Computing with noise: phase transitions in Boolean formulas

Computing circuits composed of noisy logical gates and their ability to represent arbitrary Boolean functions with a given level of error are investigated within a statistical mechanics setting. Existing bounds on their performance are straightforwardly retrieved, generalized, and identified as the corresponding typical-case phase transitions. Results on error rates, function depth, and sensitivity, and their dependence on the gate-type and noise model used are also obtained.

The readability of textual materials in biology

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On reliable computation by noisy random Boolean formulas

We study noisy computation in randomly generated k-ary Boolean formulas. We establish bounds on the noise level above which the results of computation by random formulas are not reliable. This bound is saturated by formulas constructed from a single majority-like gate. We show that these gates can be used to compute any Boolean function reliably below the noise bound.

Comparison of two formulas used to calculate summarized retinal vessel calibers

PURPOSE: To compare the Parr-Hubbard and Knudtson formulas to calculate retinal vessel calibers and to examine the effect of omitting vessels on the overall result. METHODS: We calculated the central retinal arterial equivalent (CRAE) and central retinal venular equivalent (CRVE) according to the formulas described by Parr-Hubbard and Knudtson including the six largest retinal arterioles and venules crossing through a concentric ring segment (measurement zone) around the optic nerve head. Once calculated, we removed one arbitrarily selected artery and one arbitrarily selected vein and recalculated all outcome parameters again for (1) omitting one artery only, (2) omitting one vein only, and (3) omitting one artery and one vein. All parameters were compared against each other. RESULTS: Both methods showed good correlation (r for CRAE = 0.58; r for CRVE = 0.84), but absolute values for CRAE and CRVE were significantly different from each other when comparing both methods (p < 0.000001): CRAE had higher values for the Parr-Hubbard (165 [±16] μm) method compared with the Knudtson method (148 [±15] μm). In addition, CRAE and CRVE values dropped for both methods when omitting one arbitrarily selected vessel each (all p < 0.000001). Arteriovenous ratio (AVR) calculations showed a similar change for both methods when omitting one vessel each: AVR decreased when omitting one arteriole whereas it increased when omitting one venule. No change, however, was observed for AVR calculated with six or five vessel pairs each. CONCLUSIONS: Although the absolute value for CRAE and CRVE is changing significantly depending on the number of vessels included, AVR appears to be comparable as long as the same number of arterioles and venules is included.

Semi-supervised learning of hierarchical latent trait models for data visualisation

An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteH_GTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKaban_pami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteH_GTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

Analysis and simulation of computer controlled cellular mobile radio systems

Cellular mobile radio systems will be of increasing importance in the future. This thesis describes research work concerned with the teletraffic capacity and the canputer control requirements of such systems. The work involves theoretical analysis and experimental investigations using digital computer simulation. New formulas are derived for the congestion in single-cell systems in which there are both land-to-mobile and mobile-to-mobile calls and in which mobile-to-mobile calls go via the base station. Two approaches are used, the first yields modified forms of the familiar Erlang and Engset formulas, while the second gives more complicated but more accurate formulas. The results of computer simulations to establish the accuracy of the formulas are described. New teletraffic formulas are also derived for the congestion in multi -cell systems. Fixed, dynamic and hybrid channel assignments are considered. The formulas agree with previously published simulation results. Simulation programs are described for the evaluation of the speech traffic of mobiles and for the investigation of a possible computer network for the control of the speech traffic. The programs were developed according to the structured progranming approach leading to programs of modular construction. Two simulation methods are used for the speech traffic: the roulette method and the time-true method. The first is economical but has some restriction, while the second is expensive but gives comprehensive answers. The proposed control network operates at three hierarchical levels performing various control functions which include: the setting-up and clearing-down of calls, the hand-over of calls between cells and the address-changing of mobiles travelling between cities. The results demonstrate the feasibility of the control netwvork and indicate that small mini -computers inter-connected via voice grade data channels would be capable of providing satisfactory control

Accuracy of cornea and lens biometry using anterior segment optical coherence tomography

We assess the accuracy of the Visante anterior segment optical coherence tomographer (AS-OCT) and present improved formulas for measurement of surface curvature and axial separation. Measurements are made in physical model eyes. Accuracy is compared for measurements of corneal thickness (d1) and anterior chamber depth (d2) using-built-in AS-OCT software versus the improved scheme. The improved scheme enables measurements of lens thickness (d 3) and surface curvature, in the form of conic sections specified by vertex radii and conic constants. These parameters are converted to surface coordinates for error analysis. The built-in AS-OCT software typically overestimates (mean±standard deviation(SD)]d1 by +62±4 μm and d2 by +4±88μm. The improved scheme reduces d1 (-0.4±4 μm) and d2 (0±49 μm) errors while also reducing d3 errors from +218±90 (uncorrected) to +14±123 μm (corrected). Surface x coordinate errors gradually increase toward the periphery. Considering the central 6-mm zone of each surface, the x coordinate errors for anterior and posterior corneal surfaces reached +3±10 and 0±23 μm, respectively, with the improved scheme. Those of the anterior and posterior lens surfaces reached +2±22 and +11±71 μm, respectively. Our improved scheme reduced AS-OCT errors and could, therefore, enhance pre- and postoperative assessments of keratorefractive or cataract surgery, including measurement of accommodating intraocular lenses. © 2007 Society of Photo-Optical Instrumentation Engineers.

Phase transitions and memory effects in the dynamics of Boolean networks

The generating functional method is employed to investigate the synchronous dynamics of Boolean networks, providing an exact result for the system dynamics via a set of macroscopic order parameters. The topology of the networks studied and its constituent Boolean functions represent the system's quenched disorder and are sampled from a given distribution. The framework accommodates a variety of topologies and Boolean function distributions and can be used to study both the noisy and noiseless regimes; it enables one to calculate correlation functions at different times that are inaccessible via commonly used approximations. It is also used to determine conditions for the annealed approximation to be valid, explore phases of the system under different levels of noise and obtain results for models with strong memory effects, where existing approximations break down. Links between Boolean networks and general Boolean formulas are identified and results common to both system types are highlighted. © 2012 Copyright Taylor and Francis Group, LLC.

Damping in zinc-based alloys

The damping behaviour of the cold chamber pressure-die-casting alloy: M3, ZA8, ZA27, ZM11, Cosmal, Supercosmal and newly developed ZA27H1 and ZA27H2 was investigated at room temperature and elevated temperatures of up to 90 degrees C. The damping properties of the alloys were established at all temperatures. Formulas were established to predict damping properties of each alloy at any given temperature. The prediction formulae were found to be very accurate. All of the experimental alloys were heterogenous with varying microstructure and grain size; this was the major contribution and dominated the damping properties of the alloys. Super cosmal and ZA27 possessed the highest tensile strength but ZA27H1, ZA27H2 and ZM11 showed the highest damping properties. The relationship between microstructure and damping capacity of all alloys was also examined using back-scattered electron on the SEM. Further more detailed examinations of the microstructures of alloys ZM11, Cosmal and Supercosmal were carried out on the transmission electron microscope in order to establish the phases present in all alloys. These helped to obtain the mechanism of damping in the experimental alloys. The main damping mechanism in most of the experimental alloys was due to grain-boundary-sliding. Micro structural examinations also revealed the absence of -phase in the Cosmal and Supercosmal. This was thought to be due to a change in solid solubility of the alloys, which could have been caused by the addition of Si.

Dynamics of Boolean networks: an exact solution

The dynamics of Boolean networks (BN) with quenched disorder and thermal noise is studied via the generating functional method. A general formulation, suitable for BN with any distribution of Boolean functions, is developed. It provides exact solutions and insight into the evolution of order parameters and properties of the stationary states, which are inaccessible via existing methodology. We identify cases where the commonly used annealed approximation is valid and others where it breaks down. Broader links between BN and general Boolean formulas are highlighted.

Analyzing MSI rules for the USA extracted from a feedforward neural network

This paper introduces a mechanism for generating a series of rules that characterize the money price relationship for the USA, defined as the relationship between the rate of growth of the money supply and inflation. Monetary component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of the monetary component dataset.

Doctoral work in translation studies as an interdisciplinary mutual learning process:how a translator, teacher educator and linguistic typologist worked together

The focus of this paper is on the doctoral research training experienced by one of the authors and the ways in which the diverse linguistic and disciplinary perspectives of her two supervisors (co-authors of this paper) mediated the completion of her study. The doctoral candidate is a professional translator/interpreter and translation teacher. The paper describes why and how she identified her research area and then focused on the major research questions in collaboration with her two supervisors, who brought their differing perspectives from the field of linguistics to this translation research, even though they are not translators by profession or disciplinary background and do not speak Korean. In addition, the discussion considers the focus, purpose and theoretical orientation of the research itself (which addressed questions of readability in translated English-Korean texts through detailed analysis of a corpus and implications for professional translator training) as well as the supervisory and conceptual processes and practices involved. The authors contend that doctoral research of this kind can be seen as a mutual learning process and that inter-disciplinary research can make a contribution not only to the development of rigorous research in the field of translation studies but also to the other disciplinary fields involved.

Man, I feel like a woman:when and how gender-role motivation helps mind-reading

Two experiments were undertaken with 3 goals: (a) to determine whether manipulating the desirability of including empathy as part of one's gender-role identity motivates accurate mind-reading, (b) to ascertain whether target readability moderates the strength of this effect, and (c) to test whether these effects are mediated by the complexity of perceivers' inferential strategies. Participants viewed videotapes of 2 couples discussing relationship problems and attempted to infer each partner's thoughts and feelings. Both experiments demonstrated that motivation improved accuracy when male and female perceivers valued the empathy-relevant aspects of the traditional female gender role. However, as predicted, high levels of motivation facilitated the accurate reading of easy targets but not of difficult targets. Several mediational models were tested, the results of which showed that the complexity of perceivers' attributions mediated the link between motivation and mind-reading accuracy.

Reading without central vision:effects of text spacing on reading in patients with macular disease

Abstract: Loss of central vision caused by age-related macular degeneration (AMD) is a problem affecting increasingly large numbers of people within the ageing population. AMD is the leading cause of blindness in the developed world, with estimates of over 600,000 people affected in the UK . Central vision loss can be devastating for the sufferer, with vision loss impacting on the ability to carry out daily activities. In particular, inability to read is linked to higher rates of depression in AMD sufferers compared to age-matched controls. Methods to improve reading ability in the presence of central vision loss will help maintain independence and quality of life for those affected. Various attempts to improve reading with central vision loss have been made. Most textual manipulations, including font size, have led to only modest gains in reading speed. Previous experimental work and theoretical arguments on spatial integrative properties of the peripheral retina suggest that ‘visual crowding’ may be a major factor contributing to inefficient reading. Crowding refers to the phenomena in which juxtaposed targets viewed eccentrically may be difficult to identify. Manipulating text spacing of reading material may be a simple method that reduces crowding and benefits reading ability in macular disease patients. In this thesis the effect of textual manipulation on reading speed was investigated, firstly for normally sighted observers using eccentric viewing, and secondly for observers with central vision loss. Test stimuli mimicked normal reading conditions by using whole sentences that required normal saccadic eye movements and observer comprehension. Preliminary measures on normally-sighted observers (n = 2) used forced-choice procedures in conjunction with the method of constant stimuli. Psychometric functions relating the proportion of correct responses to exposure time were determined for text size, font type (Lucida Sans and Times New Roman) and text spacing, with threshold exposure time (75% correct responses) used as a measure of reading performance. The results of these initial measures were used to derive an appropriate search space, in terms of text spacing, for assessing reading performance in AMD patients. The main clinical measures were completed on a group of macular disease sufferers (n=24). Firstly, high and low contrast reading acuity and critical print size were measured using modified MNREAD test charts, and secondly, the effect of word and line spacing was investigated using a new test, designed specifically for this study, called the Equal Readability Passages (ERP) test. The results from normally-sighted observers were in close agreement with those from the group of macular disease sufferers. Results show that: (i) optimum reading performance was achieved when using both double line and double word spacing; (ii) the effect of line spacing was greater than the effect of word spacing (iii) a text size of approximately 0.85o is sufficiently large for reading at 5o eccentricity. In conclusion, the results suggest that crowding is detrimental to reading with peripheral vision, and its effects can be minimized with a modest increase in text spacing.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.