On the Complexity and Behaviour of Cryptocurrencies Compared to Other Markets

We show that the behaviour of Bitcoin has interesting similarities to stock and precious metal markets, such as gold and silver. We report that whilst Litecoin, the second largest cryptocurrency, closely follows Bitcoin's behaviour, it does not show all the reported properties of Bitcoin. Agreements between apparently disparate complexity measures have been found, and it is shown that statistical, information-theoretic, algorithmic and fractal measures have different but interesting capabilities of clustering families of markets by type. The report is particularly interesting because of the range and novel use of some measures of complexity to characterize price behaviour, because of the IRS designation of Bitcoin as an investment property and not a currency, and the announcement of the Canadian government's own electronic currency MintChip.Comment: 16 pages, 11 figures, 4 table

Integrate the GM(1,1) and Verhulst models to predict software stage effort

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Software effort prediction clearly plays a crucial role in software project management. In keeping with more dynamic approaches to software development, it is not sufficient to only predict the whole-project effort at an early stage. Rather, the project manager must also dynamically predict the effort of different stages or activities during the software development process. This can assist the project manager to reestimate effort and adjust the project plan, thus avoiding effort or schedule overruns. This paper presents a method for software physical time stage-effort prediction based on grey models GM(1,1) and Verhulst. This method establishes models dynamically according to particular types of stage-effort sequences, and can adapt to particular development methodologies automatically by using a novel grey feedback mechanism. We evaluate the proposed method with a large-scale real-world software engineering dataset, and compare it with the linear regression method and the Kalman filter method, revealing that accuracy has been improved by at least 28% and 50%, respectively. The results indicate that the method can be effective and has considerable potential. We believe that stage predictions could be a useful complement to whole-project effort prediction methods.National Natural Science Foundation of China and the Hi-Tech Research and Development Program of Chin

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

Helping Business Schools Engage with Real Problems: The Contribution of Critical Realism and Systems Thinking

The world faces major problems, not least climate change and the financial crisis, and business schools have been criticised for their failure to help address these issues and, in the case of the financial meltdown, for being causally implicated in it. In this paper we begin by describing the extent of what has been called the rigour/relevance debate. We then diagnose the nature of the problem in terms of historical, structural and contextual mechanisms that initiated and now sustain an inability of business schools to engage with real-world issues. We then propose a combination of measures, which mutually reinforce each other, that are necessary to break into this vicious circle – critical realism as an underpinning philosophy that supports and embodies the next points; holism and transdisciplinarity; multimethodology (mixed-methods research); and a critical and ethical-committed stance. OR and management science have much to contribute in terms of both powerful analytical methods and problem structuring methods

The view from elsewhere: perspectives on ALife Modeling

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor

Introduction: Layered Landscapes

This Special Issue of Arts investigates a series of creative projects focused upon and sited within certain peripheral landscapes of northern Britain ..

Archaeological practices, knowledge work and digitalisation

Defining what constitute archaeological practices is a prerequisite for understanding where and how archaeological and archaeologically relevant information and knowledge are made, what counts as archaeological information, and where the limits are situated. The aim of this position paper, developed as a part of the COST action Archaeological practices and knowledge work in the digital environment (www.arkwork.eu), is to highlight the need for at least a relative consensus on the extents of archaeological practices in order to be able to understand and develop archaeological practices and knowledge work in the contemporary digital context. The text discusses approaches to study archaeological practices and knowledge work including Nicolini’s notions of zooming in and zooming out, and proposes that a distinction between archaeological and archaeology-related practices could provide a way to negotiate the ‘archaeologicality’ of diverse practices