Credit card fraud detection by adaptive neural data mining

The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate

Neural data mining for credit card fraud detection

The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate

Adequate formalization

This article identifies problems with regard to providing criteria that regulate the matching of logical formulae and natural language. We then take on to solve these problems by defining a necessary and sufficient criterion of adequate formalization. On the basis of this criterion we argue that logic should not be seen as an ars iudicandi capable of evaluating the validity or invalidity of informal arguments, but as an ars explicandi that renders transparent the formal structure of informal reasonin

Agriculture, Population, Land and Water Scarcity in a Changing World – The Role of Irrigation

Fertile land and fresh water constitute two of the most fundamental resources for food production. These resources are affected by environmental, political, economic, and technical developments. Regional impacts may transmit to the world through increased trade. With a global forest and agricultural sector model, we quantify the impacts of increased demand for food due to population growth and economic development on potential land and water use. In particular, we investigate producer adaptation regarding crop and irrigation choice, agricultural market adjustments, and changes in the values of land and water.Irrigation, Food supply, Integrated assessment, Water use intensity, Agricultural adaptation, Land scarcity, Partial equilibrium model, Resource /Energy Economics and Policy,

No evidence for auditory N1 dishabituation in healthy adults after presentation of rare novel distractors

Previous studies were not able to show that presentation of change stimuli leads to dishabituation of the auditory evoked potential (AEP) component N1 for repeated stimuli. However, these change stimuli were usually themselves repeatedly presented. Here, we tested whether the presentation of non-repeating distractor stimuli (‘novels’) would lead to N1 dishabituation. The study sample consisted of 18 healthy participants who had to identify auditory target stimuli (´targets´) among repeated standard stimuli and rare novels. AEPs to standards were separately averaged, depending on the preceding stimulus (standards after standards, standards after targets, and standards after novels) and were compared by F statistics and Bayesian t-test. Moreover, N1 repetition effects within recording blocks were analyzed in single trial analyses. The analyses showed that targets elicited significantly larger N1 amplitudes than standards and standards elicited larger N1 amplitudes than novels. In contrast, the N1 amplitude to standards did not vary with the preceding stimulus. The single trial analyses revealed significant, but similar N1 amplitude decreases within the recording blocks for all standards. The current study revealed no evidence for N1 dishabituation, as the N1 amplitude for standards after novels was not increased as compared to the N1 for standards after standards. Thus, stimulus variation had no impact on the N1 of repeated standards, as also suggested by the single trial analyses. The lack of N1 dishabituation is at odds with the assumption that the N1 amplitude decrease after repeated stimulation results from habituation

Distributed Interior Point Methods for Optimization in Energy Networks

This note discusses an essentially decentralized interior point method, which is well suited for optimization problems arising in energy networks. Advantages of the proposed method are guaranteed and fast local convergence also for problems with non-convex constraints. Moreover, our method exhibits a small communication footprint and it achieves a comparably high solution accuracy with a limited number of iterations, whereby the local subproblems are of low computational complexity. We illustrate the performance of the proposed method on a problem from energy systems, i.e., we consider an optimal power flow problem with 708 buses

Towards A Method for Developing Reference Enterprise Architectures

In most economic sectors organizations face rapid environmental changes like regulations. Such changes can force them to adjust both their organizational and operational structure. For instance, in the energy utility sector numerous developments moved German Public Utilities (PUs) towards a liberalized market. Nowadays PUs have to stay competitive while managing a heterogeneous information technology (IT) landscape. We address this demand for aligning business and IT by combining the holistic perspective of Enterprise Architecture Management (EAM) with the characteristic of reference modeling to reuse knowledge in a problem domain. Therefore, we utilize configurative reference modeling within Design Science Research (DSR). The artefact at hand is a method for developing a Reference Enterprise Architecture (R-EA), which is applied in the problem domain of PUs. Our contributions are the (i) adaptation of Configurative Reference Modelling (CRM) to develop a R-EA and (ii) a procedure how to elicit knowledge for R-EA development method