A “Knot” – breaking the inertia in construction?

The aim of this paper is to contribute to new collaborative processes in construction practice, which are challenged by a traditional understanding of teams in construction project management. A dynamic innovative and open-ended expansive process is requested and badly needed. The development and implementation of new technology require a parallel process of developing the use of technology and the social processes of its use. Knotworking represents a distributed collaborative expertise in pursuit of a task that is organised among designers from different design disciplines and other players in a construction process. In Finland and Denmark experiments with Knotworking is being developed and tested: Experiments with Knots, how can it change or create new objects and solutions in construction? The method of the study is action research and applied ethnography that is a practice-oriented approach to contribute to change processes. The degree of authors’ participation varied from being a facilitator, consultant or observer in the Danish case and from being a facilitator and observant in the Finnish case. The data collection was a participant observation in a Finish and Danish case. The participants of the experiments were architects, contractors, energy specialists, HVAC design engineers, structural engineers, a cost calculator, representatives of property owners and researchers. The data was saved in digital format using several video cameras. We also gathered BIM documents, process charts, advisors’ reports and photographs. Experiments with Knots have the potential to break inertia in construction, multiple solutions will persist and it implies learning by experimenting with the new practice. The Knots are organised to solve specific problems or tasks requiring multidisciplinary expertise. Working with Knots as a successful process requires intensive collaboration across organizational boundaries and hierarchies through object-oriented actions, i.e. objects of activities that include both material and cognitive constructions which lead to entail directionality, purpose, and meaning to collective activities.Peer reviewe

Clinical application of a simple questionnaire for the differentiation of asthma and chronic obstructive pulmonary disease

AbstractBackground: Asthma and chronic obstructive pulmonary disease (COPD) are highly prevalent chronic diseases characterized by airflow limitation. Both diseases have a distinct pathogenesis and require unique treatment approaches. Due to some common characteristic traits, asthma and COPD are often lumped together in clinical practice. We sought to develop a simple questionnaire for the distinction of asthma and COPD.Methods: Clinical discriminants of asthma and COPD were retrospectively identified by multiple logistic regression using files from 547 consecutive adult patients presenting to a pulmonary specialist practice with a diagnosis of asthma or COPD. With these features, we generated a simple quantitative questionnaire supporting a diagnosis of COPD with high scores and asthma with low scores (range 0–15 points). Questionnaire results were compared with physician's diagnosis based on GINA and GOLD guidelines including skin tests, spirometry and reversibility data.Results: 210 patients had COPD and 337 had asthma. Age of onset, smoking history, atopy status, and cough quality were significantly associated with a diagnosis of asthma or COPD. Questionnaire scores for COPD patients were higher than those for asthmatics (mean score 10.5±0.18 vs. 4±0.12, P<0.0001). Receiver operational characteristics (ROC) analysis revealed a cutoff score of 7 with the highest discriminant power (87.6% sensitivity, 87.2% specificity for COPD, 87.4% correctly classified, area under the ROC curve: 0.954). The overlap between asthma and COPD (score 6–8) comprised about 20% of the total population, these patients included a higher proportion of COPD patients with atopy, and smoking asthmatics.Conclusions: In patients with obstructive airway diseases, a simple questionnaire can support the differentiation of asthma and COPD in everyday clinical practice. Further prospective trials are necessary to confirm these initial observations

Adding Why to What? Analyses of an Everyday Explanation

In XAI it is important to consider that, in contrast to explanations for professional audiences, one cannot assume common expertise when explaining for laypeople. But such explanations between humans vary greatly, making it difficult to research commonalities across explanations. We used the dual nature theory, a techno-philosophical approach, to cope with these challenges. According to it, one can explain, for example, an XAI's decision by addressing its dual nature: by focusing on the Architecture (e.g., the logic of its algorithms) or the Relevance (e.g., the severity of a decision, the implications of a recommendation). We investigated 20 game explanations using the theory as an analytical framework. We elaborate how we used the theory to quickly structure and compare explanations of technological artifacts. We supplemented results from analyzing the explanation contents with results from a video recall to explore how explainers justified their explanation. We found that explainers were focusing on the physical aspects of the game first (Architecture) and only later on aspects of the Relevance. Reasoning in the video recalls indicated that EX regarded the focus on the Architecture as important for structuring the explanation initially by explaining the basic components before focusing on more complex, intangible aspects. Shifting between addressing the two sides was justified by explanation goals, emerging misunderstandings, and the knowledge needs of the explainee. We discovered several commonalities that inspire future research questions which, if further generalizable, provide first ideas for the construction of synthetic explanations.Comment: Paper accepted and presented at XAI World Conference 2023, Lisbo

Estimating good discrete partitions from observed data: symbolic false nearest neighbors

A symbolic analysis of observed time series data requires making a discrete partition of a continuous state space containing observations of the dynamics. A particular kind of partition, called ``generating'', preserves all dynamical information of a deterministic map in the symbolic representation, but such partitions are not obvious beyond one dimension, and existing methods to find them require significant knowledge of the dynamical evolution operator or the spectrum of unstable periodic orbits. We introduce a statistic and algorithm to refine empirical partitions for symbolic state reconstruction. This method optimizes an essential property of a generating partition: avoiding topological degeneracies. It requires only the observed time series and is sensible even in the presence of noise when no truly generating partition is possible. Because of its resemblance to a geometrical statistic frequently used for reconstructing valid time-delay embeddings, we call the algorithm ``symbolic false nearest neighbors''