In this paper, we investigate the properties of commonly used prepruning heuristics for rule learning by visualizing them in PN-space. PN-space is a variant of ROC-space, which is particularly suited for visualizing the behavior of rule learning and its heuristics. On the one hand, we think that our results lead to a better understanding of the effects of stopping and filtering criteria, and he...

Novel technologies are required for three-dimensional cell biology and biophysics. By three-dimensional we refer to experimental conditions that essentially try to avoid hard and flat surfaces and favour unconstrained sample dynamics. We believe that light-sheet-based microscopes are particularly well suited to studies of sensitive three-dimensional biological systems. The application of such i...

This is a short overview of the principles of a novel development in surgery called enhanced recovery after surgery (ERAS) programs. This is an evidence-based approach to perioperative care that has shown to reduce complications and recovery time by 30-50%. The main mechanism is reduction of the stress reactions to the operation. These principles have been shown to be particularly well suited f...

Scope of this analysis is to tune the proportional-integral-derivative (PID) parameters autonomously for controlling the moisture content in the paper industry by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The GA and PSO based PID tuning results are compared with the Conventional based PID tuning to examine the performance of time domain specifications; hence,...

The Neural Networks are best at identifying patterns or trends in data and they are well suited for predicting or forecasting. Hence neural networks are extensively applied to biomedical systems. An analysis is carried out to motivate neural network applications in medical diagnosis. A special note is made on neural network effort on cancer diagnosis. This paper focuses on the importance of app...

Reconfigurable computing has shown impressive successes with data intensive and latency tolerant applications. Pipelined and parallel implementations of CORDICs can achieve very high throughput for rotation, and various other functions such as multiplication, division, as well as hyperbolic and other higher order functions. Reconfiguration allows us to adapt the implementation of CORDICs and re...

Several induction theorem provers were developed to verify functional programs mechanically. Unfortunately, automated verification usually fails for functions with accumulating arguments. In particular, this holds for tail-recursive functions that correspond to imperative programs, but also for programs with nested recursion. Based on results from the theory of tree transducers, we develop an a...

Generating decision rule sets from observational data is an established branch of machine learning. Although such rules may be well-suited to machine execution, a human being may have problems interpreting them. Making inferences about the dependencies of a number of attributes on each other by looking at the rules is hard, hence the need to summarize and visualize a rule set. In this paper we ...

A useful discriminant vector for pattern classification is one that maximizes the minimum separation of discriminant function values for two pattern classes. This optimality criterion can prove valuable in many situations because it emphasizes the class elements that are most difficult to classify. A method for computing this discriminant vector by quadratic programming is derived. The resultin...

Static HTML links are not appropriate for quickly evolving teachware to which several authors independently contribute material on overlapping topics. Furthermore static links are not capable of providing students with an individualized linearization of the hypertext suited to their individual level of previous knowledge and competence. We hence propose a linking mechanism based on concept maps...