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Learning Disability Monitor

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Rekha Sugandhi, Tejaswini Kasture, Yash Gupta, Ashish Varghese
10.5120/ijca2017913069

Rekha Sugandhi, Tejaswini Kasture, Yash Gupta and Ashish Varghese. Learning Disability Monitor. International Journal of Computer Applications 160(6):37-42, February 2017. BibTeX

@article{10.5120/ijca2017913069,
	author = {Rekha Sugandhi and Tejaswini Kasture and Yash Gupta and Ashish Varghese},
	title = {Learning Disability Monitor},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {160},
	number = {6},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {37-42},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume160/number6/27081-2017913069},
	doi = {10.5120/ijca2017913069},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Autism refers to a group of brain development disorders, which are characterized by difficulty in communication and repetitive behaviors. Every autistic child is unique and hence each child should be given special care and attention for his or her development. In today’s world it is quite tedious and frustrating for teachers as well as parents to teach autistic children because they have to be taught repeatedly again and again. Due to this many parents actually accept the fact that their child cannot be taught or provided knowledge. Recent development in mobile technologies have provided teachers a better way to teach autistic children through a user friendly GUI and customizable systems deployed on mobile phones. Our proposed system eliminates the repetitive efforts required by teachers and parents by providing a customizable, adaptable and cost efficient system which adapts itself according to the behavior and learning of the child.

References

  1. N.H. Sweilam, A. Tharwat, A. Abdel, N. K. Moniem, “Support vector machine for diagnosis cancer disease”, Egyptian Informatics Journal , Volume (11), pp. 81–92, 2010.
  2. F. Heppner, U. Grenander, “A stochastic nonlinear model for coordinated bird flocks”, AAAS publications, Washington, 1990
  3. Tu, Chung-Jui, Li-Yeh Chuang, Jun-Yang Chang, and Cheng-Hong Yang. "Feature selection using PSO-SVM." IAENG International journal of computer science 33, no. 1 (2007): 111-116.
  4. B.T. Chen, M.Y. Chen, “Applying particles swarm optimization for support vector machines on predicting company financial crisis”, International Conference on Business and Economics Research, 2010.
  5. N. Arvanitopoulos, D. Bouzas, A. Tefas, “Subclass Error Correcting Output Codes Using Fisher’s Linear Discriminant Ratio, Pattern Recognition”, pp. 2953-2956, 2010.
  6. E.Alba, J. Garcıa-Nieto, L. Jourdan, E. Talbi, “Gene selection in Cancer Classification using PSO/SVM and GA/SVM Hybrid Algorithms”, Congress on Evolutionary Computation, 2007
  7. Smruti Rekha Das, Pradeepta Kumar Panigrahi, Kaberi Das,Debahuti Mishra, “Improving RBF Kernel Function of Support Vector Machine using Particle Swarm Optimizaton”, International Journal of Advanced Computer Research ,pp 2277-7970,Volume -2,Number -4,Issue-7,December-2012.
  8. M.S. Mythili, A.R.Mohamed Shanavas,”A Study on Autism Spectrum Disorders using classification Techniques”,IJSCE,ISSN:2231-2307,Volume 4,Issue 5,Nov 2014.
  9. MaryAnn Romski, PhD,CCC-SLP;Rose A.Sevcik,PhD,” Augmentative Communication And Early Intervention”, Vol. 18, No. 3, pp. 174-185,2005
  10. M.S. Mythili,, A.R.Mohamed Shanavas,” A Novel Approach to Predict the Learning Skills of Autistic Children using SVM and Decision Tree ”, Vol. 5 (6), 2014, 7288-729
  11. 11) C. E. Pugliese, L. Anthony, J. F. Strang, K. Dudley, G. L. Wallace, and L. Kenworthy, “Increasing Adaptive Behavior Skill Deficits From Childhood to Adolescence in Autism Spectrum Disorder: Role of Executive Function,” Journal of Autism and Developmental Disorders, vol. 45, no. 6, pp. 1579–1587, 2015.
  12. 12) D. A. Gómez-Aguilar, Á. Hernández-García, F. J. García-Peñalvo, and R. Therón, “Tap into visual analysis of customization of grouping of activities in eLearning,” Computers in Human Behavior, vol. 47, pp. 60–67, 2015.
  13. M. H. Charlop-Christy, L. Le, and K. A. Freeman, “A comparison of video modeling with in vivo modeling for teaching children with autism,” Journal of Autism and Developmental Disorders, vol. 30, no. 6, pp. 537–552, 2000.
  14. G. R. Hayes, S. Hirano, G. Marcu, M. Monibi, D. H. Nguyen, and M. Yeganyan, “Interactive visual supports for children with autism,” Personal and Ubiquitous Computing, vol. 14, no. 7, pp. 663–680, 2010.
  15. M. Monibi and G. R. Hayes, “Mocotos: Mobile communications tools for children with special needs,” in Proceedings of the 7th International Conference on Interaction Design and Children, IDC 2008, 2008, pp. 121–124.
  16. J. P. Hourcade, N. E. Bullock-Rest, and T. E. Hansen, “Multitouch tablet applications and activities to enhance the social skills of children with autism spectrum disorders,” Personal and Ubiquitous
  17. H. S. S. Yee, “Mobile technology for children with autism spectrum disorder: Major trends and issues,” presented at the 2012 IEEE Symposium on E-Learning, E-Management and E-Services, IS3e 2012, 2012, pp. 6–10.
  18. I. G. Careaga, Evaluación de la eficacia de las intervenciones psicoeducativas en los trastornos del espectro autista. Ministerio de Ciencia e Innovación, Instituto de Salud Carlos sIII, 2009.
  19. E. Husni and Budianingsih, “Mobile Applications BIUTIS: Let’s Study Vocabulary Learning as a Media for Children with Autism,” Procedia Technology, vol. 11, pp. 1147–1155, 2013
  20. S. Venkatesh, S. Greenhill, D. Phung, B. Adams, and T. Duong, “Pervasive multimedia for autism intervention,” Pervasive and Mobile Computing, vol. 8, no. 6, pp. 863–882, 2012.
  21. L. DeThorne, B. Aparicio, K. Karahalios, J. Halle, and E. Bogue, “Visualizing Syllables: Real-Time Computerized Feedback Within a Speech–Language Intervention,” Journal of Autism and Developmental Disorders, vol. 45, no. 11, pp. 3756–3763, 2015.
  22. L. Escobedo, D. H. Nguyen, L. A. Boyd, S. H. Hirano, A. Rangel, D García-Rosas, M. Tentori, and G. R. Hayes, “MOSOCO: A mobile assistive tool to support children with autism practicing social skills in real-life situations,” presented at the Conference on Human Factors in Computing Systems - Proceedings, 2012, pp. 2589–2598.
  23. S. Bernardini, K. Porayska-Pomsta, and T. J. Smith, “ECHOES: An intelligent serious game for fostering social communication in children with autism,” Information Sciences, vol. 264, pp. 41–60, 2014.
  24. J. Mintz, “Additional key factors mediating the use of a mobile technology tool designed to develop social and life skills in children with Autism Spectrum Disorders: Evaluation of the 2nd HANDS prototype,” Computers and Education, vol. 63, pp. 17–24, 2013..
  25. A. Lerna, D. Esposito, M. Conson, and A. Massagli, “Long-term effects of PECS on social-communicative skills of children with autism spectrum disorders: a follow-up study,” International journal of language & communication disorders / Royal College of Speech.
  26. B.H Sreenivasa Sarma and B.Ravindran “Intelligent tutoring systems using reinforcement learning to teach autistic children”thesis http://www.cse.iitm.ac.in/~ravi/papers/Sreenivas_thesis.pdf
  27. Evelyn Bartlett, Craig Lutz, Roger Bartlett (2012): My Socius
  28. Sayali D.Jadhav and H.P Channe” Comparative Study of K-NN, Naïve Bayes, Decision Tree Classification Techniques “International Journal of Science an d Research 319-7064

Keywords

Intelligent tutors, HCI, autism