Mareike Dornhöfer

Applying Rules for Representing and Reasoning of Objective Product Use Information Exemplarily for Injection Molding Machines

Information gathered during daily life can be generally categorized as either of objective or of subjective character. The given work focuses on the objective field of product use information and how to represent and reason the information with the help of Rules or a Rule Based System. The aim of the reasoning process is to infer new knowledge form the given product information and to use this knowledge for the improvement of a new product generation of the product. The application scenario detailed in this work focuses on the objective information gathered from an injection molding machine to improve not only parts of the machine, but indirectly the quality of the produced parts.

Med-Assess System for Evaluating and Enhancing Nursing Job Knowledge and Performance

The European funded project Med-Assess supports assessing of work-based competences and job knowledge of nurses, indicating existing knowledge gaps, and ultimately providing recommendations for improving nursing competences. This paper presents the Med-Assess concept, and reflects the implementation results of its ontological approach for analysis and assessment of nursing job knowledge. The ontological approach matches the nursing requirements and domain specific knowledge, and provides the logic for assessment of the end-users i.e. job applicants, nurses and care-givers.

Integrating knowledge management in the context of evidence based learning: two concept models for facilitating the assessment and acquisition of job knowledge

Within the field of Human Resource Management (HRM), the role of individual knowledge has received limited research attention despite offering the promise of superior job performance and improved managerial decision-making. In part, this lack of research may be attributed to the difficulty and laboriousness inherent to the adequate and accurate modeling of job relevant knowledge, particularly since such knowledge by definition varies from job to job. Despite this caveat, there is much to be gained from a knowledge based approach to (managing) human resources. The current paper presents two ontology based concepts for modeling job relevant knowledge, namely Meta-Practitioner and Med-Assess. The former focuses on availing to a practitioner audience the evidence that has accumulated in the academic literature, whereas the latter focuses on the facilitation of personnel selection and training in the medical field through a detailed assessment of individual job knowledge and general mental ability. Ultimately both concepts are aimed at knowledge provision to job applicants and incumbents alike. Having discussed the concepts, the paper summarizes the gains that may be expected from their implementation by presenting an integrated framework. The framework focuses on integrating aspects of Knowledge Management (KM) in the context of Evidence Based Learning (EBL) for business organizations. The paper concludes by addressing the challenges that lie ahead, highlighting some of the limitations of this approach and offering suggestions for further research.

NeuroCare—Personalization and Adaptation of Digital Training Programs for Mild Cognitive Impairments

Changes of cognitive and physical skills are a fundamental aspect of normal aging, but these personal skills fundamentally influence the quality of life and independency of a person. This is even more critical when the changes are decreasing in an above-average or even a pathologic manner. Keeping an individual’s cognitive skills at a certain level is therefore an individual as well as a societal goal. Accompanying the demographic change, however, the number of people with Mild Cognitive Impairments (MCI) rapidly increases. One intervention approach for the stabilization of the personal skill level and a deferment of possible further degradation are specialized cognitive and physical training programs. In order to increase the effectiveness and efficiency of such training programs, concepts for the adaption and personalization of such systems constitute the focus of the scientific discussion. In this publication, a new approach for the realization of digital dementia screening as well as technological solutions for the creation of adaptive and personalized training systems are presented. These approaches and solutions build the basis for the scientifically founded creation of effective and user-centered cognitive training modules within the research project NeuroCare, funded by the German Federal Ministry of Education and Research.

Knowledge Based Technologies for Promoting Innovation in Material Science

Materials and their properties are nowadays mostly represented either in forms of material data bases or digital data sheets. While these are sources of facts about the particular materials, the interconnection between the different materials, their usage and development is still lacking. Besides, the data bases are mostly distributed, run by different institutions or specialized on only one category like metals or polymers. The given article addresses the application of knowledge management in the area of material science and engineering for gathering, representing and distributing knowledge as well as supporting a sustainable material and product development. Sustainability, green engineering and innovativeness are crucial deciding factors for today’s material development and should therefore be addressed and integrated in the scope of promoting innovation in material science. To accomplish the aforementioned goal, a combination of semantic and case based methods will be applied in a holistic concept, entitled MatProSQI. It is thus become possible to interconnect and reference fact or knowledge of materials, like category, property, test results, production requirements, sustainability factors, user feedback and experiences of former applications. In addition to the representation of knowledge, collaboration between the engineers is detected as an essential factor for a steady transfer of knowledge.

KNowledge Based Innovation Detection And Control Framework To Foster Scientific Research Projects In Material Science

This paper introduces a comprehensive concept idea for building up a knowledge based innovation framework for scientific research projects in general and especially in the field of material science (IConMas). Regarding the aspect of material science the aim is to develop and establish a knowledge based material innovation method. Both aspects, innovation framework and innovation method, are integrated in a common concept which is accurately described within this paper. The outlook focuses on possibilities for realizing the concept and further work in the project.

Computer aided writing --- a framework supporting research tasks, topic recommendations and text readability

Although the concept of computer aided writing and word processing is already about 50 years old, there are only few features supporting text creation for authors in todays standard word processing tools. This work presents a Computer Aided Writing (CAW) framework, which supports the user not only during research tasks, but also in creating a text and varieties of this initial text. A feature for proof reading of the text highlights paragraphs which might cause readability problems. The CAW framework bases on methods from the research fields of Knowledge Discovery from Text (KDT) and Recommender Systems.