Web usage mining is the application of data mining techniques to better serve the needs of web-based applications on the web site. In this paper, we analyze the web usage mining by applying the pattern recognition techniques on web log data. Pattern recognition is defined as the act of taking in raw data and making an action based on the ‘category’ of the pattern. Web usage mining is divided in...

This paper presents an electromyographic (EMG) pattern recognition method to identify motion commands for the control of a prosthetic arm by evidence accumulation based on artificial intelligence with multiple parameters. The integral absolute value, variance, autoregressive (AR) model coefficients, linear cepstrum coefficients, and adaptive cepstrum vector are extracted as feature parameters f...

The brain white matter is responsible for the transmission of electrical signals through the central nervous system. Lesions in the brain white matter, called white matter hyperintensity (WMH), can cause a significant functional deficit. WMH are commonly seen in normal aging, but also in a number of neurological and psychiatric disorders. We propose here an automatic method for WHM analysis in ...

Pattern recognition is the discipline studying the design and operation of systems capable to recognize patterns with specific properties in data sources. Intrusion detection, on the other hand, is in charge of identifying anomalous activities by analyzing a data source, be it the logs of an operating system or in the network traffic. It is easy to find similarities between such research fields...

Biofilms are complex aggregates formed by microorganisms such as bacteria, fungi and algae, which grow at the interfaces between water and natural or artificial materials. They are actively involved in processes of sorption and desorption of metal ions in water and reflect the environmental conditions in the recent past. Therefore, biofilms can be used as bioindicators of water quality. The goa...

This Special Issue of the Elsevier Journal of Pattern Recognition entitled “Computer Vision applying Pattern Recognition Techniques” presents the ongoing and active research in the Pattern Recognition applied to Computer Vision area, with emphasis on topics around emerging paradigms on computer vision, robotics, and up-to-date applications to related fields (hardware implementations, parallels ...

Time-series prediction is important in physical and financial domains. Pattern recognition techniques for time-series prediction are based on structural matching of the current state of the time-series with previously occurring states in historical data for making predictions. This paper describes a Pattern Modelling and Recognition System (PMRS) which is used for forecasting benchmark series a...

Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discover biologically meaningful knowledge in large data sets. Many researchers have begun an endeavor in this direction to devise such data-mining techniques. As such, there is a need for...

This paper presents an analysis of different learning styles observed in a group of college freshmen. Recognizing relevant aspects of each style provides aid in the planning of actions that could reduce dropouts and increase the academic performance of first-year students in colleges. To accomplish this study an assessment tool was devised and implemented applying techniques of clustering and m...