Sequence Learning (SL) tasks have been used to investigate implicit and explicit aspects in human performance. In the present study the SL task approach has been adapted to investigate human performance under conditions of lacking information. In this case participants have to use their own model (participant model, PM) of a possible stimulus structure. Here we introduce the term Moment of Unde...

Data in the real world can not be recorded or collected precisely due to human errors, machine errors, or some other unexpected situations. And reliability analysis is an important research topic in engineering. The data, however, can not be recorded precisely sometimes as described above. Then some researchers pay attention to the fuzzy reliability. In this paper, we are going to analyze the f...

Cancer diagnosis and personalized cancer treatment are heavily based on the visual assessment of immunohistochemically-stained tissue specimens. The precision of this assessment depends critically on the quality of immunostaining, which is governed by a number of parameters used in the staining process. Tuning of the staining-process parameters is mostly based on pathologists’ qualitative asses...

This paper investigates the performance and relevance of a set of acoustic features for the task of automatic recognition of affect from speech using machine learning techniques. Eighty seven novel and classical features related to loudness, intonation, and voice quality, are examined. Using feature selection, the results yield a performance level of 49.4% recognition rate (compared to a human ...

This paper analyzes the impact of several lexical and grammatical features in automated assessment of students’ finegrained understanding of tutored concepts. Truly effective dialog and pedagogy in Intelligent Tutoring Systems is only achievable when systems are able to understand the detailed relationships between a student’s answer and the desired conceptual understanding. We describe a new m...