. MULTIMODE is now able to calculate rovibrational levels for polyatomic molecules which have one large-amplitude motion. (C) 2003 Elsevier B.V. All rights reserved.

Large vibrational variational calculations using 'multimode' and an iterative diagonalization technique

We have favoured the variational (secular equation) method for the determination of the (ro-) vibrational energy levels of polyatomic molecules. We use predominantly the Watson Hamiltonian in normal coordinates and an associated given potential in the variational code 'Multimode'. The dominant cost is the construction and diagonalization of matrices of ever-increasing size. Here we address this problem, using pertubation theory to select dominant expansion terms within the Davidson-Liu iterative diagonalization method. Our chosen example is the twelve-mode molecule methanol, for which we have an ab initio representation of the potential which includes the internal rotational motion of the OH group relative to CH3. Our new algorithm allows us to obtain converged energy levels for matrices of dimensions in excess of 100 000.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

The integration of figurative language and static depictions: an eye movement study of fictive motion

Do we view the world differently if it is described to us in figurative rather than literal terms? An answer to this question would reveal something about both the conceptual representation of figurative language and the scope of top-down influences oil scene perception. Previous work has shown that participants will look longer at a path region of a picture when it is described with a type of figurative language called fictive motion (The road goes through the desert) rather than without (The road is in the desert). The current experiment provided evidence that such fictive motion descriptions affect eye movements by evoking mental representations of motion. If participants heard contextual information that would hinder actual motion, it influenced how they viewed a picture when it was described with fictive motion. Inspection times and eye movements scanning along the path increased during fictive motion descriptions when the terrain was first described as difficult (The desert is hilly) as compared to easy (The desert is flat); there were no such effects for descriptions without fictive motion. It is argued that fictive motion evokes a mental simulation of motion that is immediately integrated with visual processing, and hence figurative language can have a distinct effect on perception. (c) 2005 Elsevier B.V. All rights reserved.

Spatial offset of test field elements from surround elements affects the strength of motion aftereffects

Static movement aftereffects (MAEs) were measured after adaptation to vertical square-wave luminance gratings drifting horizontally within a central window in a surrounding stationary vertical grating. The relationship between the stationary test grating and the surround was manipulated by varying the alignment of the stationary stripes in the window and those in the surround, and the type of outline separating the window and the surround [no outline, black outline (invisible on black stripes), and red outline (visible throughout its length)]. Offsetting the stripes in the window significantly increased both the duration and ratings of the strength of MAEs. Manipulating the outline had no significant effect on either measure of MAE strength. In a second experiment, in which the stationary test fields alone were presented, participants judged how segregated the test field appeared from its surround. In contrast to the MAE measures, outline as well as offset contributed to judged segregation. In a third experiment, in which test-stripe offset wits systematically manipulated, segregation ratings rose with offset. However, MAE strength was greater at medium than at either small or large (180 degrees phase shift) offsets. The effects of these manipulations on the MAE are interpreted in terms of a spatial mechanism which integrates motion signals along collinear contours of the test field and surround, and so causes a reduction of motion contrast at the edges of the test field.

Humans ignore motion and stereo cues in favor of a fictional stable world

As we move through the world, our eyes acquire a sequence of images. The information from this sequence is sufficient to determine the structure of a three-dimensional scene, up to a scale factor determined by the distance that the eyes have moved [1, 2]. Previous evidence shows that the human visual system accounts for the distance the observer has walked [3,4] and the separation of the eyes [5-8] when judging the scale, shape, and distance of objects. However, in an immersive virtual-reality environment, observers failed to notice when a scene expanded or contracted, despite having consistent information about scale from both distance walked and binocular vision. This failure led to large errors in judging the size of objects. The pattern of errors cannot be explained by assuming a visual reconstruction of the scene with an incorrect estimate of interocular separation or distance walked. Instead, it is consistent with a Bayesian model of cue integration in which the efficacy of motion and disparity cues is greater at near viewing distances. Our results imply that observers are more willing to adjust their estimate of interocular separation or distance walked than to accept that the scene has changed in size.

Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

Perceived spatial displacement of motion-defined contours in peripheral vision

The perceived displacement of motion-defined contours in peripheral vision was examined in four experiments. In Experiment 1, in line with Ramachandran and Anstis' finding [Ramachandran, V. S., & Anstis, S. M. (1990). Illusory displacement of equiluminous kinetic edges. Perception, 19, 611-616], the border between a field of drifting dots and a static dot pattern was apparently displaced in the same direction as the movement of the dots. When a uniform dark area was substituted for the static dots, a similar displacement was found, but this was smaller and statistically insignificant. In Experiment 2, the border between two fields of dots moving in opposite directions was displaced in the direction of motion of the dots in the more eccentric field, so that the location of a boundary defined by a diverging pattern is perceived as more eccentric, and that defined by a converging as less eccentric. Two explanations for this effect (that the displacement reflects a greater weight given to the more eccentric motion, or that the region containing stronger centripetal motion components expands perceptually into that containing centrifugal motion) were tested in Experiment 3, by varying the velocity of the more eccentric region. The results favoured the explanation based on the expansion of an area in centripetal motion. Experiment 4 showed that the difference in perceived location was unlikely to be due to differences in the discriminability of contours in diverging and converging pattems, and confirmed that this effect is due to a difference between centripetal and centrifugal motion rather than motion components in other directions. Our result provides new evidence for a bias towards centripetal motion in human vision, and suggests that the direction of motion-induced displacement of edges is not always in the direction of an adjacent moving pattern. (C) 2008 Elsevier Ltd. All rights reserved.

Variable step LMS algorithm using the accumulated instantaneous error concept

The convergence speed of the standard Least Mean Square adaptive array may be degraded in mobile communication environments. Different conventional variable step size LMS algorithms were proposed to enhance the convergence speed while maintaining low steady state error. In this paper, a new variable step LMS algorithm, using the accumulated instantaneous error concept is proposed. In the proposed algorithm, the accumulated instantaneous error is used to update the step size parameter of standard LMS is varied. Simulation results show that the proposed algorithm is simpler and yields better performance than conventional variable step LMS.

Unsupervised genetic algorithm deployed for intrusion detection

This paper represents the first step in an on-going work for designing an unsupervised method based on genetic algorithm for intrusion detection. Its main role in a broader system is to notify of an unusual traffic and in that way provide the possibility of detecting unknown attacks. Most of the machine-learning techniques deployed for intrusion detection are supervised as these techniques are generally more accurate, but this implies the need of labeling the data for training and testing which is time-consuming and error-prone. Hence, our goal is to devise an anomaly detector which would be unsupervised, but at the same time robust and accurate. Genetic algorithms are robust and able to avoid getting stuck in local optima, unlike the rest of clustering techniques. The model is verified on KDD99 benchmark dataset, generating a solution competitive with the solutions of the state-of-the-art which demonstrates high possibilities of the proposed method.

A new algorithm for OFDM joint data detection and phase noise cancellation

This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.