Exploring Design Principles of Organizing for Collaborative Innovation: The Case of an Open Innovation Initiative

In a distributed world, relationships and partnering become even more critical for business, as delivering on rising and complex demands and addressing complex issues is more than one organization can do alone. Such a situation constitutes a huge challenge for many organizations. Building on an inductive case study of an open innovation initiative, illustrating the complex and messy nature of such organizing, we outline five design principles that appear fundamental to the organizing for collaborative innovation. These design principles are our main contribution to the emerging research on organizing for collaborative innovation as they form a perspective and a conceptual tool to talk about and understand the messiness and disorganization of dynamic and discontinuous contemporary organizational constructs.     

Supraparticles for Sustainability

The indispensable transformation to a (more) sustainable human society on this planet heavily relies on innovative technologies and advanced materials. The merits of nanoparticles (NPs) in this context are demonstrated widely during the last decades. Yet, it is believed that the impact of particle-based nanomaterials to sustainability can be even further enhanced: taking NPs as building blocks enables the creation of more complex entities, so-called supraparticles (SPs). Due to their evolving phenomena coupling, emergence, and colocalization, SPs enable completely new material functionalities. These new functionalities in SPs can be utilized to render six fields, essential to human life as it is conceived, more sustainable. These fields, selected based on an entropy-rate-related definition of sustainability, are as follows: 1) purification technologies and 2) agricultural delivery systems secure humans “fundamental needs.” 3) Energy storage and conversion, as well as 4) catalysis enable the “basic comfort.” 5) Extending materials lifetime and 6) bringing materials back in use ensure sustaining “modern life comfort.” In this review article, a perspective is provided on why and how the properties of SPs, and not simply properties of individual NPs or conventional bulk materials, may grant attractive alternative pathways in these fields.     

Evaluating Digital Peer Support for Children Cured from Cancer

This article describes a case study of the challenges that emerged from a formative evaluation process with the purpose of evaluating a digital peer support (DPS) service for children between 8 and 12 cured from cancer. The evaluation of DPS for children is particularly challenging. While the literature on evaluation with children is extensive, challenges such as risk assessment that become prevalent in the evaluation of DPS are not highlighted. This case study analyzes how the DPS service was evaluated over the course of two usability tests, a two-week diary study, a focus group interview, and a survey. Challenges relating to ethics, trust, risk assessment, and recruitment emerged during the evaluation process. We identify key strategies to handle these challenges: progression, proxies, and reflection. Performing a multistage evaluation process with progressing sensitivity allowed control of some of the complexities of the context in order to balance the degree of the children’s involvement with the degree of sensitivity.     

Schutz ökologisch sensibler Fließgewässer: Konzepte und Fallbeispiele

European rivers are subject to heavy demand. In this regard, hydromorphological alterations in connection with energy production or flood protection measures are among the most serious issues. Today only very few natural or near-natural river reaches remain, and in Austria only 15% of the rivers are classified as being in “very good” and a further 22% percent as being in “good” ecological condition. In keeping with the objectives of the EU Water Framework Directive, the National River Basin Management Plan defines measures intended to achieve a good ecological status and/or avoid the further deterioration of Austria’s waterbodies.     

Planning in the Real World

In this article, we describe how real world planning problems can be solved by employing Artificial Intelligence planning techniques. We introduce the paradigm of hybrid planning, which is particularly suited for applications where plans are not intended to be automatically executed by systems, but are made for humans. Hybrid planning combines hierarchical planning ?C the stepwise refinement of complex tasks ?C with explicit reasoning about causal dependencies between actions, thereby reflecting exactly the kinds of reasoning humans perform when developing plans. We show how plans are generated and how failed plans are repaired in a way that guarantees stability. Our illustrating examples are taken from a domain model for disaster relief missions enforced upon extensive floods. Finally, we present a tool to support the challenging task of constructing planning domain models. The article ends with an overview of a wide varity of actual planning applications and outlines further such in the area of cognitive technical systems.     

Firing variability is higher than deduced from the empirical coefficient of variation

A convenient and often used summary measure to quantify the firing variability in neurons is the coefficient of variation (CV), defined as the standard deviation divided by the mean. It is therefore important to find an estimator that gives reliable results from experimental data, that is, the estimator should be unbiased and have low estimation variance. When the CV is evaluated in the standard way (empirical standard deviation of interspike intervals divided by their average), then the estimator is biased, underestimating the true CV, especially if the distribution of the interspike intervals is positively skewed. Moreover, the estimator has a large variance for commonly used distributions. The aim of this letter is to quantify the bias and propose alternative estimation methods. If the distribution is assumed known or can be determined from data, parametric estimators are proposed, which not only remove the bias but also decrease the estimation errors. If no distribution is assumed and the data are very positively skewed, we propose to correct the standard estimator. When defining the corrected estimator, we simply use that it is more stable to work on the log scale for positively skewed distributions. The estimators are evaluated through simulations and applied to experimental data from olfactory receptor neurons in rats.     

Topological numbering of features on a mesh

Assume we are given ann ×n binary image containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. In this paper we consider the problem of assigning topological numbers to such features, i.e., assign a number to every featuref so that all features to the left off in the image have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. We present a parallel algorithm to solve the topological numbering problem inO(n) time on ann ×n mesh of processors. The key idea of our solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.The work of M. J. Atallah was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, and the National Science Foundation under Grant DCR-8451393, with matching funds from AT&T. Part of this work was done while he was a Visiting Scientist at the Center for Advanced Architectures project of the Research Institute for Advanced Computer Science, NASA Ames Research Center, Moffett Field, CA 94035, USA. S. E. Hambrusch's work was supported by the Office of Naval Research under Contracts N00014-84-K-0502 and N00014-86K-0689, and by the National Science Foundation under Grant MIP-87-15652. Part of this work was done while she was visiting the International Computer Science Institute, Berkeley, CA 94704, USA. The work of L. E. TeWinkel was supported by the Office of Naval Research under Contract N00014-86K-0689.