TRIZ methods applied to the analysis of disruption in the marketplace

Unidentified risks, also known as unknown unknowns, have traditionally been underemphasized by risk management. Most unknown unknowns are believed to be impossible to find or imagine in advance. But this study reveals that many are not truly unidentifiable. This study develops a model using separation principles of the Theory of Inventive Problem Solving (whose Russian acronym is TRIZ) to explain the mechanism that makes some risks hard to find in advance and show potential areas for identifying hidden risks. The separation principles used in the model are separation by time, separation by space, separation upon condition, separation between parts and whole, and separation by perspective. It shows that some risks are hard to identify because of hidden assumptions and illustrates how separation principles can be used to formulate assumptions behind what is already known, show how the assumptions can be broken, and thus identify hidden risks. A case study illustrates how the model can be applied to the Deepwater Horizon oil spill and explains why some risks in the oil rig, which were identified after the incident, were not identified in advance.

Using Bayesian belief networks for reliability management : construction and evaluation: a step by step approach

Spatiotemporal pattern of phenology across geographic gradients in insects

Data Assimilation for Marine Ecosystem Models

Variable eating quality was identified as a major contributor to declining Australian beef consumption in the early 1990s. The primary issue was the inability to predict the eating quality of cooked beef before consumption. A R&D program funded by industry and Meat and Livestock Australia investigated the relationships between critical control points along the supply chain, cooking methods and beef palatability. These relationships were underpinned by extensive consumer taste panels. Out of this R&D grew the Meat Standards Australia (MSA) voluntary meat grading system which aimed at predicting consumer palatability scores of cooked beef. Quality was defined on the basis of one of four grades. The grading model predicts consumer scores for 135 ‘cut by cooking method’ combinations for each graded carcass. The MSA system commenced in 1999/2000 and at present some 850,000 cattle are graded annually, about 25% of the total domestic kill. This paper first describes the evolution of the MSA grading scheme and its adoption by industry. Next, evidence is presented relating to consumers’ willingness to pay (WTP) for guaranteed eating quality, the premiums that Australian consumers have actually paid for MSA graded cuts, and the extent to which premiums paid by consumers are transmitted back along the value chain to cattle producers. WTP data collected during exit surveys from taste panels in Australia, the United States, Japan and Ireland showed that consumers were willing to pay more for premium quality. However, whilst MSA has the capacity for four quality grades, it is mostly used to simply discriminate between ungraded and graded product (ie 3 star or better). A survey of Australian beef retailers and wholesalers suggested that from 2004/05 to 2007/08, beef consumers were prepared to pay around $0.32/kg extra for MSA branded beef on a carcass weight equivalent basis. Retailers kept about $0.06/kg and wholesalers kept about $0.12/kg. The remaining $0.14/kg was passed back to cattle producers. Despite accelerated use of MSA in the wholesale trade, visibility at retail is generally low. It is being used predominantly to support private brand initiatives or to underpin existing channel partner offers. The paper concludes by discussing two case studies of business models that small niche beef retailers have developed to further capture the benefits from the MSA scheme through introduction of private brands. In summary, the MSA innovation has resulted in a higher degree of accuracy in the ability to predict beef eating quality for consumers. This has improved consumer choice, opportunities for value adding, and sufficient transmission of the premiums paid by consumers for graded cuts to provide real incentives for beef producers to supply MSAcompliant cattle.

A challenge for ecology is to understand the structure and function of ecological communities. While studies of particular species and ecosystems underpin much of ecology, a deeper understanding requires knowledge of processes that are common to all ecological communities. I consider whether a fundamental understanding of ecology might be achieved through a focus on energy, which is common to all ecological systems. I use theory to predict the structure and function of ecological communities from thermodynamic first principles and I use data to determine whether ecological communities respond predictably to local environmental conditions. Much of my work considers the individual size distribution (ISD), which is the distribution of organism sizes in a community, irrespective of species identities. ISDs contain information on energy and resource use but also contain information on abundances and size diversity, which is considered to be a proxy for morphological and physiological trait diversity. For this reason, ISDs are suited to studying both the structure and function of ecological communities. I reviewed existing thermodynamic approaches to ecology and identified several theories but few empirical studies. I developed a broad thermodynamic principle that encompassed existing thermodynamic theories and I used this principle to generate predictions of ISDs. I extended this analysis to predict how organism and community energy use would scale with biomass. This analysis identified density-dependent energy use as a possible mechanism for many observed scaling relationships and generated predictions that were consistent with data on metabolic scaling relationships in organisms and communities. The study of links between ISDs and their local environmental conditions required statistical approaches that could incorporate functions as a response variable (function regression). I developed software for several function regression analyses and used this software to study ISDs along environmental gradients and through time. ISDs changed predictably along environmental gradients and through time, which suggests that consistent ecological rules might regulate ISDs. Changes in ISDs were compared to changes in species abundance distributions (SADs), which measure relative species abundances. ISDs changed more rapidly than SADs, which suggests that size diversity might respond more closely than species diversity to environmental conditions or to stochastic changes in species composition. Although a focus on body size might uncover important ecological processes, many applied ecologists are interested primarily in species-based measures (e.g., species richness). I extended the function regression analyses to test whether ISDs could predict variation in species richness and found strong links between species richness and ISDs. A species richness-ISD relationship suggests that changes in size diversity might underlie changes in species diversity. The results presented in this thesis support a greater focus on size-based measures alongside species-based measures in ecology. The inclusion of body size revealed links between community structure and function and highlighted that size-based measures might reflect changes in ecological communities that are missed by species-based measures. Rebuilding ecology around ISDs would bring together organism, population, community and ecosystem ecology and potentially may move ecologists closer to a fundamental and general understanding of the functioning of ecological systems.

th 1999 Many theorists emphasize the role of an “internal model of the world” in directing intelligent behavior. Internal models predict the evolution of the environment by imitating its causal flow. They compute prediction signals and use these prediction signals to form novel associative chains. Formation of such predictive chains may contribute to reasoning and planning. Animals seem to learn and use internal models; they learn to anticipate predictable events, and their behavior in latent learning experiments reflects formation of novel associative chains. Despite such behavioral evidence, the neural basis of an internal model is still under debate. In order to investigate possible neural correlates of an internal model, a previous model of animal learning was extended to an internal model approach. As believed to occur in animals, the proposed neural network model computes predictions and uses these predictions to form novel associative chains in a latent learning experiment. Simulated signals resembled anticipatory neural activity which has been reported in cortex, striatum, and midbrain dopamine neurons. Simulated prediction signals were comparable to tonic anticipatory activities in cortex and striatum. Furthermore, simulated reward prediction error signals were comparable to phasic activities of midbrain dopamine neurons. These findings suggest that tonic anticipatory activities can reflect prediction signals and that phasic anticipatory activities can reflect prediction error signals. Furthermore, comparison of the model architecture with biological neural networks suggests that chains of neurons with anticipatory activity underlie formation of novel associative chains. In conclusion, anticipatory activity seems to reflect the processing of an internal model.

Quantifying the relationship between subsolidus mantle convection and surface evolution is a fundamental goal of geophysics. Toward this goal progress has been slow due to incomplete knowledge of the earth’s internal structure and properties. While seismic tomography reveals details on internal 3D structure of the present mantle, evolution of the subsolidus mantle during the geological past remains elusive. This thesis attempts to solve the time inversion of mantle convection using the adjoint method based on present-day seismic images and geological and geophysical observations dictating the past evolution of solid earth. The adjoint method, widely used in meteorological and oceanographic predictions, can be applied to mantle convection for the recovery of unknown initial conditions through the assimilation of present-day mantle seismic structure. We propose that an optimal first guess to the initial condition can be obtained through a simple backward integration (SBI) of the governing equations thus lessening the computational expense. By incorporating time-dependent surface dynamic topography in addition to present-day mantle structure, the adjoint method is improved so as to constrain uncertain mantle dynamic properties and initial condition simultaneously. The theory is derived from the governing equations of mantle convection and validated by synthetic experiments for a single- and two-layer viscosity mantle within regionally bounded spherical shells. For both cases, we show that the theory can constrain mantle properties with errors arising through the adjoint recovery of the initial condition. For the two-layer model, there is a trade-off between the temperature scaling and lower mantle viscosity. By assimilating seismic structure and plate motions in the inverse mantle convection model, we reconstruct Farallon plate subduction back to 100 Ma. We put constraints on basic mantle properties, including both the depth dependence of mantle viscosity and slab buoyancy, by predicting proxies of dynamic topography evident in the stratigraphy of the North American Cretaceous western interior seaway. Models that fit stratigraphy well require the Farallon slab to have been flat lying in the Late Cretaceous, consistent with geological reconstructions. The models predict an extensive zone of shallow-dipping subduction extending beyond the flat-lying slab farther east and north, while the limited region of subducting flat slab resembles an oceanic plateau. In order to test the hypothesis of oceanic plateau subduction and its relationship to the Laramide orogeny, we compare the inverse convection model with plate reconstructions. Two prominent seismic anomalies on the Farallon plate recovered from inverse models coincide with paleogeographically-restored positions of conjugates to the Shatsky and Hess plateaus when they subducted beneath North America. The distributed shortening of the Laramide orogeny closely tracked the passage of the Shatsky conjugate beneath North America, while the effects of Hess conjugate subduction were restricted to the northern Mexico foreland belt. We find that Laramide uplifts were consequences of the removal, rather than the emplacement, of the Shatsky conjugate, and we predict that these subducted plateaus should be detectable by the USArray seismic experiment. The inverse convection models predict a continuous vertical motion history of western U.S., which is further validated by constraints on the vertical motion of the Colorado Plateau since the Cretaceous. With the arrival of the flat-lying Farallon slab, dynamic subsidence swept from west to east over the western U.S., peaking at 86 Ma within the Colorado Plateau. This eastward migrating dynamic subsidence is consistent with a recently compiled backstripping study that shows a long-wavelength residual subsidence shifting to the east, coincident with the passage of the flat slab beneath North America in our inverse model. Two stages of uplift followed the removal of the Farallon slab below the Colorado Plateau: one in the latest Cretaceous, and the other in the Eocene, with a cumulative uplift of ~1.2 km; the former represents the Laramide uplift which also marks the initial uplift of the entire western U.S. Both the descent of the slab and buoyant upwellings raised the Colorado Plateau to its current elevation during the Oligocene. A locally thick lithosphere enhances coupling to the upper mantle so that the Colorado Plateau has a higher topography with sharp edges. Our models also predict that the plateau tilted downward to the northeast before the Oligocene, caused by northeast-trending subduction of the Farallon slab, and that this northeast tilting diminished and reversed to the southwest during the Miocene in response to buoyant upwellings. Overall, this thesis shows that the adjoint models with data assimilation are useful in linking surface evolution to deep mantle processes both over North America and areas beyond. While more research is clearly needed to construct a more earth-like model, this thesis presents an important advance in data-oriented geodynamic models.

Forecasting the outcome of events that will happen in the future is a frequently indulged and important task for humans. Despite the ubiquity of the forecasts, predicting the outcome of future events is a challenging task for humans or even computers - it requires extremely complex calculations involving a reasonable amount of domain knowledge, significant amounts of information processing and accurate reasoning. Recently, a market-based paradigm called prediction markets has shown ample success to solve this problem by using the aggregated 'wisdom of the crowds' to predict the outcome of future events. This is evidenced from the successful predictions of actual events done by the Iowa Electronic Marketplace(IEM), Tradesports, Hollywood Stock Exchange, the Gates-Hillman market, etc., and by companies such as Hewlett Packard, Google and Yahoo's Yootles.

Exergy and Sustainability: Insights into the Value of Exergy Analysis in Sustainability Assessment of Technological Systems

Reservoir storage prediction is so crucial for water resources planning and managing water resources, drought risk management and flood predicting throughout the world. In this study, Gray Wolf Optimizer algorithm (GWO) was applied to predict Shaharchay dam reservoir storage of located in the Urmia Lake basin, northwest of Iran. The results of the GWO algorithm have been compared with the continuous genetic algorithm (CGA). The predicted values from the GWO algorithm matched the measured values very well. According to the results, the error is not significant (2.11%) in the implementation of the GWO and the correlation coefficient between the predicted and measured values is 0.92. In addition, the statistical criteria of RMSE, MAE and NSE for GWO algorithm were estimated to be 0.03, 0.41 and 0.74, respectively, indicated a satisfactory performance. Excessive value of correlation coefficient expresses that the GWO algorithm pretty suit the variables and may finally be used for predicting of reservoir storage for operational overall performance. Comparison of results showed that the GWO algorithm with average best objective function value of 121, 112 and 83.10 with a number of further evaluations of the objective function to achieve higher capacity is the optimum answer.

Problem Definition According to the World Health Organization, traffic injuries have become the eighth cause of death and the leading cause among children and young adults. Human error, and in particular perceptual error, is among the most frequently reported causes of road fatalities. The desire to reduce traffic fatalities has led to the development of automated driving, which promises revolutionary advances in driver safety, traffic capacity and driver convenience. Since true autonomy in mixed traffic has not yet been achieved, today's automated vehicles require the driver to continuously supervise the automation and to capably intervene when necessary. However, simulator studies and experiences from disciplines such as aviation and factories have demonstrated that humans are generally ill-equipped to monitor automation for longer periods. This raises the concern that partial automation may harm rather than help traffic safety if not designed to adequately support the drivers in their supervisory tasks. Research objectives To address this concern, further insights are needed in how drivers monitor automation in complex real-world traffic, and how their behaviour and performance change with long-term automated driving experience. This dissertation sets out to investigate how real-world automation changes the availability of attentional resources, to establish where and how drivers use automation in naturalistic conditions, and evaluate how these change with experience. While these objectives investigate periods of automated driving, vehicles with automated driving functionalities will often be driven manually, when outside the operational design domain or at the driver’s preference. In these conditions, the available automation may still outperform the driver on particular tasks, such as detecting and tracking surrounding road users without bias or distraction. This dissertation therefore also contributes to the search for ways in which automation can provide meaningful support to the traffic monitoring task in manual and supervised driving. To evaluate if and when supervised automated driving negatively affects the driver’s ability to monitor, mental workload is evaluated in a Tesla model S on public roads (Chapter 2). Voluntary automation use and attention are examined in a naturalistic driving study on public roads (Chapter 3). To evaluate the effect of experience with automated driving, Chapter 2 compares drivers with and without prior automation use, whereas Chapter 3 examines how behaviour changes over a two-month period, compared to one month of manual driving. Two studies are performed to examine how driving automation can support the driver with the monitoring task, for which an instrumented vehicle was extended with cameras which track the driver’s gaze and associate it to surrounding road users as detected by the vehicle perception. The first study (Chapter 4) investigates how well gaze behaviour can indicate driver awareness toward individual road users, and proposes a recognition task to obtain a ground truth for awareness of multiple other road-users. The second study (Chapter 5) evaluates if driver gaze and head pose can provide earlier predictions for emergency alerting and intervention systems. A crossing pedestrian collision risk prediction system is used as a case study where gaze and contextual cues are evaluated in their contribution to path and risk prediction using a dynamic Bayesian network. Findings & recommendations Chapter 2 found that workload differed between roads with high and low traffic complexity, both for manual and automated driving, which indicates that drivers remain sensitive to changes in task demand while supervising automated driving. Drivers with prior experience in automated driving perceived a lower workload while supervising automation compared to manual driving. No workload difference was perceived for first-time users. In contrast, attentional demand as measured by a detection-response task was higher during automation use compared to manual driving regardless of experience. This indicates that monitoring automation (SAE2) requires more mental capacity compared to manual driving, which suggests that in contrast to a wide range of studies, SAE2 can increase workload. Supervising automation may therefore be beneficial for driver attention, but perception of workload during supervision may be too low for this to occur naturally. Future work should consider calibrating workload perception and system limitation understanding rather than actual task demand to encourage attentive supervision. Chapter 3 shows that automation is mostly used on road types generally considered suitable for automated driving with only incidental use on urban roads. This suggests that users are adhering to the operational design domain of these vehicles. On highways, automation is used at all speeds, but less during short periods of slow driving. No time-in-drive, time-of-day or experience effects were found for automation use. On the highway, head pose deviation was smaller during automation use compared to manual driving but tended to increase over the first six weeks of use, which may indicate a change in monitoring strategy. Further research is needed to assess if this difference indicates better or worse monitoring behaviour. Chapter 4 found that drivers performed better on the recognition task when road users were relevant for the driven manoeuvre and when drivers had directed their gaze within 10 degrees of these road users. However, at least 18% of road users were recognised while only observed peripherally, suggesting that peripheral vision should not be neglected in attention monitoring. Recognition performance was not predicted by gaze metrics and requires further development to reduce forget rates. Further analysis is needed to compare the recognition task to established situation awareness measures after these improvements are obtained. Chapter 5 demonstrates that driver and pedestrian attention monitoring can provide a benefit to pedestrian crossing collision risk prediction when predicting further than 0.75 seconds ahead. The higher workload during supervised automation and the general adherence to the operational design domain in naturalistic driving indicate that supervising driving automation can be beneficial to driver attention and traffic safety, but literature and recent accidents demonstrate that challenges remain in encouraging such attentive behaviour. Strategies to encourage attentive supervision should therefore be further developed, as well as ways to maintain these strategies while automation technology improves in pursuit of the opposite objective to reduce engagement in the driving task. The joint analysis of driver gaze and road scene may improve driver support during manual driving and supervised automation, and benefit the development of automated driving. But care should be taken that systems which use driver attention or rely on other contextual cues do not become susceptible to the same mistakes as drivers tend to make. While careful design approaches can reduce the risk of mimicking human error, validation will ultimately require a reliable way to distinguish between awareness and inattentional blindness. The instrumentation and conducted studies with on-road automation demonstrate that on-road research is becoming more practical and accessible than ever before, thanks to recent developments in automation. The observation that during on-road automation, inexperienced drivers perceive higher workload compared to in simulators testifies for the importance of on-road driving research. Challenges encountered during the naturalistic study and attention study demonstrate that the instrumentation and processing have to be designed and tested carefully for on-road research to be effective.

Specific volume of polymers : influence of the thermomechanical history

Stochastic wave models play a central role in our present-day wave modelling capabilities. They are frequently used to compute wave statistics, to generate boundary conditions and to include wave effects in coupled model systems. Historically, such models were developed to predict the wave field evolution in deep water where the conditions of Gaussianity generally hold. However, in recent decades, such models have been applied to the shallower coastal environment where the stochastic representation of the dominant wave physics becomes questionable. This is primarily due to the increased influence of wave nonlinearity and the additional depth-induced wave processes that are dominant in this region.<br/><br/>Unfortunately, the two most dominant wave processes in the surf zone: depth-induced wave breaking and nonlinear triad wave-wave interactions are also the least well represented and understood. This is due to both their complexity and the scarcity of analytical solutions for realistic wave fields. As such, they represent a significant obstacle in the accurate modelling of the wave dynamics in the coastal region. Providing accurate representations of these wave processes is essential to answering the questions demanded from stochastic wave models from coastal engineers for coastal management and design. Such advancements are necessary to improve our understanding of wave-induced processes, to reduce costs in managing the coastal environment and to tackle contemporary issues such as uncertainties with respect to increased sea level rise.<br/><br/>Due to the complexity of depth-induced wave breaking, a complete representation of this wave process does not exist for both stochastic and deterministic modelling frameworks. Although there is extensive literature on the subject of parameterizing depth-induced wave breaking in a stochastic sense, these parameterizations are inconsistent with theory, observations and (deterministic) model predictions. In particular, present-day modelling defaults perform poorly over (near-)horizontal bathymetries with over-enhanced wave dissipation of locally-generated waves and insufficient dissipation of swell waves. Equally, nonlinear triad wave-wave interactions are poorly represented in stochastic wave models due to the problem of closure and the impractical computational expense of more accurate representations. In particular, the most commonly applied parameterization in the wave literature incorrectly predicts the evolution of the spectral shape, and the convergence to an equilibrium high-frequency tail deep in the surf zone. Correctly resolving these issues is essential for the management of many of the activities occurring at the coast; from the design of coastal defenses to feasibility studies for wave energy converters, from port operation and availability to vessel navigation, from understanding the ecology at the coast to the fisheries, and from managing leisure and tourism to safety at the coast.<br/><br/> In this work, we investigate the process of depth-induced wave breaking through a comprehensive analysis of the literature and a comparison of modelling performance. Here, we use an extensive set of wave observations representing a large range of wave conditions and bathymetric profiles. The analysis demonstrates that no currently available depth-induced breaking source term is capable of sufficiently representing the process of depth-induced wave breaking. This is shown to be in agreement with the wave literature with parameterizations either over-predicting wave dissipation for locally generated waves or under-predicting wave dissipation for non-locally generated waves over (near-)horizontal bathymetries. To address this issue, a new joint scaling using both local wave and bathymetric conditions is proposed. Using both the normalized characteristic wave number and local bottom slope unifies two approaches prevalent in the wave literature. This is shown to improve the model performance for the dissipation of both locally and non-locally generated waves over (near-)horizontal bathymetries. <br/><br/>Furthermore, the validity of the assumption that wave dissipation can be modelled as analogous to a 1D dissipative bore is explored. Subsequently, a heuristic directional modification is introduced for depth-induced wave breaking dissipation models. This directionally partitions the 2D spectrum into several directional partitions that are assumed to be unidirectional. Model results demonstrate that the effect of the directional partitioning is to reduce the dissipation of wave energy and to enhance the significant wave height; in agreement with field measurements. Not only is this modification shown to be applicable to the joint wave breaking parameterization proposed in this study, but also for well-established parameterizations. <br/><br/>The effects of both the proposed scaling and directional modification are then reviewed from an operational context and are compared to state-of-the-art source terms, field observations and a hypothetical storm representative of Dutch design conditions. Such design conditions are expected to be representative of design conditions found globally. In an environment where storm intensities may be increasing, for example due to global warming, the results of wave breaking models near the coast under such extreme conditions become of greater relevance. The influence of wave breaking models in coupled model systems is anticipated to provide important new insights in understanding the various wave-driven processes along our coasts. <br/><br/>Next, the representation of the nonlinear triad wave-wave interactions in stochastic wave models is reviewed. In particular, the collinear approximation used to transform 1D triad source terms for implementation in 2D stochastic wave models is revisited. These approximations are necessitated by considerations of computational efficiency. The conventional collinear approximation is shown to be inconsistent at the unidirectional limit and to be a primary source of modelling error. Instead of converging to the values predicted by the 1D triad source terms at the unidirectional limit, the energy transfers as computed by stochastic wave models are shown to become unbounded. This results in a dimensional calibration coefficient which is at least an order of magnitude smaller than that found in the wave literature. Consequently, for directional wave conditions, 1D triad source terms implemented with the conventional collinear approximation insufficiently capture the wave evolution. To address this problem, a new collinear approximation is presented which accounts for the wave energy contained within a finite directional bandwidth. This collinear approximation is shown to converge correctly at the unidirectional limit and to agree well with predictions from a second-order accurate deterministic wave model. In particular, better agreement is shown in the modelling prediction of the spectral shape and related integral parameters, e.g. wave period, under idealized wave conditions. Under certain conditions, these error reductions are shown to be more significant than differences between the underlying triad models.<br/><br/>The contribution of this work demonstrates that while the underlying theory underpinning stochastic wave modelling in the coastal environment still remains questionable, the accurate determination of wave statistics in the coastal zone is tenable. With the advancements presented in this study, the new source terms correspond better with the current wave literature and are shown to provide significant steps forward over existing default source terms. The developments presented here are anticipated to form the foundation for future source term research, and to be used for the representation of the dominant wave physics in the coastal environment in operational wave models.

Interorganisational new service development capability in the mobile communications ecosystem