User’s mental representations and cognitive strategies can have a profound influence on how they interact with computer interfaces (Janosky, Smith & Hildreth, 1986). However, there is very little research that elucidates such mental representations and strategies in the context of interactive hypermedia. Furthermore, interface design for hypermedia information presentation systems is rarely dri...

Table A1 summarizes the various characteristics of the synthetic models used in the experiments, including the number of event types, the size of the state space, whether a challenging construct is contained (loops, duplicates, nonlocal choice, and concurrency), and the entropy of the process defined by the model (estimated based on a sample of size 10,000). The original models may contain eith...

Quantitative predictions for complex scientific theories are often obtained by running simulations on computational models. In order for a theory to meet with wide-spread acceptance, it is important that the model be reproducible and comprehensible by independent researchers. However, the complexity of computational models can make the task of replication all but impossible. Previous authors ha...

The digital backchannel Backstage aims at supporting active and socially enriched participation in large class lectures by improving the social awareness of both lecturer and students. For this purpose, Backstage provides microblog-based communication for fast information exchange among students as well as from audience to lecturer. Rating enables students to assess relevance of backchannel mes...

We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly and are therefore comprehensible to the users. Learning is performed by a feedforward neural network and the rules are extracted from the trained network. A pattern classification task is used to demonstrate the efficacy...

Comprehensible high level representations of software development processes are often not available. By using a clustering algorithm, software development tasks can be represented in a more comprehensible way when using a new diagram style which represents developers as well as the tasks they are performing. Integration in the TESNA project has succeeded and showed that the algorithms work for ...

This paper develops an adaptive ensemble Genetic Algorithm (GA) model for bankruptcy classification of firms cited in the SEC’s Accounting and Auditing Enforcement Release (AAER). Our research contributes to the bankruptcy literature in several ways. First of all, it fills a gap in bankruptcy classification by developing a domain specific model for AAER firms. Secondly, by using financial and n...

Ventilation process model is important for automatically appropriate ventilation for patients residing in the intensive care unit (ICU). Based on other researchers’ work, we try to build a data driven ventilation model under the framework of dynamic Bayesian networks (DBNs). All the variables in our model are suggested by the doctor in ICU. They are all noninvasive measurements obtained directl...

Sense-making, within enactive theories, provides a novel way of understanding how a comprehensible and manageable world arises for a subject. Elaboration of the concept of sense-making allows a fundamental reframing of the notion of perception that does not rely on the pick up of information about a pre-given world. In rejecting the notion of the subject as an input/output system, it is also ne...

A flatness-based approach to fault tolerant control is proposed. The approach uses the recently published algebraic derivative estimation method for the estimation of those output derivatives that are necessary for determining intermittent actuator faults. The rapid performance of the estimation allows for an accommodation of the control to the fault. Additionally, taking into account the contr...