This paper describes a probabilistic approach to the problem of recognizing places based on their appearance. The system we present is not limited to localization, but can determine that a new ...observation comes from a previously unseen place, and so augment its map. Effectively this is a SLAM system in the space of appearance. Our probabilistic approach allows us to explicitly account for perceptual aliasing in the environment—identical but indistinctive observations receive a low probability of having come from the same place. We achieve this by learning a generative model of place appearance. By partitioning the learning problem into two parts, new place models can be learned online from only a single observation of a place. The algorithm complexity is linear in the number of places in the map, and is particularly suitable for online loop closure detection in mobile robotics.
•Propose a real options based decision support tool to aid practical evaluation of R&D investments in technology.•Take explicit account of the technical risk in R&D, while market risk and ...learning-by-doing in operational technologies are also modelled.•Model R&D progress in a stylised logistic function form to give economic meaning.•Apply decision support tool for evaluating R&D investment potential in CO2 recycling technology.
We propose a practice relevant real options based decision support tool to aid in the practical evaluation of R&D investments in technology. Using a Poisson process to simulate the discrete progress typical of advancements in R&D, we take explicit account of the technical risk of the technology development, while market risk exposure and the effect of learning-by-doing through operating the technology is also explicitly modelled. We present a compound real option design, where a European real option structure is used to model the fixed length term typical of early phase research, which is exercisable into an American real option structure to model a subsequent phase R&D. In this latter phase, a successful outcome is acted upon immediately to operationalise the technology. We propose a simulation approach, which models R&D progress in a stylised logistic function or ’S-shape’ form, capturing the typically slow rate of R&D progress at the start of the early phase, through to more rapid improvement as the R&D advances, which then slows again as the limitations of the R&D are approached. We propose a business appropriate and workable economic meaning to this progress in the R&D process. We demonstrate the decision support tool with an application to evaluating the R&D investment potential in CO2 recycling technology, where an energy commodity is produced.
WTI and Brent futures are tested for the presence of psychological barriers around $10 price levels, applying a multiple hypothesis testing approach for statistical robustness. Psychological barriers ...are found to be present in Brent prices but not in WTI prices, which is argued to be due to the more prominent role that Brent plays as a global benchmark and, based on recent behavioural finance research, the greater complexity inherent in Brent fundamental value determination. Brent particularly displays evidence that when breaching a $10 barrier level from below with rising prices, the trend is for prices to fall on average subsequently. Similar behavioural-based patterns are evidenced at the $1 barrier level for the WTI–Brent spread. We show that psychological barriers only appear to influence prices in the pre-credit crisis period of 1990–2006, with such effects dissipating during the crisis and as markets reverted back to wider economy focused fundamentals. A range of reaction windows are applied with the main finding being that the trading potential around such psychological barrier levels is primarily in the immediate 1–5 days following a breach. The research contributes to the scant existing research on psychological influences on energy market traders, and suggests strong potential for further application of behavioural finance theories to improving understanding of energy markets price dynamics.
•Investigate presence of psychological barriers in oil futures prices about $10 levels•Brent shows effects over WTI; differences in global benchmark roles and complexity•Evidence Brent prices fall in general after a $10 barrier breach from rising prices•Results shown to be robust within a generalised multiple hypothesis testing framework
Loop closure detection systems for monocular SLAM come in three broad categories: (i) map-to-map, (ii) image-to-image and (iii) image-to-map. In this paper, we have chosen an implementation of each ...and performed experiments allowing the three approaches to be compared. The sequences used include both indoor and outdoor environments and single and multiple loop trajectories.
We describe a new formulation of appearance-only SLAM suitable for very large
scale place recognition. The system navigates in the space of appearance,
assigning each new observation to either a new ...or a previously visited location,
without reference to metric position. The system is demonstrated performing
reliable online appearance mapping and loop-closure detection over a 1000 km
trajectory, with mean filter update times of 14 ms. The scalability of the
system is achieved by defining a sparse approximation to the FAB-MAP model
suitable for implementation using an inverted index. Our formulation of the
problem is fully probabilistic and naturally incorporates robustness against
perceptual aliasing. We also demonstrate that the approach substantially
outperforms the standard term-frequency inverse-document-frequency (tf-idf)
ranking measure. The 1000 km data set comprising almost a terabyte of
omni-directional and stereo imagery is available for use, and we hope that it
will serve as a benchmark for future systems.
The comprehensive guide to working more effectively within the multi-commodity market. The Handbook of Multi-Commodity Markets and Products is the definitive desktop reference for traders, ...structurers, and risk managers who wish to broaden their knowledge base. This non-technical yet sophisticated manual covers everything the professional needs to become acquainted with the structure, function, rules, and practices across a wide spectrum of commodity markets. Contributions from a global team of renowned industry experts provide real- world examples for each market, along with tools for analyzing, pricing, and risk managing deals. The discussion focuses on convergence, including arbitrage valuation, econometric modeling, market structure analysis, contract engineering, and risk, while simulated scenarios help readers understand the practical application of the methods and models presented. Gradual deregulation and the resulting increase in diversity and activity have driven the evolution of the traditionally segmented market toward integration, raising important questions about opportunity identification and analysis in multi-commodity deals. This book helps professionals navigate the shift, providing in-depth information and practical advice. * Structure and manage both simple and sophisticated multi-commodity deals * Exploit pay-off profiles and trading strategies with a diversified set of commodity prices * Develop more accurate forecasting models by considering additional metrics * Price energy products and other commodities in segmented markets with an eye toward specific structural features As one of the only markets strong enough to boom during the credit crunch, the commodities markets are growing rapidly. Combined with increasing convergence, this transition presents potentially valuable opportunities for the development of a robust multi-commodity portfolio. For the professional seeking deeper understanding and a more effective strategy, the Handbook of Multi-Commodity Markets and Products offers complete information and expert guidance.
Globalisation, technological advances, liberalisation of financial markets, and changing consumer behaviour are transforming banking profoundly. Under the EU Payment Services Directive 2 (PSD2), ...incumbent banks must open up their data, processes, and business functionalities to customers and third parties including rivals. It is critical to understand consumer behaviour post-PSD2, and the potential impact of PSD2 on the functioning of the retail banking and financial services market. In this preliminary study of 244 consumers from six European countries, we explore the role of social influence, facilitating conditions, perceived risk, and effort and performance expectancy in order to unravel the determinants of consumers’ acceptance of account information services (AIS) as provisioned under PSD2, which provide consolidated bank account information for consumers with multiple bank accounts across multiple banking institutions. Our findings suggest that the competing influences of (a) positive perceptions such as social influence, facilitating conditions, and performance expectancy, and (b) negative perceptions related to risk, sway consumers’ intentions to adopt AIS.
This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under ...increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry.
Using survey data from the Afrobarometer, we document that respondents who live in areas where more people report having paid a bribe to access household services are more likely to have access to ...electricity. The existing literature suggests three mechanisms that could explain why more corruption increases access to electricity. Corruption could incentivize firms to operate in the shadow economy and facilitate them doing so. Corruption could reduce enforcement of the law for electricity theft. Finally, corruption could lower firms’ costs by allowing them to reduce the burden of red tape and or ignore standards. The data do not support the first two of these mechanisms suggesting that corruption is “greasing the wheels” for firms in the electricity sector. Supporting this conclusion is the fact that this relationship between corruption and access is only statistically significant in countries where the ease of getting electricity is low and there is private participation in the electricity sector.
•Households in more corrupt localities are more likely to have access to electricity.•This is not driven by corruption enabling electricity theft or the shadow economy.•Evidence consistent with corruption “greasing the wheels” for private suppliers.•A trade-off between anti-corruption and electrification efforts in some contexts.•Important to consider other electricity governance issues when fighting corruption.
PhotoOCR: Reading Text in Uncontrolled Conditions Bissacco, Alessandro; Cummins, Mark; Netzer, Yuval ...
2013 IEEE International Conference on Computer Vision,
12/2013
Conference Proceeding, Journal Article
We describe Photo OCR, a system for text extraction from images. Our particular focus is reliable text extraction from smartphone imagery, with the goal of text recognition as a user input modality ...similar to speech recognition. Commercially available OCR performs poorly on this task. Recent progress in machine learning has substantially improved isolated character classification, we build on this progress by demonstrating a complete OCR system using these techniques. We also incorporate modern data center-scale distributed language modelling. Our approach is capable of recognizing text in a variety of challenging imaging conditions where traditional OCR systems fail, notably in the presence of substantial blur, low resolution, low contrast, high image noise and other distortions. It also operates with low latency, mean processing time is 600 ms per image. We evaluate our system on public benchmark datasets for text extraction and outperform all previously reported results, more than halving the error rate on multiple benchmarks. The system is currently in use in many applications at Google, and is available as a user input modality in Google Translate for Android.
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