Change Detection Using Directional Statistics
Authors: Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The method is validated with real-world data from an ore mining system. |
| Researcher Affiliation | Industry | IBM Research, T. J. Watson Research Center 1101 Kitchawan Rd., Yorktown Heights, NY 10598, USA {tide,phandu,jayant}@us.ibm.com |
| Pseudocode | Yes | Algorithm 1 RED algorithm. |
| Open Source Code | No | The paper does not provide an explicit statement or link to open-source code for the described methodology. |
| Open Datasets | No | The paper uses 'real-world data from an ore mining system' which was 'generated by a testbed system' and 'synthetic three-dimensional time-series data', but does not provide any link, DOI, or formal citation for public access to these datasets. |
| Dataset Splits | No | The paper defines a 'training window' and 'test window' (Figure 1) and mentions determining (λ, ε) values using F-score on the test data, but does not explicitly provide a separate 'validation' dataset split with specific percentages or counts. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | For RED, we used (λ, ) = (1, 4), while for SSA we used D = 25. |