Background Characterizing area-at-risk has become a sought-after clinical indicator for the treatment of cardiovascular disease. MRI can provide such information without contrast and radiation. Recently, cardiac phase-resolved blood-oxygen-level-dependent (CP-BOLD) MRI, has shown that this is possible at rest, without even stress agents. However, most of the necessary post-processing analysis r...

This paper examines how hot spots shift by hour of day and day of week. Hot spot analysis is more likely to have a substantial impact on crime patterns if spatiotemporal shifts are incorporated into the crime analysis process. Even in some of the highest crime neighborhoods in Bronx County (NY), not all micro-level geographies (e.g. street segments and property lots) contain substantial (if any...

Applications of a constitutive framework providing compound complexity analysis and indexing of coarse-grained self-similar time series representing behavioural data are presented. A notion of behavioural entropy and hysteresis is introduced as two different forms of compound measures. These measures provide clinically applicable complexity analysis of behavioural patterns yielding scalar chara...

Based on accelerometer, we propose a 3D handwriting recognition system in this paper. The system is consists of 4 main parts: (1) data collection: a single tri-axis accelerometer is mounted on a handheld device to collect different handwriting data. A set of key patterns have to be written using the handheld device several times for consequential processing and training. (2) data preprocessing:...

In this paper, recent technical progress in developing a compact high-speed Grayscale Optical Correlator (GOC) for real-time pattern recognition at the Jet Propulsion Laboratory (JPL) will be presented. This GOC, under partial sponsorship by the Telecommunication and Mission Operation Directorate (TMOD) program at JPL, is being investigated for spacecraft navigation applications. All up-to-date...

Many fault detection methods have been proposed for monitoring the health of various industrial systems. Characterizing the monitored signals is a prerequisite for selecting an appropriate detection method. However, fault detection methods tend to be decided with user's subjective knowledge or their familiarity with the method, rather than following a predefined selection rule. This study inves...

Parameter identification of dynamical systems from time series has received increasing interest due to its wide applications in secure communication, pattern recognition, neural networks, and so on. Given the driving system, parameters can be estimated from the time series by using an adaptive control algorithm. Recently, it has been reported that for some stable systems, in which parameters ar...

Pattern Recognition (PR) in its standard form, which involves training and testing classifiers on a representative set of data drawn from a domain of interest, has been applied to automate an immense number of classification tasks. More recently, a challenging set of so-called “one-class” classification problems have been identified and explored. In this thesis, we introduce a further challengi...

This paper describes new temporal data mining techniques for extracting information from temporal health records consisting of time series of diabetic patients’ treatments. In this new method, there are three steps for analyzing patterns from a longitudinal data set. The first step, a structural-based pattern search, to find qualitative patterns (or, structural patterns). The second step perfor...