References
- H.-C. Kwon and S.-Y. Chae, "A study of the psychosocial impact of wheelchair use on physical disabilities", Disability & Employment, Vol. 20, pp. 33-50, 2010. https://doi.org/10.15707/disem.2010.20.1.002
- A. D. Marco, M. Russell, and M. Masters, "Standards for wheelchair prescription", Aust. Occup. Ther. J., Vol. 50, pp. 30-39, 2003. https://doi.org/10.1046/j.1440-1630.2003.00316.x
- S. Davolt, "The anodised, aerodynamic, ultralight, candy red wheelchair", PT Magazine of Physical Therapy, Vol. 4, pp. 6-11, 1996.
- S. Katsura and K. Ohnishi, "Semiautonomous wheelchair based on quarry of environmental information", IEEE Trans. Ind. Electron., Vol. 53, pp. 1373-1382, 2006.
- R. Simpson, E. Prestil, S. Hayashi, I. Nourbakhsh, and D. Miller, "The smart wheelchair component system", J. Rehabil. Res. Dev., Vol. 41, pp. 429-442, 2004. https://doi.org/10.1682/JRRD.2003.03.0032
- K. Wang, L. Zhang, B. Luan, H. Tung, Q. Liu, J. Wei, M. Sun, and Z. Mao, "Brain-computer interface combining eye saccade two-electrode EEG signals and voice cues to improve the maneuverability of wheelchair", Rehabilitation Robotics (ICORR), 2017 International Conference on, London, pp. 1073-1078, July 17-20, 2017.
- Z. Su, X. Xu, J. Ding, and W. Lu, "Intelligent wheelchair control system based on BCI and the image display of EEG", Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2016 IEEE, pp. 1350-1354, October 3-5, 2016.
- B.-H. Song, M.-A. Jung, and S.-R. Lee, "A design and implementation red tide prediction monitoring system using case based reasoning", The Korean Institute of Communications and Information Sciences, Vol. 35, pp.1219-1226, 2010.
- D. Zhuang, B. Zhang, Q. Yang, J. Yan, Z. Chen, and Y. Chen, "Efficient text classification by weighted proximal SVM", Data Mining, Fifth IEE International Conference on, Houston, Texas, November 27-30, 2005.
- J. Coetsier and R. Jiamthapthaksin, "Parallelized FPA-SVM: Parallelized parameter selection and classification using Flower Pollination Algorithm and Support Vector Machine", Computer Science and Software Engineering (JCSSE), 2017 14th International Joint Conference on, pp. 1-6, July 12-14, 2017.
- S. H. Park, I. M. Kim, S. T. Yoon, K. W. Park, and B. J. Go, "Implementation of the disaster monitoring system with PLC/CDMA environments", Journal of Advanced Navigation Technology, Vol. 14, pp. 824-828, 2010.
- S. Akbar, W. Kurniawan, M. Ichsan, I. Arwani, and M. Handono, "Pervasive device and service discovery protocol in XBee sensor network", Advanced Computer Science and Information Systems (ICACSIS), 2016 International Conference on, Malang, pp. 79-84, October 15-16, 2016.
- Q. Liu and C. Liu, "A Novel Locally Linear KNN Method With Applications to Visual Recognition", IEEE Trans. Neural Networks and Learning Systems, Vol. 28, No. 9, pp. 2010-2021, 2017.
- G. Morcous, H. Rivard, and A. M. Hanna, "Casebased reasoning system for modeling infrastructure deterioration", Journal of Computing in Civil Engineering, Vol. 16, pp. 104-114, 2002. https://doi.org/10.1061/(ASCE)0887-3801(2002)16:2(104)
- G. Finnie and Z. Sun, "Similarity and metrics in case-based reasoning", International Journal of Intelligent System, Vol. 17, pp. 273-287, 2002. https://doi.org/10.1002/int.10021