Interactive topic models are powerful tools for understanding large collections of text. However, existing sampling-based interactive topic modeling approaches scale poorly to large data sets. Anchor methods, which use a single word to uniquely identify a topic, offer the speed needed for interactive work but lack both a mechanism to inject prior knowledge and lack the intuitive semantics neede...

We develop a novel interactive segmentation and 3-D visualization system for cone-beam computedtomography (CBCT) data in a personal computer environment. Its design includes both a new user interface to ease the interactive manual segmentation of the volume rendered and artifact-suppressing algorithms to improve the quality of CBCT images. Four pipelines of noise removal were carried out by app...

In this paper we propose an iterative learning algorithm based on observer and linear quadratic performance function. We calculate the initial control value for the iteractive learning algorithm based on the estimation of the states, which guarantees the efficient asymptotic tracking of any desired trajectories. Furthermore, with Linear quadratic optimal control theory, we obtain the optimized ...

In this paper, a program is presented that applies interactive evolution to sound generation, i.e., preferred individuals are repeatedly selected from a population of genetically bred sound objects, created with various synthesis and pattern generation algorithms. This simplifies aural exploration of huge synthesis parameter spaces, and presents a possibility for the sound artist to create new ...

By using the penalty function method with objective parameters, the paper presents an interactive algorithm to solve the inequality constrained multi-objective programming (MP). The MP is transformed into a single objective optimal problem (SOOP) with inequality constrains; and it is proved that, under some conditions, an optimal solution to SOOP is a Pareto efficient solution to MP. Then, an i...