SME Network Characteristics vs. Product Innovativeness: How to Achieve High Innovation Performance

Small‐ and medium‐sized enterprises (SMEs) must on the one hand innovate for company survival with the appropriate degree of product innovativeness, and on the other they need to collaborate and focus on core competences for efficiency matters. This research examines the relation of network characteristics and product innovativeness on innovation performance in SMEs. We tested hypotheses on the relationship between these three variables via data gathered from 60 SMEs, active in the medical devices sector. In this context we aim to offer consensus on the theoretical and empirical question of whether or not network characteristics and product innovativeness have a direct effect on innovation performance of SMEs. Results show no significant direct effect of product innovativeness on innovation performance. A positive interaction effect of multiple network characteristics on innovation performance was found, which confirms the significant importance of network configuration on innovation performance for SMEs. It indicates that, for SMEs in a highly regulated sector like the medical devices sector, the interaction of network characteristics is of crucial importance for high innovation performance. It is the combination of network characteristics that counts.     

Co-located collaborative visual analytics around a tabletop display

Co-located collaboration can be extremely valuable during complex visual analytics tasks. We present an exploratory study of a system designed to support collaborative visual analysis tasks on a digital tabletop display. Fifteen participant pairs employed Cambiera, a visual analytics system, to solve a problem involving 240 digital documents. Our analysis, supported by observations, system logs, questionnaires, and interview data, explores how pairs approached the problem around the table. We contribute a unique, rich understanding of how users worked together around the table and identify eight types of collaboration styles that can be used to identify how closely people work together while problem solving. We show how the closeness of teams’ collaboration and communication influenced how they performed on the task overall. We further discuss the role of the tabletop for visual analytics tasks and derive design implications for future co-located collaborative tabletop problem solving systems.     

Numerical solutions of unsteady flows with low inlet Mach numbers

This study deals with a numerical solution of a 2D unsteady flow of a compressible viscous fluid in a channel for low inlet airflow velocity. The unsteadiness of the flow is caused by a prescribed periodic motion of a part of the channel wall with large amplitudes, nearly closing the channel during oscillations. The channel is a simplified model of the glottal space in the human vocal tract and the flow can represent a model of airflow coming from the trachea, through the glottal region with periodically vibrating vocal folds, and to the human vocal tract.     

Evaluation of in-air hand gestures interaction for older people

Universal Access in the Information Society - In-air gestural interfaces are gaining popularity due to the increasing availability and low cost of gesture recognition hardware. However, the current...     

Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture

Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring a substantial labeling effort, both of which are scarce in precision agriculture. Additional design efforts are required to achieve commercially viable performance levels under varying environmental conditions and crop growth stages. In this paper, we explore the role of knowledge transfer between deep‐learning‐based classifiers for different crop types, with the goal of reducing the retraining time and labeling efforts required for a new crop. We examine the classification performance on three datasets with different crop types and containing a variety of weeds and compare the performance and retraining efforts required when using data labeled at pixel level with partially labeled data obtained through a less time‐consuming procedure of annotating the segmentation output. We show that transfer learning between different crop types is possible and reduces training times for up to 80%. Furthermore, we show that even when the data used for retraining are imperfectly annotated, the classification performance is within 2% of that of networks trained with laboriously annotated pixel‐precision data.     

Requirements engineering in health care: the example of chemotherapy planning in paediatric oncology

Health care is characterized by highly complex processes of patient care that require unusual amount of communication between different health care professionals of different institutions. Sub-optimal processes can significantly impact on the patient’s health, increase the consumption of services and resources and in severe cases can lead to the patient death. For these reasons, requirements engineering for the development of information technology in health care is a complex process as well: without constant and rigorous evaluation, the impact of new systems on the quality of care is unknown and it is possible that badly designed systems significantly harm patients. To overcome these limitations, we present and discuss an approach to requirements engineering that we applied for the development of applications for chemotherapy planning in paediatric oncology. Chemotherapy planning in paediatric oncology is complex and time-consuming and errors must be avoided by all means. In the multi-hospital/multi-trial-centre environment of paediatric oncology, it is especially difficult and time-consuming to analyse requirements. Our approach combines a grounded theory approach with evolutionary prototyping based on the constant development and refinement of a generic domain model, in this case a domain model for chemotherapy planning in paediatric oncology. The prototypes were introduced in medical centres and final results show that the developed generic domain model is adequate.     

Responding to the Global Challenges: Regional Entrepreneurship within the Change Society

In this paper, some fundamental aspects of societal change processes are described, leading to proposals of how to cope with such changes through continuous learning within society. This change society is presently emerging worldwide. It is very much shaped by advanced networked information and communication technology. Correspondingly, certain trends are identified in this paper which indicate the change processes towards this new emerging society. Subsequently, different personal skills are described which are required for all members of society to cope with these trends. The paper finishes with a case study which deals with regional development through open networked business processes. The aim of the project described was to develop a joint family vacation concept in the former socialist East German state of Saxonia. Thus, it illustrates the change and learning processes across society which have taken place in many countries after the socialist era.