Neural Networks as Cybernetic Systems - 3rd and revised edition

This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part I

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part 2

eural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Transfer Functions in Artificial Neural Networks - A Simulation-Based Tutorial

Artificial neural networks are based on computational units that resemble basic information processing properties of biological neurons in an abstract and simplified manner. Generally, these formal neurons model an input-output behaviour as it is also often used to characterize biological neurons. The neuron is treated as a black box; spatial extension and temporal dynamics present in biological neurons are most often neglected. Even though artificial neurons are simplified, they can show a variety of input-output relations, depending on the transfer functions they apply. This unit on transfer functions provides an overview of different transfer functions and offers a simulation that visualizes the input-output behaviour of an artificial neuron depending on the specific combination of transfer functions.

Neural Networks as Cybernetic Systems - Part I

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology.

Neural Networks as Cybernetic Systems - Part II

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology.

Neural Networks as Cybernetic Systems

This book on biological cybernetics combines system theory and artificial neural networks. Following a 'holistic' approach, the book examines the role of simulation in biology. Mainly addressed to students of Biology, the book tries to avoid the use of mathematical formula as far as possible. Exercises can be performed with a related software tool (tkCybernetics) for part 1 as well as with educational simulation on neural networks for part two (in prepration.)

Anomic Crime in Post-Welfarist Societies. Cult of the Individual, Integration Patterns and Delinquency

Post-Fordist economies come along with post-welfarist societies marked by intensified cultural individualism and increased structural inequalities. These conditions are commonly held to be conducive to relative deprivation and, thereby, anomic crime. At the same time, post-welfarist societies develop a new ‘balance of power’ between institutions providing for welfare regulation, such as the family, the state and the (labour) market – and also the penal system. These institutions are generally expected to improve social integration, ensure conformity and thus reduce anomic crime. Combining both perspectives, we analyse the effects of moral individualism, social inequality, and different integration strategies on crime rates in contemporary societies through the lenses of anomie theory. To test our hypotheses, we draw on time-series cross-section data compiled from different data sources (OECD, UN, WHO, WDI) for twenty developed countries in the period 1970-2004, and run multiple regressions that control for country-specific effects. Although we find some evidence that the mismatch between cultural ideal (individual inclusion) and structural reality (stratified exclusion) increases the anomic pressure, whereas conservative (i. e. family-based), social-democratic (i. e. state-based) and liberal (i. e. market-based) integration strategies to a certain extent prove effective in controlling the incidence of crime, the results are not very robust. Moreover, reservations have to be made regarding the effects of “market” income inequality as well as familialist, unionist and liberalist employment policies that are shown to have reversed effects in our sample: the former reducing, the latter occasionally increasing anomic crime. As expected, the mismatch between cultural ideal (individual inclusion) and structural reality (stratified exclusion) increases the anomic pressure, whereas conservative (i. e. family-based), social-democratic (i. e. state-based) and liberal (i. e. market-based) integration strategies generally prove effective in controlling the incidence of crime. Nevertheless, we conclude that the new cult of the individual undermines the effectiveness of conservative and social-democratic integration strategies and drives societies towards more “liberal” regimes that build on incentive as well as punitive elements.

Governance of Massive Multiauthor Collaboration – Linux, Wikipedia, and Other Networks: Governed by Bilateral Contracts, Partnerships, or Something in Between?

Open collaborative projects are moving to the foreground of knowledge production. Some online user communities develop into longterm projects that generate a highly valuable and at the same time freely accessible output. Traditional copyright law that is organized around the idea of a single creative entity is not well equipped to accommodate the needs of these forms of collaboration. In order to enable a peculiar network-type of interaction participants instead draw on public licensing models that determine the freedoms to use individual contributions. With the help of these access rules the operational logic of the project can be implemented successfully. However, as the case of the Wikipedia GFDL-CC license transition demonstrates, the adaptation of access rules in networks to new circumstances raises collective action problems and suffers from pitfalls caused by the fact that public licensing is grounded in individual copyright. Legal governance of open collaboration projects is a largely unexplored field. The article argues that the license steward of a public license assumes the position of a fiduciary of the knowledge commons generated under the license regime. Ultimately, the governance of decentralized networks translates into a composite of organizational and contractual elements. It is concluded that the production of global knowledge commons relies on rules of transnational private law.