Data mining is becoming an increasingly important tool to transform enormous data into useful information. Mining periodic patterns in temporal dataset plays an important role in data mining and knowledge discovery tasks. This paper presents, design and development of software for sequential pattern mining for asynchronous periodic patterns in temporal database. Comparative study of various alg...

background: with regard to the high prevalence of schizophrenia, research on brain structural changes in this disease has been one of the interesting issues among the medical scientists. in this research, brain mri findings of schizophrenic patients have been compared with non-schizophrenic ones. methods: this study was an analytic-comparative one in which two groups of schizophrenic and non-sc...

There are two paths of research on temporal datasets. One is temporal reasoning, which uses artificial intelligence and data mining for tasks such as diagnosis, monitoring, projection, forecasting and planning [SHAHAR 97]. Another path involves providing an interactive interface for dynamic visualization of the temporal dataset. This paper extends several approaches in this second path. 2.1 Abs...

We propose a temporal segmentation and procedure learning model for long untrimmed and unconstrained videos, e.g., videos from YouTube. The proposed model segments a video into segments that constitute a procedure and learns the underlying temporal dependency among the procedure segments. The output procedure segments can be applied for other tasks, such as video description generation or activ...

Background: Epilepsy surgery has become a successful treatment option for patients with drug-resistant epilepsies. Objectives: This study aimed to assess temporal lobe epilepsy (TLE) surgery outcome and its association with epilepsy duration, the presence of pre-surgical generalized tonic-clonic seizure (GTCS), and brain MRI findings. Materials & Methods: This retrospective study was perfo...

The goal of execution monitoring is to determine whether a system or person is fonowmg a plan appropriately. Monitoring information may be uncertain, and the plan being monitored may have complex temporal constraints. We develop a new framework for reasoning under uncertainty with quantitative temporal constraints Quantitative Temporal Dynamic Bayesian Networks and we discuss its application to...

The goal of execution monitoring is to determine whether a system or person is following a plan appropriately. Monitoring information may be uncertain, and the plan being monitored may have complex temporal constraints. We develop a new framework for reasoning under uncertainty with quantitative temporal constraints – Quantitative Temporal Bayesian Networks – and we discuss its application to p...