Østfold University College

About: Østfold University College is a education organization based out in Halden, Norway. It is known for research contribution in the topics: Context (language use) & Health care. The organization has 438 authors who have published 1213 publications receiving 12510 citations. The organization is also known as: HiØ.

Undressing the Emperor? On the ethical dilemmas of hierarchical knowledge

Abstract: The title refers to Hans Christian Andersen's fairytale "The Emperor's New Clothes". It indicates how hierarchies of power dominate what we see and how we act - in short, our ethical interaction. The author considers collaboration to be a prerequisite for improving quality in the arenas of health and social work, in persons as well as systems. She argues that a radical change in the direction of understanding knowledge and competence as co-creational is required. This again calls for a redefinition not only of the role of professions, of what it takes to be a professional, but also of the role of the user. Consequently, the author's approach challenges the institutional framework of health and social work, as well as the content and methodology of teaching.

Sustainability in Software Engineering - A Systematic Mapping

Abstract: Information Technology (IT) has become a key element in our everyday life, and one of humanity’s current challenges is to conserve the environment and attain a sustainable IT development. Therefore, it has become increasingly important how environmentally friendly a software product is during its life cycle and the effects on the environment related to the development, exercise, maintenance and disposal of the software product. The purpose of this study is to outline recent development of frameworks and guidelines in sustainable software engineering. A systematic mapping was conducted which focuses on practices and models that are being used or proposed in this regard. The results reveal different types of models and different criteria for evaluating sustainability properties. In addition, the study indicates an increase of interest in this field in recent years whereas results suggest a handful of prominent authors and venues publishing research within the scope of sustainable software engineering.

Improving Decision Tree Pruning through Automatic Programming

Abstract: Automatic Design of Algorithms through Evolution (ADATE) is a machine learning system for program synthesis with automatic invention of recursive help functions. It is well suited for automatic improvement of other machine learning algorithms since it is difficult to design such algorithms based on theory alone which means that experimental tuning, optimization and even design of such algorithms is essential for the machine learning practitioner. To demonstrate the feasibility and usefulness of “learning how to learn” through program evolution, we used the ADATE system to automatically rewrite the code for the so-called error based pruning that is an important part of Quinlan’s C4.5 decision tree learning algorithm. We evaluated the resulting novel pruning algorithm on a variety of machine learning data sets from the UCI machine learning repository and found that it generates trees with seemingly better generalizing ability. The same meta-learning may be applied to most machine learning methods.