Naturalistic longitudinal recordings of child development promise to reveal fresh perspectives on fundamental questions of language acquisition. In a pilot effort, we have recorded 230,000 hours of audio-video recordings spanning the first three years of one child’s life at home. To study a corpus of this scale and richness, current methods of developmental cognitive science are inadequate. We ...

Fuzzy c-means clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. Aimed at the problems existed in the FCM clustering algorithm, a kernelbased fuzzy c-means (KFCM) is clustering algorithm is proposed to optimize fuzzy ...

In this paper, we examine the performance of fuzzy clustering algorithms as the major technique in pattern recognition. Both possibilistic and probabilistic approaches are explored. While the Possibilistic C-Means (PCM) has been shown to be advantageous over Fuzzy C-Means (FCM) in noisy environments, it has been reported that the PCM has an undesirable tendency to produce coincident clusters. R...

Artificial Neural Networks are universal and highly flexible function approximators first used in the fields of cognitive science and engineering. In recent years, Neural Networks have become increasingly popular in finance for tasks such as pattern recognition, classification and time series forecasting. The ability to predict cash requirement within reasonable accuracy of actual demand provid...

Clustering is an important research topic that has practical applications in many 5elds. It has been demonstrated that fuzzy clustering, using algorithms such as the fuzzy C-means (FCM), has clear advantages over crisp and probabilistic clustering methods. Like most clustering algorithms, however, FCM and its derivatives need the number of clusters in the given data set as one of their initiali...

The ability to generate, narrate, and understand stories allows humans to accomplish tasks they would otherwise find difficult or impossible. We draw on observations of human narrative to identify a number of capabilities underlying the narrative faculty that we assert must be integrated into any cognitive architecture intended to achieve human-level performance. In particular, we identify sequ...

Magnetic Resonance Spectroscopic Imaging (MRSI) measures relative concentrations of metabolites in vivo and can thus be used for the diagnosis of certain tumors. We introduce the program CLARET that makes MRSI accessible for clinical routine use. Instead of embarking on an error-prone quantification of metabolites that requires manual checking of the results in many voxels, the program uses pat...

This paper, recognize of the patterns using spiking neural networks with temporal encoding and learning. Neural networks place the important role in cognitive and decision making process. Processing the different type of inputs lead to find the discriminate the pattern. Leaky Integrate Fire Neurons are used to recognize the patterns. During the recognition supervised learning method is used to ...

We instrument a system for recognizing handwritten mathematical expressions using the Recognition Strategy Library, a data provenance tool for pattern recognition research, in order to study the behavior of the recognition system and demonstrate the utility of the library. In this case study, the library was used to perform comparison tests to quantitatively analyze several modifications to the...