Parkinson’s disease (PD) is a global public health problem of enormous dimension. In this study, we aimed to discriminate between healthy people and people with Parkinson’s disease (PD). Various studies revealed, that voice is one of the earliest indicator of PD, and for that reason, Parkinson dataset that contains biomedical voice of human is used. The main goal of this paper is to automatical...

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. The automatic diagnosis of breast cancer is an important, real-world medical problem. In this article is introduced a new approach for diagnosis of breast cancer. The proposed approach uses Fuzzy c-means (FCM) algorithm and patter...

Pattern recognition is the science of data structure and its classification. There are many classification and clustering methods prevalent in pattern recognition area. In this research, rainfall data in a region in Northern Iran are classified with natural breaks classification method and with a revised fuzzy c-means (FCM) algorithm as a clustering approach. To compare these two methods, the r...

The purpose of this study is to describe how the attribute hierarchy method (AHM) can be applied to assessment engineering. The AHM is a psychometric method for classifying examinees’ test item responses into a set of attribute mastery patterns associated with different components in a cognitive model of task performance. Attribute probabilities, computed using a neural network, can be estimate...

Herbert Simon made overlapping substantive contributions to the fields of economics, psychology, cognitive science, artificial intelligence, decision theory, and organization theory. Simon s work was motivated by the belief that neither the human mind, human thinking and decision making, nor human creativity need be mysterious. It was after he helped create ‘‘thinking’’ machines that Simon came...

Fuzzy C-means (FCM) is simple and widely used for complex data pattern recognition and image analyses. However, selecting an appropriate fuzzifier (m) is crucial in identifying an optimal number of patterns and achieving higher clustering accuracy, which few studies have investigated. Built upon two existing methods on selecting fuzzifier, we developed an integrated fuzzifier evaluation and sel...

In order to design an artificial entity that is able to use language naturally, a computer program that simply manipulates lexical symbols is not good enough. Using these symbols without understanding the meaning attached to them is pointless. Not only does use of natural language require a framework for computational function (the brain), but it requires a physical embodiment. Our lab’s focus ...

Executive Overview How do entrepreneurs identify opportunities for new business ventures? One possibility, suggested by research on human cognition, is that they do so by using cognitive frameworks they have acquired through experience to perceive connections between seemingly unrelated events or trends in the external world. In other words, they use cognitive frameworks they possess to “connec...

Learning of temporal sequences is a topic of research in such different areas as speech and other temporal pattern recognition as well as motor control (for a survey see e.g. Mozer, 1993). In this paper an approach is presented which is particularly suitable for motor control due to the fact that it does not only reproduce temporal sequences in exactly the way they where learned but it is able ...

BACKGROUND Long-term follow-up studies of people with schizophrenia report stability of cognitive performance; less is known about any shorter-term changes in cognitive function. METHODS This longitudinal study aimed to establish whether there was stability, improvement or decline in memory and executive functions over four assessments undertaken prospectively in one year. Cognitive performan...