Democratizing Journalism – How User‐Generated Content and User Communities Affect Publishers’ Business Models

Publishers, today, are struggling with their business model: Their efforts to convert traditional content into digital products seem to be insufficient as recipients expect more than simply the mere digitalization of content. Dissatisfied with solely being informed by selected journalists, modern recipients are often interested in acquiring information from various sources, in discussing with others, or even in contributing with their own content. Hence, recipients seem to evolve from being simply readers to contributors themselves. With regard to the established term ‘user‐generated content’, we refer to those co‐creating recipients as users. To underline these assumptions, the present study explores (1) users’ expectations of sources of content and (2) their willingness to provide their own content. Our findings show that both user‐generated content and professional journalists’ content is of value to users. Second, we show that users are mainly driven to contribute by their own expertise, welfare of others, and personal acceptance in the community. With this study, we consider mainly the changed user behaviour in order to derive implications of user involvement for future business models of publishers, in particular on the customer value proposition as well as key resources and key processes.     

Open generification

To what extent can software ‘travel’ to organizations and countries for which it was not designed for, and how important are local contexts for a successful design and implementation of generic software? Information systems researchers have differing views on this, some emphasizing the strengths of the generic and others the importance of contextual aspects. Contributing to this debate, Pollock and Williams have coined the term generification in order to describe how large vendors succeed in globalizing software packages through management by community, content and social authority. In this paper, we explore an approach that we call open generification, which extends Pollock and Williams' work in the sense that we acknowledge the need for and the feasibility of generic software, but propose an alternative model for the governance of it. Open generification is not about managing the community of users attached to a software package by homogenization or segmentation but aims at addressing the diverse needs of the community the software is expected to serve. Our empirical basis is a longitudinal study of the development of an open‐source health information system software (District Health Information software version 2), which is being used in more than 47 countries. Its success is attributed to a continuous interplay between generic and specific software and continuous cycles of embedding (implementing the global in the local context) and disembedding (taking local innovations into the global). We identify and discuss the contingent mechanisms of this interplay.     

Big data in the public sector: Uncertainties and readiness

Big data is being implemented with success in the private sector and science. Yet the public sector seems to be falling behind, despite the potential value of big data for government. Government organizations do recognize the opportunities of big data but seem uncertain about whether they are ready for the introduction of big data, and if they are adequately equipped to use big data. This paper addresses those uncertainties. It presents an assessment framework for evaluating public organizations’ big data readiness. Doing so demystifies the concept of big data, as it is expressed in terms of specific and measureable organizational characteristics. The framework was tested by applying it to organizations in the Dutch public sector. The results suggest that organizations may be technically capable of using big data, but they will not significantly gain from these activities if the applications do not fit their organizations and main statutory tasks. The framework proved helpful in pointing out areas where public sector organizations could improve, providing guidance on how government can become more big data ready in the future.     

An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range

In this paper, we present an automatic C-code generation strategy for real-time nonlinear model predictive control (NMPC), which is designed for applications with kilohertz sample rates. The corresponding code export module has been implemented within the software package ACADO Toolkit. It is capable of exporting fixed step-size integrators together with their sensitivities as well as a real-time Gauss–Newton method. Here, we employ the symbolic representation of optimal control problems in ACADO in order to auto-generate plain C-code which is optimized for final production. The exported code has been tested for model predictive control scenarios comprising constrained nonlinear dynamic systems with four states and a control horizon of ten samples. The numerical simulations show a promising performance of the exported code being able to provide feedback in much less than a millisecond.     

A survey on industrial applications of fuzzy control

Fuzzy control has long been applied to industry with several important theoretical results and successful results. Originally introduced as model-free control design approach, model-based fuzzy control has gained widespread significance in the past decade. This paper presents a survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000.     

Probabilistic Marching Cubes

In this paper we revisit the computation and visualization of equivalents to isocontours in uncertain scalar fields. We model uncertainty by discrete random fields and, in contrast to previous methods, also take arbitrary spatial correlations into account. Starting with joint distributions of the random variables associated to the sample locations, we compute level crossing probabilities for cells of the sample grid. This corresponds to computing the probabilities that the well‐known symmetry‐reduced marching cubes cases occur in random field realizations. For Gaussian random fields, only marginal density functions that correspond to the vertices of the considered cell need to be integrated. We compute the integrals for each cell in the sample grid using a Monte Carlo method. The probabilistic ansatz does not suffer from degenerate cases that usually require case distinctions and solutions of ill‐conditioned problems. Applications in 2D and 3D, both to synthetic and real data from ensemble simulations in climate research, illustrate the influence of spatial correlations on the spatial distribution of uncertain isocontours.     

TimeLapseAnalyzer: multi-target analysis for live-cell imaging and time-lapse microscopy

The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.     

Independent Hybrid Force/Motion Control of Constrained Six-Degrees-of-Freedom Manipulators

Controlling the dynamics of a constrained manipulator includesposition tracking as well as stabilization of the contact wrench.In this paper we derive a control scheme, that makes it possible to treat position and force control independently.The approach is based on a mass-orthogonal splitting of the space of joint torques, allowing independent actuation and therefore independent specification of control laws. An appropriate definition of the reference wrenchmakes it possible to achieve independent stability of the position and force loop.     

Contrast-optimal k out of n secret sharing schemes in visual cryptography

Visual cryptography and (k,n)-visual secret sharing schemes were introduced by Naor and Shamir (Advances in Cryptology — Eurocrypt 94, Springer, Berlin, 1995, pp. 1–12). A sender wishing to transmit a secret message distributes n transparencies amongst n recipients, where the transparencies contain seemingly random pictures. A (k,n)-scheme achieves the following situation: If any k recipients stack their transparencies together, then a secret message is revealed visually. On the other hand, if only k−1 recipients stack their transparencies, or analyze them by any other means, they are not able to obtain any information about the secret message. The important parameters of a scheme are its contrast, i.e., the clarity with which the message becomes visible, and the number of subpixels needed to encode one pixel of the original picture. Naor and Shamir constructed (k,k)-schemes with contrast 2^−(k−1). By an intricate result from Linial (Combinatorica 10 (1990) 349–365), they were also able to prove the optimality of these schemes. They also proved that for all fixed kn, there are (k,n)-schemes with contrast . For k=2,3,4 the contrast is approximately and . In this paper, we show that by solving a simple linear program, one is able to compute exactly the best contrast achievable in any (k,n)-scheme. The solution of the linear program also provides a representation of a corresponding scheme. For small k as well as for k=n, we are able to analytically solve the linear program. For k=2,3,4, we obtain that the optimal contrast is at least and . For k=n, we obtain a very simple proof of the optimality of Naor's and Shamir's (k,k)-schemes. In the case k=2, we are able to use a different approach via coding theory which allows us to prove an optimal tradeoff between the contrast and the number of subpixels.