Seeing light vs dark lines: psychophysical performance is based on separate channels, limited by noise and uncertainty

Visual detection performance (d') is usually an accelerating function of stimulus contrast, which could imply a smooth, threshold-like nonlinearity in the sensory response. Alternatively, Pelli (1985 Journal of the Optical Society of America A 2 1508 - 1532) developed the 'uncertainty model' in which responses were linear with contrast, but the observer was uncertain about which of many noisy channels contained the signal. Such internal uncertainty effectively adds noise to weak signals, and predicts the nonlinear psychometric function. We re-examined these ideas by plotting psychometric functions (as z-scores) for two observers (SAW, PRM) with high precision. The task was to detect a single, vertical, blurred line at the fixation point, or identify its polarity (light vs dark). Detection of a known polarity was nearly linear for SAW but very nonlinear for PRM. Randomly interleaving light and dark trials reduced performance and rendered it non-linear for SAW, but had little effect for PRM. This occurred for both single-interval and 2AFC procedures. The whole pattern of results was well predicted by our Monte Carlo simulation of Pelli's model, with only two free parameters. SAW (highly practised) had very low uncertainty. PRM (with little prior practice) had much greater uncertainty, resulting in lower contrast sensitivity, nonlinear performance, and no effect of external (polarity) uncertainty. For SAW, identification was about v2 better than detection, implying statistically independent channels for stimuli of opposite polarity, rather than an opponent (light - dark) channel. These findings strongly suggest that noise and uncertainty, rather than sensory nonlinearity, limit visual detection.

Techno-economic assessment and uncertainty analysis of thermochemical processes for second generation biofuels

Biomass-To-Liquid (BTL) is one of the most promising low carbon processes available to support the expanding transportation sector. This multi-step process produces hydrocarbon fuels from biomass, the so-called “second generation biofuels” that, unlike first generation biofuels, have the ability to make use of a wider range of biomass feedstock than just plant oils and sugar/starch components. A BTL process based on gasification has yet to be commercialized. This work focuses on the techno-economic feasibility of nine BTL plants. The scope was limited to hydrocarbon products as these can be readily incorporated and integrated into conventional markets and supply chains. The evaluated BTL systems were based on pressurised oxygen gasification of wood biomass or bio-oil and they were characterised by different fuel synthesis processes including: Fischer-Tropsch synthesis, the Methanol to Gasoline (MTG) process and the Topsoe Integrated Gasoline (TIGAS) synthesis. This was the first time that these three fuel synthesis technologies were compared in a single, consistent evaluation. The selected process concepts were modelled using the process simulation software IPSEpro to determine mass balances, energy balances and product distributions. For each BTL concept, a cost model was developed in MS Excel to estimate capital, operating and production costs. An uncertainty analysis based on the Monte Carlo statistical method, was also carried out to examine how the uncertainty in the input parameters of the cost model could affect the output (i.e. production cost) of the model. This was the first time that an uncertainty analysis was included in a published techno-economic assessment study of BTL systems. It was found that bio-oil gasification cannot currently compete with solid biomass gasification due to the lower efficiencies and higher costs associated with the additional thermal conversion step of fast pyrolysis. Fischer-Tropsch synthesis was the most promising fuel synthesis technology for commercial production of liquid hydrocarbon fuels since it achieved higher efficiencies and lower costs than TIGAS and MTG. None of the BTL systems were competitive with conventional fossil fuel plants. However, if government tax take was reduced by approximately 33% or a subsidy of £55/t dry biomass was available, transport biofuels could be competitive with conventional fuels. Large scale biofuel production may be possible in the long term through subsidies, fuels price rises and legislation.

Risk and uncertainty in supply markets and sustainability-related innovation

tentially valuable innovations. In energy policy, much attention is given to analysing and incentivising customer demand, but new technologies also need new supply markets, to provide products and services to build, operate and maintain the innovative technology. This paper addresses the impact of supply constraints on the long-term viability of sustainability related innovations, using the case of energy from waste (EfW). Uncertainties in the pricing and availability of feedstock (i.e. waste) deter potential investors in EfW projects. We draw on prior supply management research to conceptualise the problem, and identify what steps might be taken to address it. Based on this analysis, we propose a research agenda aimed at purchasing and supply scholars and centred on the need to understand better how markets evolve and how stakeholders can (legitimately) influence the evolution of supply markets to support the adoption of sustainability related innovation. Within this broad case, specific themes are recommended for further investigation.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

A hybrid measurement systems analysis and uncertainty of measurement approach for industrial measurement in the light controlled factory

The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.

The framework of the virtual laser tracker - A systematic approach to the assessment of error sources and uncertainty in laser tracker measurement

Laser trackers have been widely used in many industries to meet increasingly high accuracy requirements. In laser tracker measurement, it is complex and difficult to perform an accurate error analysis and uncertainty evaluation. This paper firstly reviews the working principle of single beam laser trackers and state-of- The- Art of key technologies from both industrial and academic efforts, followed by a comprehensive analysis of uncertainty sources. A generic laser tracker modelling method is formulated and the framework of the virtual tracker is proposed. The VLS can be used for measurement planning, measurement accuracy optimization and uncertainty evaluation. The completed virtual laser tracking system should take all the uncertainty sources affecting coordinate measurement into consideration and establish an uncertainty model which will behave in an identical way to the real system. © Springer-Verlag Berlin Heidelberg 2010.

Probabilistic uncertainty in an interoperable framework

This thesis provides an interoperable language for quantifying uncertainty using probability theory. A general introduction to interoperability and uncertainty is given, with particular emphasis on the geospatial domain. Existing interoperable standards used within the geospatial sciences are reviewed, including Geography Markup Language (GML), Observations and Measurements (O&M) and the Web Processing Service (WPS) specifications. The importance of uncertainty in geospatial data is identified and probability theory is examined as a mechanism for quantifying these uncertainties. The Uncertainty Markup Language (UncertML) is presented as a solution to the lack of an interoperable standard for quantifying uncertainty. UncertML is capable of describing uncertainty using statistics, probability distributions or a series of realisations. The capabilities of UncertML are demonstrated through a series of XML examples. This thesis then provides a series of example use cases where UncertML is integrated with existing standards in a variety of applications. The Sensor Observation Service - a service for querying and retrieving sensor-observed data - is extended to provide a standardised method for quantifying the inherent uncertainties in sensor observations. The INTAMAP project demonstrates how UncertML can be used to aid uncertainty propagation using a WPS by allowing UncertML as input and output data. The flexibility of UncertML is demonstrated with an extension to the GML geometry schemas to allow positional uncertainty to be quantified. Further applications and developments of UncertML are discussed.

Theory and data for area summation of contrast with and without uncertainty:evidence for a noisy energy model

Contrast sensitivity improves with the area of a sine-wave grating, but why? Here we assess this phenomenon against contemporary models involving spatial summation, probability summation, uncertainty, and stochastic noise. Using a two-interval forced-choice procedure we measured contrast sensitivity for circular patches of sine-wave gratings with various diameters that were blocked or interleaved across trials to produce low and high extrinsic uncertainty, respectively. Summation curves were steep initially, becoming shallower thereafter. For the smaller stimuli, sensitivity was slightly worse for the interleaved design than for the blocked design. Neither area nor blocking affected the slope of the psychometric function. We derived model predictions for noisy mechanisms and extrinsic uncertainty that was either low or high. The contrast transducer was either linear (c1.0) or nonlinear (c2.0), and pooling was either linear or a MAX operation. There was either no intrinsic uncertainty, or it was fixed or proportional to stimulus size. Of these 10 canonical models, only the nonlinear transducer with linear pooling (the noisy energy model) described the main forms of the data for both experimental designs. We also show how a cross-correlator can be modified to fit our results and provide a contemporary presentation of the relation between summation and the slope of the psychometric function.

Area summation in human vision at and above detection threshold

The initial image-processing stages of visual cortex are well suited to a local (patchwise) analysis of the viewed scene. But the world's structures extend over space as textures and surfaces, suggesting the need for spatial integration. Most models of contrast vision fall shy of this process because (i) the weak area summation at detection threshold is attributed to probability summation (PS) and (ii) there is little or no advantage of area well above threshold. Both of these views are challenged here. First, it is shown that results at threshold are consistent with linear summation of contrast following retinal inhomogeneity, spatial filtering, nonlinear contrast transduction and multiple sources of additive Gaussian noise. We suggest that the suprathreshold loss of the area advantage in previous studies is due to a concomitant increase in suppression from the pedestal. To overcome this confound, a novel stimulus class is designed where: (i) the observer operates on a constant retinal area, (ii) the target area is controlled within this summation field, and (iii) the pedestal is fixed in size. Using this arrangement, substantial summation is found along the entire masking function, including the region of facilitation. Our analysis shows that PS and uncertainty cannot account for the results, and that suprathreshold summation of contrast extends over at least seven target cycles of grating. © 2007 The Royal Society.

Neuronal convergence in early contrast vision: binocular summation is followed by response nonlinearity and area summation

We assessed summation of contrast across eyes and area at detection threshold ( C t). Stimuli were sine-wave gratings (2.5 c/deg) spatially modulated by cosine- and anticosine-phase raised plaids (0.5 c/deg components oriented at ±45°). When presented dichoptically the signal regions were interdigitated across eyes but produced a smooth continuous grating following their linear binocular sum. The average summation ratio ( C t1/([ C t1+2]) for this stimulus pair was 1.64 (4.3 dB). This was only slightly less than the binocular summation found for the same patch type presented to both eyes, and the area summation found for the two different patch types presented to the same eye. We considered 192 model architectures containing each of the following four elements in all possible orders: (i) linear summation or a MAX operator across eyes, (ii) linear summation or a MAX operator across area, (iii) linear or accelerating contrast transduction, and (iv) additive Gaussian, stochastic noise. Formal equivalences reduced this to 62 different models. The most successful four-element model was: linear summation across eyes followed by nonlinear contrast transduction, linear summation across area, and late noise. Model performance was enhanced when additional nonlinearities were placed before binocular summation and after area summation. The implications for models of probability summation and uncertainty are discussed.

Bit-error probability for direct detection of optical RZ signal degraded by ASE noise and timing jitter

We analyze theoretically the interplay between optical return-to-zero signal degradation due to timing jitter and additive amplified-spontaneous-emission noise. The impact of these two factors on the performance of a square-law direct detection receiver is also investigated. We derive an analytical expression for the bit-error probability and quantitatively determine the conditions when the contributions of the effects of timing jitter and additive noise to the bit error rate can be treated separately. The analysis of patterning effects is also presented. © 2007 IEEE.

Transaction attributes and buyer-supplier relationships in AMT acquisition and implementation:the case of Malaysia

This paper explores how transaction attributes of technology affect differences in the relationship between technology buyers and suppliers. It also examines the impact on performance of different patterns of relationship between technology buyers and suppliers. Data obtained from 147 manufacturing firms in Malaysia are used to test several hypotheses, which were derived from a review of the literature on technology, transaction cost theory and buyer–supplier relationships (BSR). The research results indicate that the higher the level of technological complexity, specificity and uncertainty, the more firms are likely to engage in a closer relationship with technology suppliers. Even though the majority of firms reported improvements in their performance, results indicate that firms demonstrating a closer relationship with technology suppliers are more likely to achieve higher levels of performance than those that do not. It is also shown that with high levels of transaction attribute, implementation performance suffers more when firms have weak relationships with technology suppliers than with moderate and low levels of transaction attribute.

The precursors and impacts of BSR on AMT acquisition and implementation

This paper reports on the results of research into the connections between transaction attributes and buyer-supplier relationships (BSRs) in advanced manufacturing technology (AMT) acquisition and implementation. The investigation began by examining the impact of the different patterns of BSR on the performance of the AMT acquisition. In understanding the phenomena, the study drew upon and integrated the literature of transaction cost economics theory, BSRs, and AMT, and used this as the basis for a theoretical framework and hypotheses development. This framework was then empirically tested using data that were gathered through a questionnaire survey with 147 companies and analyzed using a structural equation modeling technique. The results of the analysis indicated that the higher the level of technological specificity and uncertainty, the more firms are likely to engage in a stronger relationship with technology suppliers. However, the complexity of the technology being implemented was associated with BSR only indirectly through its association with the level of uncertainty (which has a direct impact upon BSR). The analysis also provided strong support for the premise that developing strong BSR could lead to an improved performance in acquiring and implementing AMT. The implications of the study are offered for both the academic and practitioner audience.

Risk-based maintenance model for offshore oil and gas pipelines:a case study

Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.