Spatiotemporal companion pattern (STCP) mining is one of the means to identify and detect group behavioral activities. To spatiotemporal traveling ships from massive trajectory data understand movement law ships, this article proposes a feature-driven approach for STCP that consists (1) generating grid index via rasterizing geospace characterizing points sequences (STTGSs) ships; (2) designing ...

In the pursuit of increased safety the mining industry has worked to develop systems for remote control and autonomous operation of both stationary and mobile equipment. This paper reports on a newly developed system for teleoperation and autonomous tramming of LHD (Load-Haul-Dump) mining vehicles that not only increases the safety of the operators, but also has the potential to increase produc...

We use mathematical optimization to determine a production schedule (i.e., a schedule of extraction and subsequent filling of the voids) for a complex underground mine in Ireland. The goal of the mining operation is to maximize metal production over the life of the mine, subject to constraints on maximum monthly extraction and backfilling quantities, maximum and minimum monthly metal production...

Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has been noted recently that some of the infrequent patterns, such as negative associations and indirect associations, provide useful insight into the data. Existing indirect association mining algorithms mine indirect asso...

Academic rewards and honors are proven to correlate with h-index, although it was not the decision criterion for them till recent years. Once h-index becomes the rule-setting scientometric ranking measure in the zero-sum game for academic positions and research resources as suggested by its advocates, the rational behavior of competing academics is expected to converge towards its gametheoretic...

Stream data mining has gained a lot of attention over the last years due to an abundance of streaming data in professional as well as personal applications. Solutions have been proposed for many mining tasks such as clustering, classification, frequent item set mining and aggregation. Stream mining is especially challenging due to the large (usually endless) amount of data and the time constrai...

Research activity in data mining has been initially focused on defining efficient algorithms to perform the computationally intensive knowledge extraction task (i.e., itemset mining). The data to be analyzed was (possibly) extracted from the DBMS and stored into binary files. Proposed approaches for mining flat file data require a lot of memory and do not scale efficiently on large databases. A...

Determining the risk factors of a job is process that requires many studies. necessary to prevent accidents at work. The closing and greening Lupeni Mining Exploitation very complex one. closure mining operation done in stages for underground surface based on project. When implementing project, all occupational safety health regulations must be observed. As part operation, it redo factor assess...

An action that removes a few novel nontrivial data enclosed in large databases is defined as Data Mining. On noticing the statistical connections between the items that are more regular in the operation databases traditional data mining methods have spotlighted mostly. Numerous functions are using data mining in dissimilar fields like medical, marketing and so on commonly. Several methods and t...