The Standard for the Exchange of Earthquake Data (SEED) is a commonly used file format in the seismology field. Steim1 and Steim2 compression schemes, i.e. lossless data compressions, are used in SEED format and are written in Data Description Language (DDL), which has computational limitations making it difficult to implement many standard compression algorithms. Steim1 and Steim2 are fixed co...

Which samples should be labelled in a large dataset is one of the most important problems for training deep learning. So far, variety active sample selection strategies related to learning have been proposed literature. We defined them as Active Deep Learning (ADL) only if their predictor or selector model, where basic learner called and labeling schemes are selector. In this survey, we categor...

Current image retrieval systems have many important limitations. Many are specialized for a particular class of images and/or queries. The more general systems support relatively weak querying by content (e.g., by color, texture or shape, but with no deeper understanding of the structure of the image). Few (if any) have addressed the issue of truly large collections of images, and how the under...

High-performance SAT solvers based on systematic search generally use either conflict driven clause learning (CDCL) or lookahead techniques to gain efficiency. Both styles of reasoning can gain from a preprocessing phase in which some form of deduction is used to simplify the problem. In this paper we undertake an empirical examination of the effects of several recently proposed preprocessors o...

We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement learning to model the confidence and consistency of human feedback. This enables deep reinforcement learning algorithms to determine the most appropriate time to listen to the human feedback, exploit the current policy m...

Distributed Description Logics (DDL) is a KR formalism that enables reasoning with multiple ontologies interconnected by directional semantic mapping. Subsumption propagation in DDL from one ontology to another as a result of mappings has been studied, but only for a simplified case when only two ontologies are involved. In this paper we study subsumption propagation in more complex cases, when...

It is necessary to monitor, acquire, preprocess, and classify microseismic data understand active faults or other causes of earthquakes, thereby facilitating the preparation early-warning earthquake systems. Accordingly, this study proposes application machine learning for signal–noise classification from Pohang, South Korea. For first time, unique were obtained monitoring system borehole stati...