Dynamic Modeling is not a precise deened concept. Nevertheless , its ambiguity makes it appropriate to use in discussions about requirements for a modern modeling methodology. \Real" systems (as CIM systems are) tend to be complex and dynamic. Models of such systems (or better: of parts of such systems) should serve diierent purposes: They should allow to answer certain questions about the unde...

In this paper, the cognitive interference model of computer anxiety (CIM-CA) is introduced as a theoretical framework for the assessment of computer anxiety and its effect on computer-based test (CBT) performance and test equivalence. Unlike other situation-specific anxieties, research on computer anxiety has not been founded on clear theories or models. Hence, the CIM-CA is intended as a new h...

We propose a temporal database scheme with data dependencies which supports complex tasks, such as version control and connguration management in computer integrated manufacturing (CIM). This architecture adds functionality to the CIM database, thereby reducing the programming eeort required outside the database. The database correctness is maintained even after introducing engineering changes....

Artificial intelligent methods are increasingly used within computer integrated manufacturing (CIM) applications. Real-time expert system environments are good tools to develop intelligent controllers. The first part of this paper summarises some problems of the application of artificial intelligence and expert systems within the CIM area. Then a new open European CNC architecture (OSACA) is in...

A 56-year-old man admitted with coronavirus disease 2019 (COVID-19) became severely ill, required ventilator support and intensive care unit management. After weaning, he was found to have quadriparesis. Guillain–Barré syndrome (GBS) suspected administration of high-dose intravenous immunoglobulin (IVIg) considered. However, markedly prolonged compound muscle action potential (CMAP) duration ob...

The classification information model or CIM classifies instances by considering the discrimination ability of their features, which was proven to be useful for word sense disambiguation at SENSEVAL-1. But the CIM has a problem of information loss. KUNLP system at SENSEVAL-2 uses a modified version of the CIM for word sense disambiguation. We used three types of features for word sense disambigu...